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  <updated>2026-10-03T03:27:26.112214+00:00</updated>
  <author>
    <name>Vulnerability-Lookup</name>
    <email>csirt@opendfir.org</email>
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  <entry>
    <id>https://cve.radiocsirt.org/vuln/cve-2025-58756</id>
    <title>CVE-2025-58756 — MONAI's unsafe torch usage may lead to arbitrary code execution</title>
    <updated>2026-10-03T03:27:26.113355+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> Project-MONAI MONAI</p>
<p>MONAI (Medical Open Network for AI) is an AI toolkit for health care imaging. In versions up to and including 1.5.0, in `model_dict = torch.load(full_path, map_location=torch.device(device), weights_only=True)` in monai/bundle/scripts.py , `weights_only=True` is loaded securely. However, insecure loading methods still exist elsewhere in the project, such as when loading checkpoints. This is a common practice when users want to reduce training time and costs by loading pre-trained models downloaded from other platforms. Loading a checkpoint containing malicious content can trigger a deserialization vulnerability, leading to code execution. As of time of publication, no known fixed versions are available.</p></div>
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    <link href="https://cve.radiocsirt.org/vuln/cve-2025-58756"/>
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