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willardj/
modelscan-pytorch-blocklist-bypass-poc

Name: modelscan-pytorch-blocklist-bypass-poc
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ModelScan Blocklist Bypass — PyTorch .pt Models (4 Independent Chains)

Summary

ModelScan's unsafe_globals blocklist has systemic gaps allowing arbitrary code execution via crafted PyTorch .pt model files that scan clean. Four independent bypass chains are demonstrated, each requiring a different blocklist addition to fix.

Affected Version

ModelScan <= 0.8.8 (latest as of 2026-03-09)

Vulnerability Details

ModelScan's pickle scanner (modelscan/tools/picklescanner.py) extracts GLOBAL/INST/STACK_GLOBAL opcodes and checks them against unsafe_globals in settings.py. The blocklist covers os, subprocess, builtins.eval, builtins.exec, operator.attrgetter, etc. — but misses 5 critical modules/functions that chain to full RCE:

Missing Entry	Why It's Dangerous
`importlib.import_module`	Imports ANY blocked module (`os`, `subprocess`, etc.) at runtime
`operator.methodcaller`	Calls any method on any object — chains with imported modules
`code.InteractiveConsole`	Executes arbitrary Python source code
`io.open`	Arbitrary file creation/overwrite
`codecs.open`	Arbitrary file creation/overwrite

Exploit Chains

Chain 1: importlib + methodcaller (Full RCE, 132 bytes)

operator.methodcaller('system', cmd)(importlib.import_module('os'))

Chain 2: code.InteractiveConsole + methodcaller (Full RCE, 150 bytes)

operator.methodcaller('push', 'import os; os.system(cmd)')(code.InteractiveConsole())

Chain 3: io.open (Arbitrary file write, 60 bytes)

io.open('/path/to/file', 'w')

Chain 4: codecs.open (Arbitrary file write, 64 bytes)

codecs.open('/path/to/file', 'w')

Reproduction

bash

pip install torch modelscan
python poc.py

Expected output:

ModelScan reports "No issues found" for all 4 malicious .pt files
All 4 chains achieve code execution when loaded via torch.load(file, weights_only=False)

Impact

An attacker publishes a malicious PyTorch model on HuggingFace or any model registry. ModelScan (the safety scanner recommended by Protect AI / Palo Alto Networks) scans the file and reports it as safe. When a victim loads the model, arbitrary code executes on their machine.

This bypasses the primary defense that ML engineers rely on to validate model file safety before loading untrusted models.

willardj/modelscan-pytorch-blocklist-bypass-poc