CVE-2024-3099: A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploit
Summary
MLflow version 2.11.1 has a vulnerability where attackers can create multiple models with the same name by using URL encoding (a technique that converts special characters into a format safe for web addresses). This allows attackers to cause denial of service (making a service unavailable) or data poisoning (inserting corrupted or malicious data), where an authenticated user might accidentally use a fake model instead of the real one because the system treats URL-encoded and regular names as different.
Vulnerability Details
5.4(medium)
EPSS: 0.1%
Classification
Taxonomy References
Affected Vendors
Related Issues
CVE-2024-37052: Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling
CVE-2026-26190: Milvus is an open-source vector database built for generative AI applications. Prior to 2.5.27 and 2.6.10, Milvus expose
Original source: https://nvd.nist.gov/vuln/detail/CVE-2024-3099
First tracked: February 15, 2026 at 08:46 PM
Classified by LLM (prompt v3) · confidence: 92%