Files
ruvnet--RuView/v2/crates/wifi-densepose-sensing-server
Dragan Spiridonov 7a05417493 fix(auth): scope gate was fail-OPEN; JWKS lock held across a blocking fetch
Two charges from an adversarial multi-vendor review (qe-court). Both verified
in source before fixing.

--- 1. AUTHORIZATION BYPASS: POST /api/v1/adaptive/train reachable with read ---

`required_scope_for` enumerated admin routes by prefix (`/api/v1/train/`, plus
DELETE on models/recording) and let EVERYTHING ELSE fall through to
`sensing:read`.

`POST /api/v1/adaptive/train` (main.rs:8112 -> handler main.rs:5028) calls
`adaptive_classifier::train_from_recordings()`, writes the model to disk with
`model.save()`, and swaps `state.adaptive_model` used by the live inference
pipeline. It does not start with `/api/v1/train/`, so it landed on
`sensing:read` — the scope `wifi-densepose login` requests BY DEFAULT. Exactly
the blast radius the read/admin split exists to prevent, reachable by the
lowest-privilege token the product issues.

Fixed by inverting the polarity, which is the real defect — a denylist for a
security gate keeps missing routes as routes keep being added:

  GET/HEAD/OPTIONS            -> sensing:read
  any other method            -> sensing:admin
  ...unless the exact path is in READ_SAFE_MUTATIONS (an explicit allowlist of
     mutations that change runtime state but destroy nothing: ws-ticket,
     model load/unload/activate, calibration start/stop, recording start/stop,
     vendor event ingest)

A mutating route added tomorrow is now admin-gated by default. Pinned by
`an_unknown_mutating_route_defaults_to_admin`. `POST /api/v1/ws-ticket` is
allowlisted deliberately and has its own test: were it admin, the read scope
could never open a stream from a browser at all.

Enumerated all 17 mutating /api/v1 routes to build the allowlist rather than
guessing. `POST /api/v1/config/ground-truth` now requires admin — a deliberate
tightening, it writes config.

--- 2. DoS: blocking JWKS fetch under std::sync::Mutex in async middleware ---

Filed INDEPENDENTLY by two prosecutors, which is why it gets fixed rather than
argued about.

`decoding_key_for` locked a `std::sync::Mutex` and held it across a blocking
`ureq` call (3s timeout, longer on a dead link), invoked from inside the async
`require_bearer`. `Mutex::lock()` in an async fn is a blocking syscall, not a
yield point — so one slow JWKS fetch blocked EVERY concurrent request on that
mutex, including ones carrying already-cached valid tokens, and parked the
tokio workers running them. On Pi-class hardware with few workers that stalls
the whole server. It fires on the routine 300s TTL rollover whenever the link
is degraded — the exact offline case the module exists to tolerate. Reachable
by anyone able to send a syntactically valid ES256 header with an unknown kid,
since kid lookup precedes signature verification.

Now three phases: read under the lock, RELEASE, network, re-take only to
install. Cost is a possible duplicated idempotent GET during a rollover, which
is strictly better than serialising every request behind one socket. The
codebase already uses spawn_blocking for outbound I/O elsewhere
(main.rs:2490, 5272); moving verification fully onto spawn_blocking remains a
follow-up — this removes the amplification, not every blocking millisecond.

Tests: 533 sensing-server (7 new scope-polarity), 82 ruview-auth.

Co-Authored-By: Ruflo & AQE
2026-07-23 09:18:33 +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