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ParallaxFx343/pickle-scanner-bypass-marshal-poc
pickle-scanner-bypass-marshal-poc is a machine learning model from ParallaxFx343. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Security research PoC submitted to huntr.com by ParallaxFx343.
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Updated Jul 1, 2026
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From the Hugging Face model README
Security research PoC submitted to huntr.com by ParallaxFx343.
malicious_model.pkl is a proof-of-concept pickle file that achieves arbitrary
code execution while completely bypassing both major ML model security
scanners:
Infected files: 0, Dangerous globals: 0No issues found!The payload chains three Python standard library calls that are not in either scanner's blocklist:
marshal.loads(bytecode) -> code object (reconstructs types.CodeType
without referencing it directly)
builtins.globals() -> globals dict
types.FunctionType(code, g) -> callable function
function() -> arbitrary code execution
types.CodeType is blocked by picklescan, but marshal.loads,
types.FunctionType, and builtins.globals are not — despite marshal.loads
being functionally equivalent to constructing a CodeType object.
Any code path that calls pickle.loads() / pickle.load() on this file —
including torch.load(weights_only=False), joblib.load(), or direct
pickle usage — will execute the embedded command. No user interaction is
required beyond loading the file with a standard deserialization API.
The embedded command is a harmless marker write for demonstration:
echo huntr_PoC_by_ParallaxFx343_pickle_scanner_bypass_executed > /tmp/huntr_poc_marker
This is a non-destructive proof-of-concept. It does not exfiltrate data, modify the host beyond writing a marker file, or persist itself.
See the accompanying huntr.com report for the complete root cause analysis, 20+ additional unblocked gadgets discovered during this research, and remediation recommendations.
Do not deserialize untrusted pickle files. This repository exists solely to demonstrate the scanner bypass for responsible disclosure purposes.