Picklescan Arbitrary Code Execution via doctest.debug_script Bypass

Executive Summary

The vulnerability in picklescan versions before 0.0.30 is that it fails to detect the doctest.debug_script function when analyzing pickle files. This allows attackers to craft malicious pickle files that include calls to doctest.debug_script, which bypasses picklescan's detection mechanisms.

When such a malicious pickle file is loaded using pickle.load, it can execute arbitrary commands on the target system.

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Detection Guidance

This vulnerability involves malicious pickle files embedding the doctest.debug_script function, which picklescan versions before 0.0.30 fail to detect. Detection involves analyzing pickle files for the presence of doctest.debug_script calls that bypass picklescan's checks.

Since picklescan itself fails to detect this function, manual inspection or enhanced scanning tools are required.

Suggested commands to detect suspicious pickle files could include using Python scripts to safely inspect pickle files without loading them, for example:

• Use a Python script to parse pickle files and look for references to 'doctest.debug_script' in the pickle bytecode or reduce calls.
• Example command snippet: `python -c "import pickletools; pickletools.dis(open('file.pkl','rb').read())"` to disassemble the pickle file and manually check for suspicious function calls.
• Monitor network traffic for unexpected pickle file transfers or loads, especially from untrusted sources.

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Impact Analysis

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

Such code execution can lead to unauthorized actions, potentially compromising system integrity, confidentiality, and availability.

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Compliance Impact

The vulnerability allows remote attackers to execute arbitrary code by bypassing picklescan detection when loading malicious pickle files. This can lead to unauthorized access or manipulation of data.

Such unauthorized code execution and potential data compromise can 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 for security may unknowingly expose themselves to supply chain risks and breaches, which could result in violations of these regulations.

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Mitigation Strategies

Immediate mitigation steps include:

• Avoid loading pickle files from untrusted or unauthenticated sources, as malicious pickle files can execute arbitrary code.
• Upgrade picklescan to version 0.0.30 or later, where detection of doctest.debug_script is improved.
• Implement additional validation or sandboxing when handling pickle files to prevent execution of arbitrary code.
• Review and restrict the use of pickle.load in your applications, considering safer serialization formats if possible.

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