Code Execution in Picklescan via Profile.run Bypass

Executive Summary

The vulnerability exists in picklescan versions before 0.0.29, where it fails to detect the built-in Python function profile.Profile.run when used in pickle reduce methods.

This failure allows attackers to craft malicious pickle files that bypass picklescan's detection mechanisms.

When these malicious pickle files are deserialized, they can execute arbitrary code on the target system.

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Detection Guidance

This vulnerability involves malicious pickle files crafted to bypass picklescan detection by using the built-in Python profile.Profile.run function in pickle reduce methods. Detection involves identifying such malicious pickle files or monitoring deserialization processes that use pickle.load().

A practical approach is to scan pickle files with an updated version of picklescan (version 0.0.29 or later), which includes the patch to detect this exploit.

For command-line detection, use the following command to scan pickle files:

• picklescan scan <pickle_file>

Additionally, monitor your system for unexpected execution of Python processes or suspicious deserialization activities, especially those invoking profile.Profile.run.

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Impact Analysis

This vulnerability can allow remote attackers to execute arbitrary code on your system by tricking it into deserializing malicious pickle files.

Because the vulnerability has a high impact on confidentiality and integrity (as indicated by the CVSS scores), it can lead to unauthorized access to sensitive data and manipulation of system behavior.

The attack requires no privileges and can be performed remotely, making it a significant security risk.

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Compliance Impact

CVE-2025-71374 allows remote attackers to execute arbitrary code by bypassing picklescan's detection mechanisms. This can lead to unauthorized access or manipulation of sensitive data during deserialization processes.

Such unauthorized code execution and potential data breaches can negatively impact compliance with data protection regulations like GDPR and HIPAA, which require strict controls over data confidentiality and integrity.

Organizations using vulnerable versions of picklescan may face increased risk of supply chain attacks and data compromise, thereby potentially violating regulatory requirements for safeguarding personal and sensitive information.

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Mitigation Strategies

The primary mitigation step is to update picklescan to version 0.0.29 or later, where the vulnerability has been patched.

Avoid deserializing pickle files from untrusted or unauthenticated sources to reduce the risk of arbitrary code execution.

Implement monitoring and alerting for suspicious deserialization activities and consider restricting or sandboxing environments where pickle files are loaded.

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