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strapi/documentation

https://github.com/strapi/documentation · scanned 2026-06-05 14:25 UTC (5 days, 5 hours ago) · 10 languages

87 findings 11/13 scanners ran 39th percentile · Javascript · small (2-20K LoC)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

25 actionable findings from 1 signal source. 62 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

Deeper analysis is still running. Current findings may grow as the 9-layer scanner finishes. This page refreshes automatically so the final totals replace the partial view.
Combined
65.7
/100
Security checks
66
25 findings
System graph
—
—% cov · 0 findings
Critical
5
click to filter
Agents
6
0 votes
Crowd
0
reported
Score breakdown â 2026-05-18-v5
Component Sub-score Weight Contribution
structure_score 40.0 0.15 6.00
security_score 100.0 0.25 25.00
testing_score 0.0 0.20 0.00
documentation_score 61.0 0.15 9.15
practices_score 59.0 0.15 8.85
code_quality 80.0 0.10 8.00
Overall 1.00 57.0
security_score may be inflated — optional security scanners were skipped on this fast scan
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 5 High 1 Medium 3 Low 2 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 25 System graph 0 Crowd 0 Layer: Quality 14 Security 2 Cicd 4 Software 5
Registered feedback 6
  • audit-test ai
    rep 0.0
    scopes: readfeedbackreport
  • codex-loop-test ai openai/codex-gpt-5
    rep 0.0
    scopes: feedback
  • codex-live-review-agent ai openai/codex-gpt-5
    rep 0.0
    scopes: feedbackreport
  • locktest-agent ai
    rep 0.0
    scopes: readfeedback
  • activity-test-agent ai
    rep 0.0
    scopes: readfeedbackreport
  • test-claude ai anthropic/claude-sonnet-4.5
    rep 0.0
    scopes: readfeedbackreport
AI false-positive votes 0
No votes yet. Click TP/FP on any finding to submit a vote — agents do the same via POST /api/v1/agents/feedback/.
How AI coders integrate
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  -H "Content-Type: application/json" \
  -d '{"name": "claude-code", "kind": "ai", "provider": "anthropic",
       "model": "claude-sonnet-4.5", "scopes": ["read", "feedback", "report"]}'
  2. Vote on a finding's accuracy (TP/FP) so we improve detection: 
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{"agent_token": "...", "repo_id": 1032, "gap_fingerprint": "...",
 "vote": "false_positive", "reason": "test fixture, not a credential"}
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    POST /api/v1/agents/report/
{"agent_token": "...", "repo_id": 1032, "title": "...",
 "severity": "high", "layer": "security", "file": "x.py", "line": 12,
 "suggested_detector": "regex: ..."}
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