CVE-2025-71363

picklescan before 0.0.30 fails to detect cProfile.run function calls in pickle reduce methods, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files with cProfile.run payloads that bypass picklescan detection and achieve code execution upon deserialization.

picklescan before 0.0.30 fails to detect cProfile.run function calls in pickle reduce methods, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files with cProfile.run payloads that bypass picklescan detection and achieve code execution upon deserialization.

picklescan before 0.0.30 fails to detect cProfile.run function calls in pickle reduce methods, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files with cProfile.run payloads that bypass picklescan detection and achieve code execution upon deserialization.

Summary

Using cProfile.run 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.run 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 EvilCProfileRun:
    def __reduce__(self):
        # cProfile.run(statement) -> Profile().run(statement) -> exec(statement)
        return cProfile.run, ("__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 0.0.30 fails to detect cProfile.run function calls in pickle reduce methods, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files with cProfile.run payloads that bypass picklescan detection and achieve code execution upon deserialization.

picklescan before 0.0.30 fails to detect cProfile.run function calls in pickle reduce methods, allowing attackers to execute arbitrary code. Remote attackers can craft malicious pickle files with cProfile.run payloads that bypass picklescan detection and achieve code execution upon deserialization.

Summary

Using cProfile.run 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.run 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 EvilCProfileRun:
    def __reduce__(self):
        # cProfile.run(statement) -> Profile().run(statement) -> exec(statement)
        return cProfile.run, ("__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