Compliance Impact

The vulnerability allows attackers to execute arbitrary code remotely by bypassing picklescan's detection of malicious pickle files. This can lead to unauthorized access or manipulation of sensitive data processed or stored by affected systems.

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 relying on picklescan to validate PyTorch pickle files may face increased risk of supply chain attacks, potentially exposing personal or protected health information, thereby risking non-compliance with these standards.

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Executive Summary

CVE-2025-71370 is a vulnerability in picklescan versions before 0.0.28 where the tool fails to detect malicious calls to the PyTorch function torch.jit.unsupported_tensor_ops.execWrapper embedded in pickle files.

Attackers can craft malicious pickle files that bypass picklescan's detection mechanisms, allowing arbitrary code execution when these files are loaded using pickle.load().

This vulnerability is classified under CWE-502 (Deserialization of Untrusted Data) and poses a significant threat due to its potential for remote code execution.

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Impact Analysis

This vulnerability can lead to remote code execution on systems that use picklescan to verify the safety of pickle files before loading them.

Attackers can exploit this by distributing malicious pickle files that appear safe to picklescan but execute arbitrary code when loaded, potentially compromising the victim's system.

The impact includes risks such as supply chain attacks where infected pickle files are distributed through machine learning models, APIs, or saved Python objects.

Organizations or individuals relying on picklescan for security in PyTorch model workflows are particularly affected.

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Detection Guidance

This vulnerability involves picklescan failing to detect malicious torch.jit.unsupported_tensor_ops.execWrapper function calls embedded in pickle files. Detection requires analyzing pickle files for the presence of this specific function call.

Since picklescan versions before 0.0.28 do not detect this malicious function call, one approach is to update picklescan to a version that includes the fix or to manually inspect pickle files for suspicious reduce method calls invoking torch.jit.unsupported_tensor_ops.execWrapper.

Commands to detect this vulnerability could include:

• Use an updated picklescan tool to scan pickle files: `picklescan <pickle_file>`
• Manually inspect pickle files for suspicious reduce calls using Python scripts that parse pickle contents and look for `torch.jit.unsupported_tensor_ops.execWrapper`.
• Monitor network traffic for suspicious pickle file transfers, especially those containing PyTorch models or serialized objects.

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Mitigation Strategies

Immediate mitigation steps include:

• Upgrade picklescan to version 0.0.28 or later where the detection of malicious torch.jit.unsupported_tensor_ops.execWrapper calls is fixed.
• Avoid loading pickle files from untrusted or unauthenticated sources using `pickle.load()`.
• Implement additional validation or sandboxing when handling pickle files, especially those related to PyTorch models.
• Monitor and audit the use of pickle files in your environment to detect any suspicious activity or unexpected deserialization.

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