fix(security): audit — fix RUSTSEC vulns, clippy warnings, dead code (#769)

- Upgrade openssl to 0.10.78 (CVE-2026-41676), jsonwebtoken to 9.4
- Suppress unmaintained-only/no-CVE advisories in .cargo/audit.toml
  with per-entry rationale
- Fix all `cargo clippy --all-targets -- -D warnings` errors across
  35 crates: derivable_impls, needless_range_loop, map_or→is_some_and/
  is_none_or, await_holding_lock (drop MutexGuard before .await),
  ptr_arg (&mut Vec→&mut [T]), useless_conversion, approximate_constant
  (2.718→E, 3.14→PI), field_reassign_with_default, manual_inspect,
  useless_vec, lines_filter_map_ok, print_literal, dead_code
- Apply `cargo fmt --all`
- Pre-existing test failure in wifi-densepose-signal
  (test_estimate_occupancy_noise_only) is not introduced by this PR

v2/crates/cog-pose-estimation/src/config.rs

@@ -41,8 +41,8 @@ fn default_min_confidence() -> f32 {
 
 impl CogConfig {
     pub fn load(path: &Path) -> Result<Self, ConfigError> {
-        let raw = std::fs::read_to_string(path)
-            .map_err(|e| ConfigError::Read(path.to_path_buf(), e))?;
+        let raw =
+            std::fs::read_to_string(path).map_err(|e| ConfigError::Read(path.to_path_buf(), e))?;
         let cfg: CogConfig =
             serde_json::from_str(&raw).map_err(|e| ConfigError::Parse(path.to_path_buf(), e))?;
         Ok(cfg)

v2/crates/cog-pose-estimation/src/inference.rs

@@ -64,27 +64,51 @@ impl PoseNet {
             56,
             64,
             3,
-            Conv1dConfig { padding: 1, stride: 1, dilation: 1, groups: 1, ..Default::default() },
+            Conv1dConfig {
+                padding: 1,
+                stride: 1,
+                dilation: 1,
+                groups: 1,
+                ..Default::default()
+            },
             enc.pp("c1"),
         )?;
         let c2 = candle_nn::conv1d(
             64,
             128,
             3,
-            Conv1dConfig { padding: 2, stride: 1, dilation: 2, groups: 1, ..Default::default() },
+            Conv1dConfig {
+                padding: 2,
+                stride: 1,
+                dilation: 2,
+                groups: 1,
+                ..Default::default()
+            },
             enc.pp("c2"),
         )?;
         let c3 = candle_nn::conv1d(
             128,
             128,
             3,
-            Conv1dConfig { padding: 4, stride: 1, dilation: 4, groups: 1, ..Default::default() },
+            Conv1dConfig {
+                padding: 4,
+                stride: 1,
+                dilation: 4,
+                groups: 1,
+                ..Default::default()
+            },
             enc.pp("c3"),
         )?;
         let fc1 = candle_nn::linear(128, 256, head.pp("fc1"))?;
         let fc2 = candle_nn::linear(256, 34, head.pp("fc2"))?;
 
-        Ok(Self { c1, c2, c3, fc1, fc2 })
+        Ok(Self {
+            c1,
+            c2,
+            c3,
+            fc1,
+            fc2,
+        })
     }
 
     /// Forward pass: `[B, 56, 20]` -> `[B, 34]` in `[0, 1]`.

v2/crates/cog-pose-estimation/src/main.rs

@@ -89,14 +89,10 @@ fn cmd_manifest() -> Result<(), Box<dyn std::error::Error>> {
 
 fn cmd_health() -> Result<(), Box<dyn std::error::Error>> {
     let engine = InferenceEngine::new()?;
-    let synthetic = SyntheticInput::default();
+    let synthetic = SyntheticInput;
     let out = engine.infer(&synthetic.as_window())?;
     if out.is_finite() {
-        emit_event(&Event::health_ok(
-            COG_ID,
-            engine.backend(),
-            out.confidence,
-        ));
+        emit_event(&Event::health_ok(COG_ID, engine.backend(), out.confidence));
         Ok(())
     } else {
         Err("inference produced non-finite output".into())