Vulnerability · Published Sep 8, 2025 · Assigned by GitHub_M
CVE-2025-58756MONAI's unsafe torch usage may lead to arbitrary code execution
High 8.8
In plain English
A high-severity unsafe deserialization in MONAI from Project-MONAI. There are no confirmed reports of exploitation so far. The chance it is exploited in the next 30 days is estimated at 0.8% (higher than 55% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.
Official 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.
Affected packages & fixed versions
| Ecosystem | Package | Fixed in | Advisory |
|---|---|---|---|
| PyPI | monai | 1.5.1 | GHSA-6vm5-6jv9-rjpj |
| PyPI | monai | 1.5.1rc1 | PYSEC-2025-141 |
Affected products (as reported)
| Vendor | Product | Versions |
|---|---|---|
| Project-MONAI | MONAI | <= 1.5.0 |
Weakness: CWE-502 · Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
References
- https://github.com/Project-MONAI/MONAI/security/advisories/GHSA-6vm5-6jv9-rjpj x_refsource_CONFIRM