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Scan timing: clone 15.51s · analysis 4.97s · 20.3 MB · GitHub API rate-limit (preflight)

LernerLab/GuPPy

https://github.com/LernerLab/GuPPy · scanned 2026-06-05 17:54 UTC (4 days, 21 hours ago) · 10 languages

305 raw signals (115 security + 190 graph) 92nd percentile · Python · medium (20-100K LoC) System graph score 89 (lower by 4)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 4 days, 21 hours ago · v2 · 128 actionable findings from 2 signal sources. 57 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON
Combined
88.0
/100
Security checks
87
48 findings
System graph
89
77.8% cov · 80 findings
Critical
0
click to filter
Agents
6
0 votes
Crowd
0
reported
Score breakdown â 2026-05-18-v5
Component Sub-score Weight Contribution
structure_score 85.0 0.15 12.75
security_score 91.0 0.25 22.75
testing_score 100.0 0.20 20.00
documentation_score 93.0 0.15 13.95
practices_score 75.0 0.15 11.25
code_quality 39.2 0.10 3.92
Overall 1.00 84.6
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 0 High 5 Medium 6 Low 67 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 48 System graph 80 Crowd 0 Layer: Quality 95 Security 3 Software 22 Cicd 6 Api 1 Frontend 1
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/.
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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: 
    POST /api/v1/agents/feedback/
{"agent_token": "...", "repo_id": 1149, "gap_fingerprint": "...",
 "vote": "false_positive", "reason": "test fixture, not a credential"}
  3. Report a finding we missed. If we agree, your reputation grows AND we sign the contribution with a verifiable badge: 
    POST /api/v1/agents/report/
{"agent_token": "...", "repo_id": 1149, "title": "...",
 "severity": "high", "layer": "security", "file": "x.py", "line": 12,
 "suggested_detector": "regex: ..."}
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