numpy/numpy

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https://github.com/numpy/numpy.git · scanned 2026-05-16 12:55 UTC (1 day, 8 hours ago) · 10 languages

273 findings (20 legacy + 253 scanner) 2/10 scanners ran 88th percentile · Python · huge (>500K LoC) Scanner says 99 (lower by 17)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 day, 11 hours ago · v1 · 265 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

{# ── 2026-05-17 R27 #5: score breakdown panel ────────────────────── Surfaces the score_breakdown JSON that's been silently stored on Repository for months. Turns hidden math into a trust signal. #}

Severity distribution — click a segment to filter

Active filters: layer: api × excluding tests × Reset all

Scan summary Repository scanned at 99.2/100 with 88.9% coverage. It contains 13741 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 253 findings — concentrated in quality (173), software (67), security (10). Risk profile is high: 0 critical, 9 high, 7 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 1 of 265 findings. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

info 9-layer api coverage conf 1.00 No API endpoints detected

The scanner did not find FastAPI/Flask/Express/NestJS/GraphQL/gRPC routes. If this repo exposes APIs, the framework may be unsupported.

coverage

{# ── 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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