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numpy/numpy

https://github.com/numpy/numpy.git · scanned 2026-05-16 12:55 UTC (1 day, 9 hours ago) · 10 languages

273 findings (20 legacy + 253 scanner) 2/10 scanners ran 75th 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
Combined
89.9
/100
Repobility
81
12 legacy
9-layer
99
88.9% cov · 253 gaps
Critical
0
click to filter
Agents
6
0 votes
Crowd
0
reported
{# ── 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: security × excluding tests × Reset all
Severity: Critical 0 High 14 Medium 14 Low 182 Source: Legacy 12 9-layer 253 Crowd 0 Layer: Software 69 Security 16 Quality 177 Api 1 Frontend 1 Cicd 1
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 15 of 265 findings. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

high Legacy security path_traversal conf 0.80 [SEC013] Path Traversal — User Input in File Path: User-controlled input used in file path without sanitization. Allows reading arbitrary files.
Use os.path.realpath() and verify the path starts with your expected base directory. Use secure_filename() for uploads.
numpy/linalg/lapack_lite/clapack_scrub.py:307 path_traversallegacy
high 9-layer security owasp conf 1.00 Insecure pattern 'eval_used' in benchmarks/benchmarks/bench_ma.py:141
Found a known-risky pattern (eval_used). Review and replace if possible.
benchmarks/benchmarks/bench_ma.py:141 owaspeval_used
high 9-layer security owasp conf 1.00 Insecure pattern 'eval_used' in numpy/_build_utils/tempita/_tempita.py:320
Found a known-risky pattern (eval_used). Review and replace if possible.
numpy/_build_utils/tempita/_tempita.py:320 owaspeval_used
high 9-layer security owasp conf 1.00 Insecure pattern 'eval_used' in numpy/f2py/auxfuncs.py:632
Found a known-risky pattern (eval_used). Review and replace if possible.
numpy/f2py/auxfuncs.py:632 owaspeval_used
high 9-layer security owasp conf 1.00 Insecure pattern 'eval_used' in numpy/f2py/capi_maps.py:159
Found a known-risky pattern (eval_used). Review and replace if possible.
numpy/f2py/capi_maps.py:159 owaspeval_used
high 9-layer security owasp conf 1.00 Insecure pattern 'exec_used' in benchmarks/benchmarks/bench_indexing.py:29
Found a known-risky pattern (exec_used). Review and replace if possible.
benchmarks/benchmarks/bench_indexing.py:29 owaspexec_used
high 9-layer security owasp conf 1.00 Insecure pattern 'exec_used' in numpy/_build_utils/tempita/_tempita.py:335
Found a known-risky pattern (exec_used). Review and replace if possible.
numpy/_build_utils/tempita/_tempita.py:335 owaspexec_used
high 9-layer security owasp conf 1.00 Insecure pattern 'tls_verify_false' in numpy/_core/multiarray.py:112
Found a known-risky pattern (tls_verify_false). Review and replace if possible.
numpy/_core/multiarray.py:112 owasptls_verify_false
high 9-layer security owasp conf 1.00 Insecure pattern 'tls_verify_false' in numpy/lib/_ufunclike_impl.py:18
Found a known-risky pattern (tls_verify_false). Review and replace if possible.
numpy/lib/_ufunclike_impl.py:18 owasptls_verify_false
medium Legacy security injection conf 0.50 [SEC005] Command Injection Risk: Unsafe shell execution or eval of user input.
Use subprocess with shell=False and a list of args. Never eval user input.
tools/write_release.py:54 injectionlegacy
medium Legacy security deserialization conf 1.00 [SEC007] Unsafe Deserialization: Unsafe deserialization can execute arbitrary code.
Use yaml.safe_load() instead of yaml.load(). Avoid pickle for untrusted data.
numpy/_core/src/multiarray/methods.c:2110 deserializationlegacy
medium Legacy security deserialization conf 1.00 [SEC007] Unsafe Deserialization: Unsafe deserialization can execute arbitrary code.
Use yaml.safe_load() instead of yaml.load(). Avoid pickle for untrusted data.
numpy/_core/src/multiarray/multiarraymodule.c:2207 deserializationlegacy
medium Legacy security deserialization conf 1.00 [SEC007] Unsafe Deserialization: Unsafe deserialization can execute arbitrary code.
Use yaml.safe_load() instead of yaml.load(). Avoid pickle for untrusted data.
numpy/_core/records.py:703 deserializationlegacy
medium Legacy security crypto conf 1.00 [SEC014] SSL Verification Disabled: SSL certificate verification is disabled, allowing man-in-the-middle attacks.
Enable SSL verification. Use verify=True (default) for requests. Pin certificates if needed.
numpy/_core/multiarray.py:112 cryptolegacy
medium 9-layer security coverage conf 1.00 No auth library detected
The scanner did not find any standard auth library (JWT, OAuth, NextAuth, Auth0, etc.). Either auth lives in custom code, in a separate service, or is missing.
coverageauth
{# ── 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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