First published: Tue Jun 04 2024(Updated: )
Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.
Credit: 6f8de1f0-f67e-45a6-b68f-98777fdb759c 6f8de1f0-f67e-45a6-b68f-98777fdb759c
Affected Software | Affected Version | How to fix |
---|---|---|
pip/mlflow | >=1.1.0<=2.13.1 | |
pip/mlflow | >=1.1.0<=2.14.1 | |
MLflow | >=1.1.0 |
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CVE-2024-37052 is considered a high severity vulnerability due to its potential for executing arbitrary code.
To mitigate CVE-2024-37052, upgrade MLflow to version 2.14.0 or above to prevent deserialization of untrusted data.
CVE-2024-37052 affects MLflow versions from 1.1.0 to 2.13.1, including all versions in this range.
CVE-2024-37052 is caused by the deserialization of untrusted data from a maliciously uploaded scikit-learn model.
The impact of CVE-2024-37052 allows attackers to run arbitrary code on an end user's system.