CVE-2024-37061
Published: 04 June 2024
Summary
CVE-2024-37061 is a high-severity Code Injection (CWE-94) vulnerability in Lfprojects Mlflow. Its CVSS base score is 8.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Client Execution (T1203); ranked in the top 11.4% of CVEs by exploit likelihood; 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 Platforms; in the Supply Chain and Deployment risk domain; MITRE ATLAS techniques in scope: AI Supply Chain Compromise (AML.T0010).
Deeper analysis
CVE-2024-37061 is a remote code execution vulnerability affecting the MLflow platform in versions 1.11.0 and newer. It stems from improper control of code generation, tracked as CWE-94, and carries a CVSS 3.1 score of 8.8. The flaw allows a maliciously crafted MLproject file to trigger arbitrary code execution on an end user's system when the project is run.
An attacker can supply the crafted MLproject to a victim, who then executes it through MLflow; because the vector requires no privileges and only routine user interaction, the attacker achieves full code execution with impacts to confidentiality, integrity, and availability on the target system.
The EPSS score for this CVE rose from a low baseline to a peak of 0.0736 on 2025-12-11 before receding to the current value of 0.0395, indicating post-disclosure exploitation interest. Public advisories from HiddenLayer detail the issue and are available at the referenced URLs.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-2125
Vulnerability details
Remote Code Execution can occur in versions of the MLflow platform running version 1.11.0 or newer, enabling a maliciously crafted MLproject to execute arbitrary code on an end user’s system when run.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Other 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 logging, tracking, and loading. The vulnerability involves RCE via malicious MLproject files or deserialization in model loaders (e.g., sklearn, pyfunc, pmdarima, lightgbm integrations), confirming it affects an AI/ML platform.
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Deserialization vulnerabilities in MLflow (CVE-2024-37061 and related CVEs-2024-37052 through -37056) via unsafe pickle/cloudpickle handling in model loaders (sklearn, pyfunc, pmdarima, lightgbm) and MLproject YAML parsing enable arbitrary remote code execution on victim systems when loading malicious models or running crafted projects.
MITRE ATLAS TechniquesAI
MITRE ATLAS techniques
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Makes persistent code injection into loaded programs impossible when the executable image itself resides on hardware-protected read-only media.
Dynamically generated code can be produced and executed inside the isolated chamber, preventing host compromise from code-injection payloads.
Validates inputs used in dynamic code generation to block injected directives.
Directly prevents execution of attacker-supplied code written into data memory regions.