CVE-2024-3099
Lfprojects Mlflow
Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:LSummary
CVE-2024-3099 is a medium-severity Undefined Behavior for Input to API (CWE-475) vulnerability in Lfprojects Mlflow. Its CVSS base score is 5.4 (Medium).
Operationally, ranked at the 36th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as Other AI Platforms; in the Supply Chain and Deployment risk domain.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-1979
Vulnerability Data
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…
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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.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Other AI Platforms
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- MLflow is an open-source platform for managing the ML lifecycle, including model registry and deployment, fitting 'Other Platforms' as it is not a framework, library, or specific AI subdomain tool.
Related Threats
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover calls that supply invalid control-parameter values before deployment.
Validating inputs to API control parameters ensures only permitted values are supplied, structurally eliminating the source of undefined behavior.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing can detect undefined behavior from invalid API inputs before deployment.
Secure development lifecycle includes API specification and validation that can prevent undefined behavior from invalid inputs.
Application security requirements can mandate explicit input validation and defined behavior for API parameters.
Secure system architecture principles can require defensive coding that eliminates undefined behavior in APIs.
Secure coding directly addresses avoiding undefined behavior by enforcing defined inputs and error handling in APIs.