Arbitrary Code Execution in ESPnet via Malicious Model Checkpoints

Executive Summary

This vulnerability allows remote code execution in ESPnet before version 202609 due to unsafe deserialization. The load_pretrained_model function uses torch.load with weights_only=False, enabling arbitrary code execution when loading malicious pretrained model files. Attackers can craft files that execute code during deserialization without authentication.

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Detection Guidance

To detect this vulnerability, check if your ESPnet version is before 202609 by running: pip show espnet or checking the version in your environment. Inspect the load_pretrained_model.py file for torch.load calls with weights_only=False. Use grep -r "torch.load.*weights_only=False" /path/to/espnet to find vulnerable code paths.

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Impact Analysis

If you load untrusted model checkpoints in ESPnet before 202609, an attacker could execute arbitrary code on your system. This could lead to data theft, system compromise, or further network infiltration. The impact depends on the privileges of the user running ESPnet.

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Compliance Impact

This vulnerability could lead to unauthorized data access or modification, violating GDPR's integrity and confidentiality principles or HIPAA's security requirements. Organizations using affected ESPnet versions may face compliance violations if exploited.

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Mitigation Strategies

Upgrade ESPnet to version 202609 or later using pip install --upgrade espnet. If upgrading is not possible, modify the load_pretrained_model function to use safe_torch_load with weights_only=True. Avoid loading models from untrusted sources and validate all model checkpoints before use.

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