Authentication Bypass Vulnerability in MLflow by Databricks

CVE-2025-11200

What is CVE-2025-11200?

CVE-2025-11200 is a security vulnerability found in the MLflow platform, an open-source tool developed by Databricks for managing the machine learning lifecycle, including experimentation, reproducibility, and deployment. This vulnerability arises from weak password requirements that allow remote attackers to bypass authentication mechanisms in affected MLflow installations without needing to provide valid credentials. Such a flaw can critically undermine the security of MLflow-based systems, as unauthorized individuals can gain access to the application's functionalities, possibly leading to data exposure or manipulation. Organizations could face significant risks if sensitive machine learning models or datasets are handled in an insecure manner.

Potential Impact of CVE-2025-11200

1. Unauthorized Access to Sensitive Data: Attackers who exploit this vulnerability can gain unrestricted access to confidential data stored within the MLflow environment, which may include proprietary machine learning models and sensitive user information.

2. Manipulation of Machine Learning Workflows: The ability to bypass authentication allows attackers to alter or disrupt machine learning workflows, which can lead to incorrect model training processes, potentially degrading the quality of outputs or introducing harmful changes.

3. Compliance and Regulatory Risks: Organizations relying on MLflow may face compliance issues if sensitive data is exposed due to this vulnerability. This can carry serious implications, especially for industries governed by stringent data protection regulations, potentially resulting in financial penalties and reputational damage.

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