CVE-2025-58756 HIGH

CVE-2025-58756: MONAI's unsafe torch usage may lead to arbitrary code execution

Vendor Project-Monai
Product MONAI
Weakness CWE-502 · Unsafe deserialization
Published September 8, 2025
Last update September 9, 2025

CVSS base score

8.8/10
Attack vector Network
Attack complexity Low
Privileges required Low
User interaction None
Confidentiality High
Integrity High

CVSS vector

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

What the vulnerability does

01Description

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.

Key dates

02Disclosure timeline

September 8, 2025 CVE published
September 9, 2025 Record updated

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