CVE-2025-71368

picklescan before 0.0.30 fails to detect the doctest.debug_script function when analyzing pickle files, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files embedding doctest.debug_script calls that bypass picklescan detection and execute arbitrary commands upon pickle.load invocation.

picklescan before 0.0.30 fails to detect the doctest.debug_script function when analyzing pickle files, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files embedding doctest.debug_script calls that bypass picklescan detection and execute arbitrary commands upon pickle.load invocation.

picklescan before 0.0.30 fails to detect the doctest.debug_script function when analyzing pickle files, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files embedding doctest.debug_script calls that bypass picklescan detection and execute arbitrary commands upon pickle.load invocation.

Summary

Using doctest.debug_script 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 doctest.debug_script 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 doctest import debug_script

class EvilDoctestDebugScript:
    def __reduce__(self):
        # debug_script(src, pm=True) -> exec(src, ...)
        return debug_script, ("__import__('os').system('whoami')", True)

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

picklescan before 0.0.30 fails to detect the doctest.debug_script function when analyzing pickle files, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files embedding doctest.debug_script calls that bypass picklescan detection and execute arbitrary commands upon pickle.load invocation.

picklescan before 0.0.30 fails to detect the doctest.debug_script function when analyzing pickle files, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files embedding doctest.debug_script calls that bypass picklescan detection and execute arbitrary commands upon pickle.load invocation.

Summary

Using doctest.debug_script 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 doctest.debug_script 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 doctest import debug_script

class EvilDoctestDebugScript:
    def __reduce__(self):
        # debug_script(src, pm=True) -> exec(src, ...)
        return debug_script, ("__import__('os').system('whoami')", True)

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