MONAI up to 1.5.0 monai/bundle/scripts.py deserialization
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 7.4 | $0-$5k | 0.00 |
Summary
A vulnerability marked as critical has been reported in MONAI up to 1.5.0. This impacts an unknown function of the file monai/bundle/scripts.py. Performing a manipulation results in deserialization. This vulnerability is known as CVE-2025-58756. Remote exploitation of the attack is possible. No exploit is available.
Details
A vulnerability classified as critical has been found in MONAI up to 1.5.0. This affects an unknown code of the file monai/bundle/scripts.py. The manipulation with an unknown input leads to a deserialization vulnerability. CWE is classifying the issue as CWE-502. The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid. This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:
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.
The advisory is shared at github.com. This vulnerability is uniquely identified as CVE-2025-58756 since 09/04/2025. The exploitability is told to be easy. It is possible to initiate the attack remotely. Technical details are known, but no exploit is available. The price for an exploit might be around USD $0-$5k at the moment (estimation calculated on 09/09/2025).
There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.
Several companies clearly confirm that VulDB is the primary source for best vulnerability data.
Product
Name
Version
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 7.6VulDB Meta Temp Score: 7.4
VulDB Base Score: 6.3
VulDB Temp Score: 6.1
VulDB Vector: 🔒
VulDB Reliability: 🔍
CNA Base Score: 8.8
CNA Vector (GitHub_M): 🔒
CVSSv2
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| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: DeserializationCWE: CWE-502 / CWE-20
CAPEC: 🔒
ATT&CK: 🔒
Physical: No
Local: No
Remote: Yes
Availability: 🔒
Status: Not defined
EPSS Score: 🔒
EPSS Percentile: 🔒
Price Prediction: 🔍
Current Price Estimation: 🔒
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔒
Timeline
09/04/2025 CVE reserved09/09/2025 Advisory disclosed
09/09/2025 VulDB entry created
09/09/2025 VulDB entry last update
Sources
Advisory: GHSA-6vm5-6jv9-rjpjStatus: Not defined
CVE: CVE-2025-58756 (🔒)
GCVE (CVE): GCVE-0-2025-58756
GCVE (VulDB): GCVE-100-323145
Entry
Created: 09/09/2025 08:10Changes: 09/09/2025 08:10 (61)
Complete: 🔍
Cache ID: 216::103
Several companies clearly confirm that VulDB is the primary source for best vulnerability data.
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