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openhuman

https://github.com/tinyhumansai/openhuman · scanned 2026-05-17 19:50 UTC (33 minutes ago) · 10 languages

1415 findings (74 legacy + 1341 scanner) 8/10 scanners ran Scanner says 79 (lower by 18)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 33 minutes ago · v3 · last Δ -0.1 (diff) · 525 findings from 2 sources. Findings combine the legacy security pipeline AND the multi-layer engine (atlas, wiring, flows, ranked) AND verified AI agent contributions.

JSON
Combined
67.3
/100
Repobility
56
74 legacy
9-layer
79
100.0% cov · 451 gaps
Critical
2
click to filter
Agents
6
0 votes
Crowd
0
reported
{# ── 2026-05-17 R27 #5: score breakdown panel ────────────────────── Surfaces the score_breakdown JSON that's been silently stored on Repository for months. Turns hidden math into a trust signal. #}
Score breakdown â 2026-05-17-v4 calibration-aware
Component Sub-score Weight Contribution
structure_score 85.0 0.15 12.75
security_score 21.5 0.25 5.38
testing_score 81.0 0.20 16.20
documentation_score 75.0 0.15 11.25
practices_score 75.0 0.15 11.25
code_quality 43.0 0.10 4.30
Overall 1.00 61.1
Calibrated penalty buckets (security_score): agent: 8.1 · authz: 4.6 · docker: 15.3 · threat: 37.0 · journey: 13.5
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 2 High 15 Medium 110 Low 276 Source: Legacy 74 9-layer 451 Crowd 0 Layer: Security 19 Quality 205 Software 54 Cicd 157 Api 1 Frontend 79 Hardware 10

Bug-class explainers. Each card groups findings of the same shape — these are the patterns most likely to ship to prod and reappear in future scans unless you systematically fix the cause, not just the instance.

