picklescan Arbitrary Code Execution via trace.Trace.runctx

Executive Summary

This vulnerability exists in picklescan versions before 0.0.29. The tool fails to detect the built-in Python function trace.Trace.runctx when it is used within pickle file reduce methods. As a result, attackers can craft malicious pickle files containing trace.Trace.runctx payloads that bypass picklescan's detection mechanisms.

When such a malicious pickle file is loaded using pickle.load(), the embedded trace.Trace.runctx function executes arbitrary code on the target system.

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Detection Guidance

This vulnerability involves picklescan failing to detect malicious pickle files that use the Python built-in trace.Trace.runctx function in their reduce methods. Detection involves identifying pickle files that contain this specific payload.

Since picklescan versions before 0.0.29 do not detect this payload, one way to detect the vulnerability is to analyze pickle files for the presence of trace.Trace.runctx usage in their __reduce__ methods.

There are no specific commands provided in the available resources to detect this vulnerability on your network or system.

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Impact Analysis

This vulnerability allows remote attackers to execute arbitrary code on systems that load malicious pickle files using pickle.load().

Because the malicious payload bypasses picklescan detection, it increases the risk of unauthorized code execution, potentially leading to system compromise, data theft, or disruption of services.

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Compliance Impact

The vulnerability in picklescan allows remote code execution through malicious pickle files that bypass detection. This can lead to unauthorized execution of arbitrary code, potentially compromising the integrity and confidentiality of data processed or stored by affected systems.

Such unauthorized code execution risks violating compliance requirements under standards like GDPR and HIPAA, which mandate protection of personal and sensitive data against unauthorized access and processing.

Organizations relying on picklescan for sanitizing pickle files in machine learning models or Python objects may face increased risk of supply chain attacks, potentially leading to data breaches or unauthorized data manipulation, thereby impacting regulatory compliance.

Mitigation by updating to picklescan version 0.0.29 or later is advised to reduce these risks and help maintain compliance.

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Mitigation Strategies

The primary mitigation step is to update picklescan to version 0.0.29 or later, where this detection issue has been fixed.

Avoid loading pickle files from untrusted or unauthenticated sources, as malicious pickle files can execute arbitrary code upon loading.

Consider implementing additional validation or sandboxing mechanisms when handling pickle files to reduce the risk of remote code execution.

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