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

High 8.8 Published Updated

Attackers can execute arbitrary code by tricking users into loading malicious checkpoints in the MONAI AI toolkit due to insecure deserialization practices.

Exploited in the wild
Not known
Login needed
Any signed-in user
Attackable
Over the internet
Victim action needed
Not needed
Fix
Available

What is CVE-2025-58756?

CVE-2025-58756 is a high-severity unsafe deserialization vulnerability in Project-MONAI MONAI, published on 8 Sep 2025. Any signed-in user can exploit it over the network, with no action from the victim.

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.

Weakness: CWE-502

Which versions are affected by CVE-2025-58756?

3 open source packages ship an affected version, including monai. It affects 1 product.

PackageAffectedFixed in
monai PyPIAll versions1.5.1
monai PyPIAll versions1.5.1
monai PyPIAll versions1.5.1rc1

Products include Monai Medical Open Network for Ai.

How do I fix CVE-2025-58756?

Upgrade monai to a fixed version for your release line: 1.5.1 or 1.5.1rc1.

Upgrade, and only deserialise data from trusted sources or with an allow-list of types. More about Unsafe deserialization.

Is CVE-2025-58756 being exploited?

There is no known exploitation of CVE-2025-58756 in the wild and no public exploit code.

Sources

Also known as GHSA-6vm5-6jv9-rjpj, PYSEC-2025-141.

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