Files
ruvnet--RuView/v2/crates/wifi-densepose-sensing-server
Dragan Spiridonov 347698b67c feat(auth): browser sign-in — /oauth/start, /oauth/callback, session cookie
Closes the gap adversarial review found: `wifi-densepose login` writes
~/.ruview/credentials.json, which a BROWSER CANNOT READ. The UI therefore had no
way to obtain a Cognitum token at all, and the WebSocket ticket mechanism
ADR-272 built "for browsers" was only exercisable with the legacy static shared
secret OAuth was meant to replace. The ADRs described a browser story that did
not exist.

Ported from cognitum-one/freetokens (src/auth/oauth.ts, live at
freetokens.cognitum.one), whose shape is not the obvious one and is the whole
point:

  THE BROWSER NEVER HOLDS AN OAUTH TOKEN.

The server generates the PKCE verifier and state, keeps them in an HMAC-signed
cookie, performs the code exchange itself, verifies the token, and issues its
OWN session cookie carrying an assertion — subject, account, scope, expiry — not
a credential. So the access token cannot be read by an XSS, cannot sit in
localStorage, and cannot leak through a URL. A stolen session cookie is useless
against Cognitum or any sibling service.

  GET /oauth/start    -> 302 to auth.cognitum.one + signed transaction cookie
  GET /oauth/callback -> constant-time state check, exchange, verify, session
  GET /oauth/logout   -> clears the local session (not the Cognitum session)

Verified against the running binary: /oauth/start returns the same 302 +
HttpOnly/SameSite=Lax/Max-Age=600 shape freetokens does live; a forged `state`
is refused 400; a forged session cookie is refused 401.

DELIBERATE DEVIATION from freetokens: no `__Host-` cookie prefix. That prefix
REQUIRES `Secure`, and RuView is routinely reached at http://localhost or over
plain HTTP on a LAN, where such a cookie is never sent and sign-in would fail
silently. `Secure` is set only when the request actually arrived over TLS
(direct or via x-forwarded-proto). Every other attribute matches; the HMAC is
what protects the value.

Other decisions worth stating:
- The callback verifies through the SAME `verify_access_token` every other
  request uses — signature, audience (client_id), typ, expiry, scope. A sign-in
  path must not be a softer path.
- The session cookie is checked LAST in the middleware, after bearer and ticket:
  it is the weakest-bound credential, so a presented bearer should win.
- A browser session requests `sensing:read` only. Admin work goes through the
  CLI's explicit `--admin`.
- The token exchange runs in `spawn_blocking` — `ureq` is blocking, and parking
  an async worker is the mistake this codebase just had to fix in jwks.rs.
- `/oauth/*` sits outside `/api/v1/*` on purpose: gating the routes you use to
  obtain a credential would deadlock.

PKCE moved out from behind the `login` feature into its own light `pkce` feature
(rand + sha2 + base64, no HTTP stack), so the server can build an authorize URL
without pulling in the client-side login machinery. `login` now implies `pkce`.

Tests: 13 new browser_session unit tests — signature round-trip, tampered
payload, wrong secret, malformed cookie values, HttpOnly/SameSite/Secure
attributes, exact scope matching with no implied escalation, a cookie name that
merely ends with the target not matching, multi-scope URL encoding, and the
core property that a session cookie never contains the access token.
Totals: 547 sensing-server lib + 5 wiring integration, 87 ruview-auth.

Co-Authored-By: Ruflo & AQE
2026-07-23 09:57:15 +02:00
..

wifi-densepose-sensing-server

Crates.io Documentation License

Lightweight Axum server for real-time WiFi sensing with RuVector signal processing.

Overview

wifi-densepose-sensing-server is the operational backend for WiFi-DensePose. It receives raw CSI frames from ESP32 hardware over UDP, runs them through the RuVector-powered signal processing pipeline, and broadcasts processed sensing updates to browser clients via WebSocket. A built-in static file server hosts the sensing UI on the same port.

The crate ships both a library (wifi_densepose_sensing_server) exposing the training and inference modules, and a binary (sensing-server) that starts the full server stack.

