CWE
475
Advisory Published
Advisory Published
Updated

CVE-2024-3099: Denial of Service and Data Model Poisoning via URL Encoding in mlflow/mlflow

First published: Thu Jun 06 2024(Updated: )

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.

Credit: security@huntr.dev security@huntr.dev

Affected SoftwareAffected VersionHow to fix
pip/mlflow<2.11.3
2.11.3
MLflow

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Frequently Asked Questions

  • What is the severity of CVE-2024-3099?

    CVE-2024-3099 has a moderate severity level as it can lead to Denial of Service for authenticated users.

  • How do I fix CVE-2024-3099?

    To fix CVE-2024-3099, upgrade to mlflow version 2.11.3 or higher.

  • What does CVE-2024-3099 exploit?

    CVE-2024-3099 exploits URL encoding to allow creation of multiple models with the same name.

  • Who is affected by CVE-2024-3099?

    Authenticated users of mlflow/mlflow version 2.11.1 are affected by CVE-2024-3099.

  • What is the impact of CVE-2024-3099?

    The impact of CVE-2024-3099 is that it can disrupt user access to intended models, leading to operational issues.

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