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NVIDIA/garak

https://github.com/NVIDIA/garak · scanned 2026-05-15 16:00 UTC (2 weeks, 6 days ago) · 10 languages

169 findings (18 legacy + 151 scanner) 82nd percentile · Python · medium (20-100K LoC) Scanner says 76 (higher by 3)

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 weeks, 6 days ago · v1 · 13 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 2026-05-17-v4 calibration-aware
Component Sub-score Weight Contribution
structure_score 60.0 0.15 9.00
security_score 83.5 0.25 20.88
testing_score 100.0 0.20 20.00
documentation_score 81.0 0.15 12.15
practices_score 65.0 0.15 9.75
code_quality 73.1 0.10 7.31
Overall 1.00 79.1
Calibrated penalty buckets (security_score): threat: 16.5
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Scan summary Repository scanned at 76.3/100 with 100.0% coverage. It contains 2975 nodes across 3 cross-layer flows, written primarily in mixed languages. Engine surfaced 0 findings. Risk profile is low: 0 critical, 0 high, 0 medium. Recommended next step: open the software layer findings first — that's where the highest-impact wins live.

Showing 12 of 13 findings. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

high Legacy software dependency [BINARY] scipy: compound risk score 2194 (CVEs: 0, binary findings: 550)
Review binary security profile of scipy — consider alternatives with lower binary attack surface
dependencylegacy
high Legacy security injection conf 0.50 [SEC004] SQL Injection Risk: String interpolation in SQL execution. Allows SQL injection.
Use parameterized queries: cursor.execute('SELECT * FROM t WHERE id = %s', [id]). For dynamic table or column names, choose identifiers from a hard-coded allowlist and keep values in parameters.
garak/cli.py:563 injectionlegacy
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.
tools/packagehallucination/ruby/main.py:43 path_traversallegacy
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.
tools/packagehallucination/javascript/main.py:45 path_traversallegacy
medium Legacy quality error_handling conf 1.00 [ERR001] Silent Exception Swallowing: Silently swallowing all exceptions hides bugs. Even in cleanup code, log at DEBUG level.
Log the error: `except Exception: logger.debug('cleanup failed', exc_info=True)`. Or handle specific exception types.
garak/evaluators/base.py:309 error_handlinglegacy
medium Legacy quality error_handling conf 1.00 [ERR001] Silent Exception Swallowing: Silently swallowing all exceptions hides bugs. Even in cleanup code, log at DEBUG level.
Log the error: `except Exception: logger.debug('cleanup failed', exc_info=True)`. Or handle specific exception types.
garak/detectors/exploitation.py:128 error_handlinglegacy
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.
garak/generators/websocket.py:245 cryptolegacy
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.
garak/generators/rest.py:210 cryptolegacy
high Legacy quality quality conf 0.86 Duplicated implementation block across source files
Duplicated blocks are a common artifact when generated code is pasted or recreated instead of reused. They increase maintenance cost because every future bug fix must be found in multiple locations.
garak/probes/fitd.py:84 qualitylegacy
high Legacy quality quality conf 0.86 Duplicated implementation block across source files
Duplicated blocks are a common artifact when generated code is pasted or recreated instead of reused. They increase maintenance cost because every future bug fix must be found in multiple locations.
garak/analyze/qual_review.py:160 qualitylegacy
high Legacy quality quality conf 0.86 Duplicated implementation block across source files
Duplicated blocks are a common artifact when generated code is pasted or recreated instead of reused. They increase maintenance cost because every future bug fix must be found in multiple locations.
garak/analyze/get_tree.py:60 qualitylegacy
high Legacy quality quality conf 0.86 Duplicated implementation block across source files
Duplicated blocks are a common artifact when generated code is pasted or recreated instead of reused. They increase maintenance cost because every future bug fix must be found in multiple locations.
garak-report/src/types/ProbesChart.ts:32 qualitylegacy
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