scikit-learn/scikit-learn

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https://github.com/scikit-learn/scikit-learn · scanned 2026-05-15 09:54 UTC (3 weeks ago) · 10 languages

548 findings (26 legacy + 522 scanner) 51st percentile · Python · large (100-500K LoC)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 3 weeks ago · v1 · 20 findings from 1 source. 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 2026-05-14-v3

Component	Sub-score	Weight	Contribution
`structure_score`	60.0	0.15	9.00
`security_score`	90.0	0.25	22.50
`testing_score`	95.0	0.20	19.00
`documentation_score`	65.0	0.15	9.75
`practices_score`	65.0	0.15	9.75
`code_quality`	50.0	0.10	5.00
Overall		1.00	75.0

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 0 High 13 Medium 3 Low 4 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Legacy 20 9-layer 0 Crowd 0 Layer: Security 5 Quality 15

Exclude dismissed / FP Exclude test files

Bug-class explainers. Each card groups findings of the same shape — these are the patterns most likely to ship to prod and reappear in future scans unless you systematically fix the cause, not just the instance.

Fragile runtime 14 findings

What it is: Code that runs but breaks under predictable input — division by zero, missing keys, unbounded loops, off-by-one slicing.

Why it matters: Reaches production undetected because happy-path tests pass. First user with a weird input crashes the request.

How AI causes it: AI loves writing the happy path; doesn't probe edge cases unless explicitly asked.

Fix approach: Add property-based tests. Wrap external inputs with explicit validators. Use the framework's typed deserializer (Pydantic, attrs).

12 matching findings on this repo

medium Duplicated implementation block across source files sklearn/externals/array_api_compat/numpy/_aliases…:56
medium Duplicated implementation block across source files sklearn/externals/array_api_compat/numpy/_aliases…:52
medium Duplicated implementation block across source files sklearn/externals/array_api_compat/dask/array/_in…:48
medium Duplicated implementation block across source files sklearn/externals/array_api_compat/dask/array/_al…:106
medium Duplicated implementation block across source files sklearn/ensemble/_voting.py:279
medium Duplicated implementation block across source files sklearn/ensemble/_stacking.py:501
medium Duplicated implementation block across source files sklearn/decomposition/_fastica.py:567
medium Duplicated implementation block across source files sklearn/datasets/_species_distributions.py:111
medium Duplicated implementation block across source files sklearn/datasets/_rcv1.py:111
medium Duplicated implementation block across source files sklearn/covariance/_shrunk_covariance.py:121
medium Duplicated implementation block across source files sklearn/covariance/_shrunk_covariance.py:120
medium Duplicated implementation block across source files sklearn/covariance/_robust_covariance.py:541

View all fragile runtime findings →

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