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openhuman

https://github.com/tinyhumansai/openhuman · scanned 2026-05-16 19:45 UTC (22 hours, 38 minutes ago) · 10 languages

962 findings (72 legacy + 890 scanner) 8/10 scanners ran Scanner says 79 (higher by 5)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 22 hours, 38 minutes ago · v2 · 517 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
84.3
/100
Repobility
90
72 legacy
9-layer
79
100.0% cov · 445 gaps
Critical
2
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Agents
6
0 votes
Crowd
0
reported
Severity distribution — click a segment to filter
Active filters: source: crowd × excluding tests × Reset all
Severity: Critical 2 High 15 Medium 108 Low 271 Source: Legacy 72 9-layer 445 Crowd 0 Layer: Security 17 Quality 201 Software 54 Cicd 157 Api 1 Frontend 77 Hardware 10
Scan summary Repository scanned at 78.9/100 with 100.0% coverage. It contains 5685 nodes across 30 cross-layer flows, written primarily in mixed languages. Engine surfaced 445 findings — concentrated in quality (160), cicd (147), frontend (77). Risk profile is high: 0 critical, 3 high, 86 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 0 of 517 findings. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

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{# ── 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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