Integrates wifi-densepose-wifiscan for multi-BSSID WiFi scanning per ADR-022 Phase 3.

Features

  • UDP CSI ingestion -- Receives ESP32 CSI frames on port 5005 and parses them into the internal CsiFrame representation.
  • Vital sign detection -- Pure-Rust FFT-based breathing rate (0.1--0.5 Hz) and heart rate (0.67--2.0 Hz) estimation from CSI amplitude time series (ADR-021).
  • RVF container -- Standalone binary container format for packaging model weights, metadata, and configuration into a single .rvf file with 64-byte aligned segments.
  • RVF pipeline -- Progressive model loading with streaming segment decoding.
  • Graph Transformer -- Cross-attention bottleneck between antenna-space CSI features and the COCO 17-keypoint body graph, followed by GCN message passing (ADR-023 Phase 2). Pure std, no ML dependencies.
  • SONA adaptation -- LoRA + EWC++ online adaptation for environment drift without catastrophic forgetting (ADR-023 Phase 5).
  • Contrastive CSI embeddings -- Self-supervised SimCLR-style pretraining with InfoNCE loss, projection head, fingerprint indexing, and cross-modal pose alignment (ADR-024).
  • Sparse inference -- Activation profiling, sparse matrix-vector multiply, INT8/FP16 quantization, and a full sparse inference engine for edge deployment (ADR-023 Phase 6).
  • Dataset pipeline -- Training dataset loading and batching.
  • Multi-BSSID scanning -- Windows netsh integration for BSSID discovery via wifi-densepose-wifiscan (ADR-022).
  • WebSocket broadcast -- Real-time sensing updates pushed to all connected clients at ws://localhost:8765/ws/sensing.
  • Static file serving -- Hosts the sensing UI on port 8080 with CORS headers.

Modules

Module Description
vital_signs Breathing and heart rate extraction via FFT spectral analysis
rvf_container RVF binary format builder and reader
rvf_pipeline Progressive model loading from RVF containers
graph_transformer Graph Transformer + GCN for CSI-to-pose estimation
trainer Training loop orchestration
dataset Training data loading and batching
sona LoRA adapters and EWC++ continual learning
sparse_inference Neuron profiling, sparse matmul, INT8/FP16 quantization
embedding Contrastive CSI embedding model and fingerprint index

Quick Start

# Build the server
cargo build -p wifi-densepose-sensing-server

# Run with default settings (HTTP :8080, UDP :5005, WS :8765)
cargo run -p wifi-densepose-sensing-server

# Run with custom ports
cargo run -p wifi-densepose-sensing-server -- \
    --http-port 9000 \
    --udp-port 5005 \
    --static-dir ./ui

Using as a library

use wifi_densepose_sensing_server::vital_signs::VitalSignDetector;

// Create a detector with 20 Hz sample rate
let mut detector = VitalSignDetector::new(20.0);

// Feed CSI amplitude samples
for amplitude in csi_amplitudes.iter() {
    detector.push_sample(*amplitude);
}

// Extract vital signs
if let Some(vitals) = detector.detect() {
    println!("Breathing: {:.1} BPM", vitals.breathing_rate_bpm);
    println!("Heart rate: {:.0} BPM", vitals.heart_rate_bpm);
}

Architecture

ESP32 ──UDP:5005──> [ CSI Receiver ]
                          |
                    [ Signal Pipeline ]
                    (vital_signs, graph_transformer, sona)
                          |
                    [ WebSocket Broadcast ]
                          |
Browser <──WS:8765── [ Axum Server :8080 ] ──> Static UI files
Crate Role
wifi-densepose-wifiscan Multi-BSSID WiFi scanning (ADR-022)
wifi-densepose-core Shared types and traits
wifi-densepose-signal CSI signal processing algorithms
wifi-densepose-hardware ESP32 hardware interfaces
wifi-densepose-wasm Browser WASM bindings for the sensing UI
wifi-densepose-train Full training pipeline with ruvector
wifi-densepose-mat Disaster detection module

License

MIT OR Apache-2.0