MONAI's unsafe torch usage may lead to arbitrary code execution
Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).
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| Project-MONAI | MONAI | affected |
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No data.
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| Monai | Monai | — |
| Source | ID | Title |
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EUVD |
EUVD-2025-27190 | MONAI: Unsafe torch usage may lead to arbitrary code execution |
Github GHSA |
GHSA-6vm5-6jv9-rjpj | MONAI: Unsafe torch usage may lead to arbitrary code execution |
No CVSS v4.0
No CVSS v3.0
No CVSS v2
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.750% probability within 30 days)
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| First Time appeared |
Monai medical Open Network For Ai
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| CPEs | cpe:2.3:a:monai:medical_open_network_for_ai:*:*:*:*:*:*:*:* | |
| Vendors & Products |
Monai medical Open Network For Ai
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| First Time appeared |
Monai
Monai monai |
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| Vendors & Products |
Monai
Monai monai |
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| Metrics |
ssvc
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| 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. | |
| Title | MONAI's unsafe torch usage may lead to arbitrary code execution | |
| Weaknesses | CWE-502 | |
| References |
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| Metrics |
cvssV3_1
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