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GHSA-cffc-mxrf-mhh4

Published Dec 29, 2025·Last modified Dec 29, 2025
Affected Components(0)

No affected components available

Description

Summary

Picklescan uses numpy.f2py.crackfortran.param_eval, which is a function in numpy to execute remote pickle files.

Details

The attack payload executes in the following steps:

  • First, the attacker crafts the payload by calling the numpy.f2py.crackfortran.param_eval function via reduce method.
  • Then, when the victim checks whether the pickle file is safe by using the Picklescan library and this library doesn't detect any dangerous functions, they decide to use pickle.load() on this malicious pickle file, thus leading to remote code execution.

PoC

class RCE:
    def __reduce__(self):
        from numpy.f2py.crackfortran import param_eval
        return (param_eval,("os.system('ls')",None,None,None))

Impact

Any organization or individual relying on picklescan to detect malicious pickle files inside PyTorch models. Attackers can embed malicious code in pickle file that remains undetected but executes when the pickle file is loaded. Attackers can distribute infected pickle files across ML models, APIs, or saved Python objects.

Report by

Pinji Chen (cpj24@mails.tsinghua.edu.cn) from the NISL lab (https://netsec.ccert.edu.cn/about) at Tsinghua University, Guanheng Liu (coolwind326@gmail.com).

Risk Scores
Base Score
0.0

Measures severity based on intrinsic characteristics of the vulnerability, independent of environment.

Threat Intelligence
0.0

No exploitation activity has been observed at this time. Continue routine monitoring.

EPSS
0.45%

The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.

Exploit
Not available

We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.

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