Fragile runtime 47 findings
What it is: Code that runs but breaks under predictable input — division by zero, missing keys, unbounded loops, off-by-one slicing.
Why it matters: Reaches production undetected because happy-path tests pass. First user with a weird input crashes the request.
How AI causes it: AI loves writing the happy path; doesn't probe edge cases unless explicitly asked.
Fix approach: Add property-based tests. Wrap external inputs with explicit validators. Use the framework's typed deserializer (Pydantic, attrs).
12 matching findings on this repo
  • medium localStorage write failures are swallowed silently app/src/store/index.ts:54
  • medium localStorage write failures are swallowed silently app/src/pages/onboarding/components/BetaBanner.tsx:22
  • medium Ollama audio payload path may mislead users about direct model audio app/src/pages/Conversations.tsx:753
  • medium localStorage write failures are swallowed silently app/src/components/settings/panels/AgentChatPanel…:48
  • medium [ERR002] Empty Catch Block: Empty catch blocks hide errors. app/src-tauri/src/meet_audio/captions_bridge.js:158
  • medium [ERR002] Empty Catch Block: Empty catch blocks hide errors. app/src-tauri/src/meet_audio/audio_bridge.js:209
  • medium [ERR002] Empty Catch Block: Empty catch blocks hide errors. app/src-tauri/recipes/google-meet/recipe.js:47
  • medium localStorage write failures are swallowed silently app/src/store/userScopedStorage.ts:46
  • medium localStorage write failures are swallowed silently app/src/overlay/OverlayApp.tsx:412
  • medium Parallel implementation file sits beside a canonical file src/openhuman/memory/tree/canonicalize/email_clea…:1
  • medium Parallel implementation file sits beside a canonical file remotion/src/Mascot/mascot-yellow-wave-alt.tsx:1
  • low Duplicated implementation block across source files app/src/components/settings/panels/TeamMembersPan…:112
View all fragile runtime findings →
Legacy markers 4 findings
What it is: TODO, FIXME, XXX, HACK comments. Often indicate a known-broken path the author meant to fix.
Why it matters: Each marker is an unfinished thought. Production code shouldn't ship with debt that's documented but not tracked.
How AI causes it: AI mirrors the style of the codebase, so existing TODOs propagate into new code.
Fix approach: Convert each into a ticket. Delete the comment when the ticket lands. Use a pre-commit hook to block new TODOs without an issue link.
4 matching findings on this repo
  • low Legacy-named symbol `content_copy` in app/src-tauri/recipes/google-meet/recipe.…
  • low Legacy-named symbol `origLegacy` in app/src-tauri/src/meet_audio/audio_bridge.j…
  • low Legacy-named symbol `openhuman_device_fingerprint_v1` in app/src/utils/deviceFi…
  • low Legacy-named symbol `scribe_v1` in app/src/features/human/voice/sttClient.test.…
View all legacy markers findings →
Commented-out code 95 findings
What it is: Lines of source that were intentionally disabled but never deleted.
Why it matters: Git already remembers history — commented code rots, becomes wrong, and adds noise to diffs.
How AI causes it: AI sometimes comments out broken code instead of fixing it. Reviewers approve out of inertia.
Fix approach: Delete. Trust `git log`. If you really need to remember, save it in a notes file under `docs/`.
12 matching findings on this repo
  • info Commented-code block (9 lines) in scripts/prepareTauriConfig.js:5
  • info Commented-code block (6 lines) in app/vite.config.ts:58
  • info Commented-code block (5 lines) in app/test/OAuthLoginSection.test.tsx:21
  • info Commented-code block (6 lines) in app/test/vitest.config.ts:59
  • info Commented-code block (5 lines) in app/test/e2e/helpers/app-helpers.ts:32
  • info Commented-code block (6 lines) in app/test/e2e/helpers/deep-link-helpers.ts:204
  • info Commented-code block (5 lines) in app/test/e2e/specs/chat-harness-send-stream.s…
  • info Commented-code block (5 lines) in app/test/e2e/specs/rewards-unlock-flow.spec.t…
  • info Commented-code block (11 lines) in app/test/e2e/specs/smoke.spec.ts:42
  • info Commented-code block (6 lines) in app/test/e2e/specs/whatsapp-flow.spec.ts:103
  • info Commented-code block (5 lines) in app/test/e2e/specs/slack-flow.spec.ts:95
  • info Commented-code block (7 lines) in app/test/e2e/specs/insights-dashboard.spec.ts…
View all commented-out code findings →
Config drift 13 findings
What it is: Settings duplicated across env files, Docker compose, K8s, and code defaults, all with slightly different values.
Why it matters: Production behaviour depends on whichever copy your loader reads first. Subtle bugs in staging that don't reproduce in dev.
How AI causes it: AI writes new config from memory rather than reading the existing source.
Fix approach: Pick one source of truth (env vars + a settings module). Have every other place import from there. Lint for duplicates in CI.
12 matching findings on this repo
  • low File has no detected symbols: remotion/remotion.config.ts
  • low File has no detected symbols: app/tailwind.config.js
  • low File has no detected symbols: app/eslint.config.js
  • low File has no detected symbols: app/postcss.config.js
  • low File has no detected symbols: app/test/vitest.config.ts
  • low Very large file: src/openhuman/config/schemas.rs (1338 lines)
  • low Very large file: src/openhuman/config/schema/load.rs (1656 lines)
  • info Commented-code block (9 lines) in scripts/prepareTauriConfig.js:5
  • info Commented-code block (6 lines) in app/vite.config.ts:58
  • info Commented-code block (6 lines) in app/test/vitest.config.ts:59
  • medium `fetch()` without try/.catch or AbortSignal — app/src/utils/config.ts:41
  • info Commented-code block (6 lines) in app/src/utils/configPersistence.ts:18
View all config drift findings →
{# ── 2026-05-17 Round 14: AI-agent bridge footer ────────────────────── Discoverability: the /agents/voting/ guide + MCP manifest exist but aren't linked from anywhere users actually land. Small, opt-in footer. #}
For AI agents: Voting guide (TP/FP) MCP manifest Stdio wrapper SARIF Integrate Findings queue Vote TP/FP on findings to calibrate the engine.
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