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AI agent vulnerability · MLflow

CVE-2024-3099: Undefined Behavior in mlflow

mediumCVSS 3.1 5.4GHSA-8f8q-q2j7-7j2m

A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service (DoS) as an authenticated user might not be able to use the intended model, as it will open a different model each time.

Published Jun 6, 2024 · Updated Oct 11, 2024

Affected packages

mlflow

Ecosystem
PyPI
Affected
< 2.11.3
Fixed in
2.11.3
Check
pip show mlflow

Advisory details

From the GitHub Advisory Database (CC BY 4.0).

A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service (DoS) as an authenticated user might not be able to use the intended model, as it will open a different model each time. Additionally, an attacker can exploit this vulnerability to perform data model poisoning by creating a model with the same name, potentially causing an authenticated user to become a victim by using the poisoned model. The issue stems from inadequate validation of model names, allowing for the creation of models with URL-encoded names that are treated as distinct from their URL-decoded counterparts.

References

How this page is made: the data panel comes from the GitHub Advisory Database, CISA’s KEV catalog, the NVD and FIRST EPSS, and updates twice a day. No analysis has been written for this entry yet. Methodology

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