D4Vinci/Scrapling

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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)

https://github.com/D4Vinci/Scrapling · scanned 2026-06-04 04:11 UTC (1 day, 12 hours ago) · 10 languages

265 findings (131 legacy + 134 scanner) 73rd percentile · Python · medium (20-100K LoC) Scanner says 85 (lower by 8)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 day, 12 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.

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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

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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

Exclude dismissed / FP Exclude test files

Scan summary Repository scanned at 85.3/100 with 100.0% coverage. It contains 1802 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 67 findings — concentrated in quality (29), cicd (18), software (13). Risk profile is low: 0 critical, 0 high, 13 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

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