mirror of
https://github.com/ruvnet/RuView
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347698b67c
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
wifi-densepose-sensing-server
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
CsiFramerepresentation. - 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
.rvffile 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
netshintegration for BSSID discovery viawifi-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
Related Crates
| 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