CVE-2025-58756
However, insecure loading methods still exist elsewhere in the project, such as when loading checkpoints.
Does this matter?
High impact if exploited, but EPSS currently rates exploitation as unlikely (0.74%). Schedule it in the normal patch cycle and watch for a rise in EPSS or a public exploit.
Description
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.
- CVSS 3.1
- 8.8 HIGHCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
- EPSS
- 0.74% probability · 53th percentile
- CISA KEV
- Not listed
- Weakness
- CWE-502
- Affected
- monai/medical open network for ai
- Source
- security-advisories@github.com
References
- https://github.com/Project-MONAI/MONAI/security/advisories/GHSA-6vm5-6jv9-rjpjExploit, Vendor Advisory
Source: NVD record, EPSS from FIRST.org, KEV from CISA. Refreshed daily.