Remote Code Execution in Picklescan via Malicious Pickle Files

Executive Summary

CVE-2025-71343 is a vulnerability in the picklescan library versions 0.0.26 and earlier where the tool fails to detect malicious pickle files that exploit the Python function lib2to3.pgen2.pgen.ParserGenerator.make_label in the reduce method.

Attackers can craft specially designed pickle files that embed malicious code which evades detection by picklescan but executes arbitrary commands when the pickle file is loaded using pickle.load().

This leads to a risk of remote code execution through deserialization of untrusted data.

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Impact Analysis

This vulnerability can allow attackers to execute arbitrary code remotely by tricking the system into loading malicious pickle files that bypass detection.

It poses a supply chain risk because infected pickle files could be distributed through machine learning models, APIs, or saved Python objects.

Any organization or individual relying on picklescan for security could be impacted, potentially leading to unauthorized command execution and compromise of systems.

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Detection Guidance

This vulnerability involves malicious pickle files that exploit the lib2to3.pgen2.pgen.ParserGenerator.make_label function, which picklescan versions before 0.0.30 fail to detect. Detection requires analyzing pickle files for suspicious use of this function during deserialization.

Since the vulnerability is related to the failure of picklescan to detect malicious pickle files, one way to detect it is to run picklescan on pickle files and observe if any malicious code is flagged. However, versions before 0.0.30 will not detect this specific exploit.

Suggested commands include running picklescan on pickle files to check for malicious content, for example:

• picklescan path/to/file.pkl
• python -c "import pickle; pickle.load(open('path/to/file.pkl', 'rb'))" # Use with caution in a safe environment to observe behavior

Note that because the vulnerability allows code execution during pickle.load(), running pickle.load() on untrusted files can be dangerous and should only be done in isolated environments.

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Mitigation Strategies

The primary mitigation step is to upgrade picklescan to version 0.0.30 or later, where the detection bypass has been fixed.

Avoid loading pickle files from untrusted sources using pickle.load() as this can lead to arbitrary code execution.

Implement strict validation and sandboxing when handling pickle files to reduce the risk of executing malicious code.

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Compliance Impact

The vulnerability allows attackers to execute arbitrary code by bypassing detection in the picklescan library, which can lead to unauthorized access or manipulation of data.

Such unauthorized code execution and potential data compromise can impact compliance with standards like GDPR and HIPAA, which require protection of sensitive data and prevention of unauthorized access.

Organizations relying on picklescan for security may face increased risk of data breaches or supply chain attacks, potentially violating regulatory requirements for data integrity and confidentiality.

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