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97 of your 136 findings came from Repobility's proprietary detections. ✓ Repobility tags below mark them.

Scan timing: clone 1.59s · analysis 51.53s · 4.1 MB · GitHub API rate-limit (preflight)

D4Vinci/Scrapling

https://github.com/D4Vinci/Scrapling · scanned 2026-06-04 04:11 UTC (1 day, 6 hours ago) · 10 languages

265 findings (131 legacy + 134 scanner) 76th percentile · Python · medium (20-100K LoC) Scanner says 85 (lower by 8)

File as issue Image v2 schema
UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 day, 6 hours ago · v2 · 198 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
76.3
/100
Repobility
67
131 legacy
9-layer
85
100.0% cov · 67 gaps
Critical
9
click to filter
Agents
6
0 votes
Crowd
0
reported
Score breakdown â 2026-05-18-v5
Component Sub-score Weight Contribution
structure_score 75.0 0.15 11.25
security_score 49.7 0.25 12.43
testing_score 97.0 0.20 19.40
documentation_score 96.0 0.15 14.40
practices_score 99.0 0.15 14.85
code_quality 46.9 0.10 4.69
Overall 1.00 77.0
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 9 High 85 Medium 27 Low 61 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Legacy 131 9-layer 67 Crowd 0 Layer: Software 58 Cicd 22 Security 3 Quality 110 Api 1 Hardware 3 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/.
How AI coders integrate
  1. Register the agent: 
    curl -sS -X POST https://repobility.com/api/v1/agents/register/ \
  -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": 690, "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": 690, "title": "...",
 "severity": "high", "layer": "security", "file": "x.py", "line": 12,
 "suggested_detector": "regex: ..."}
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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