picklescan Arbitrary Code Execution via Unchecked trace.Trace.run

Executive Summary

The vulnerability exists in picklescan versions before 0.0.29, where the tool fails to detect the built-in trace.Trace.run function when analyzing pickle files.

This failure allows attackers to embed malicious code that goes undetected by picklescan.

Specifically, remote attackers can craft malicious pickle files that use trace.Trace.run in the reduce method, which leads to arbitrary code execution when the pickle.load function processes these files.

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Detection Guidance

This vulnerability involves picklescan failing to detect malicious pickle files that use the built-in Python trace.Trace.run function in the reduce method. Detection involves analyzing pickle files for the presence of trace.Trace.run calls embedded in the reduce method.

Since picklescan versions before 0.0.29 do not detect this, upgrading picklescan to version 0.0.29 or later is necessary to properly scan and detect such malicious pickle files.

To detect potentially malicious pickle files on your system, you can run picklescan (version 0.0.29 or later) against pickle files to identify unsafe usage of trace.Trace.run.

Example command to scan a pickle file (assuming picklescan is installed and updated):

• picklescan path/to/file.pkl

Additionally, you can search for pickle files on your system and inspect them manually or with scripts to detect usage of trace.Trace.run in the reduce method, but no specific commands for this are provided in the resources.

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Impact Analysis

This vulnerability can lead to arbitrary code execution on systems that use vulnerable versions of picklescan to analyze pickle files.

An attacker can remotely craft malicious pickle files that, when loaded, execute unauthorized code, potentially compromising the affected system.

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Compliance Impact

The vulnerability CVE-2025-71349 allows attackers to execute arbitrary code by bypassing picklescan's detection mechanisms. This can lead to unauthorized access or manipulation of data when malicious pickle files are loaded.

Such unauthorized code execution and potential data compromise could negatively impact compliance with data protection standards and regulations like GDPR and HIPAA, which require safeguarding sensitive data and ensuring system integrity.

Organizations relying on picklescan to secure pickle files may face increased risk of supply chain attacks, potentially leading to breaches of confidentiality and integrity obligations under these regulations.

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Mitigation Strategies

The primary mitigation step is to upgrade the picklescan library to version 0.0.29 or later, where this vulnerability has been fixed.

Avoid loading pickle files from untrusted or unauthenticated sources, especially those that may contain malicious code embedded via trace.Trace.run in the reduce method.

Use picklescan version 0.0.29 or later to scan pickle files before loading them with pickle.load to detect and block malicious payloads.

Consider implementing additional security controls around deserialization processes, such as restricting pickle file sources and monitoring for suspicious activity.

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