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PoC - modelaudit skops scanner evasion (ConstructorFromReduceNode untrusted-type gap)
Coordinated disclosure PoC for huntr (Protect AI MFV). Benign payload only.
- Scanner under test:
modelaudit==0.2.49(skops_scanner.py),skops==0.14.0, scikit-learn 1.9.0, Python 3.11.15. - Format:
.skops(zip-based; the sklearn / joblib-ecosystem secure-serialization format). - Two-sided behavior:
modelaudit scan evil.skops-> Clean / exit 0 (Scanner: skops, NO ISSUES FOUND), but loading via the documented skopstrusted=workflow executesposix.system(<benign marker>). skops itself is correct:skops.io.get_untrusted_types(file='evil.skops')returns['posix.system']and the default loader refuses it; modelaudit never enumerates that untrusted-type set. - Benign marker: the reduce node calls
posix.systemto touch a harmless sentinel file. No destructive action. - Root cause: modelaudit's skops scanner is a narrow 3-signature matcher (hardcodes CVE-2025-54412 / 54413 / 54886
plus a few joblib/pickle byte patterns) rather than a trust-boundary model. A generic
ConstructorFromReduceNodeforposix.systemmatches none of those signatures, so the file scans Clean.
Files: evil.skops (reduce node at document root), stealth.skops (same gadget grafted onto a real fitted
LogisticRegression that still predicts), build_evil_skops.py (builder). Full report + positive controls in the
huntr submission.
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