Medical Open Network For Ai
CVE-2025-58756
HIGH
Severity by source
AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Primary rating from GitHub Advisory · only source for this CVE.
CVSS VectorGitHub Advisory
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Lifecycle Timeline
4Blast Radius
ecosystem impact- 1 pypi packages depend on monai (1 direct, 0 indirect)
Ecosystem-wide dependent count for version 1.5.1.
DescriptionGitHub Advisory
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.
AnalysisAI
MONAI (Medical Open Network for AI) is an AI toolkit for health care imaging. Rated high severity (CVSS 8.8), this vulnerability is remotely exploitable, low attack complexity. Public exploit code available and no vendor patch available.
Technical ContextAI
This vulnerability is classified as Deserialization of Untrusted Data (CWE-502), which allows attackers to execute arbitrary code through malicious serialized objects. 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. Affected products include: Monai Medical Open Network For Ai.
RemediationAI
No vendor patch is available at time of analysis. Monitor vendor advisories for updates. Avoid deserializing untrusted data. Use safe serialization formats (JSON). Implement integrity checks and type allowlists.
Share
External POC / Exploit Code
Leaving vuln.today
GHSA-6vm5-6jv9-rjpj