CVE-2025-71371

picklescan before 0.0.29 fails to detect malicious pickle files using code.InteractiveInterpreter.runcode in reduce methods. Attackers can craft pickle payloads that bypass picklescan detection and execute arbitrary code when loaded via pickle.load().

picklescan before 0.0.29 fails to detect malicious pickle files using code.InteractiveInterpreter.runcode in reduce methods. Attackers can craft pickle payloads that bypass picklescan detection and execute arbitrary code when loaded via pickle.load().

picklescan before 0.0.29 fails to detect malicious pickle files using code.InteractiveInterpreter.runcode in reduce methods. Attackers can craft pickle payloads that bypass picklescan detection and execute arbitrary code when loaded via pickle.load().

Summary

Using code.InteractiveInterpreter.runcode, 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 code.InteractiveInterpreter.runcode 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

class EvilCodeRuncode:
    def __reduce__(self):
        from code import InteractiveInterpreter
        # InteractiveInterpreter().runcode(cmd) -> exec(cmd)
        return InteractiveInterpreter().runcode, ("__import__('os').system('whoami')",)

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 0.0.29 fails to detect malicious pickle files using code.InteractiveInterpreter.runcode in reduce methods. Attackers can craft pickle payloads that bypass picklescan detection and execute arbitrary code when loaded via pickle.load().

picklescan before 0.0.29 fails to detect malicious pickle files using code.InteractiveInterpreter.runcode in reduce methods. Attackers can craft pickle payloads that bypass picklescan detection and execute arbitrary code when loaded via pickle.load().

Summary

Using code.InteractiveInterpreter.runcode, 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 code.InteractiveInterpreter.runcode 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

class EvilCodeRuncode:
    def __reduce__(self):
        from code import InteractiveInterpreter
        # InteractiveInterpreter().runcode(cmd) -> exec(cmd)
        return InteractiveInterpreter().runcode, ("__import__('os').system('whoami')",)

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