CVE-2024-8859
Lfprojects Mlflow 2.15.1
Raw vector
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:NSummary
CVE-2024-8859 is a high-severity Path Traversal: '\..\filename' (CWE-29) vulnerability in Lfprojects Mlflow. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 16% 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 Machine Learning Libraries; in the Supply Chain and Deployment risk domain.
The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) and AC-3 (Access Enforcement) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
MLflow version 2.15.1 is affected by a path traversal vulnerability in its dbfs service. When a URL is concatenated directly into file protocol handling, only the path portion is validated while query strings and other parameters are ignored, allowing an arbitrary file read when the service is configured and mounted to a local directory.
An unauthenticated remote attacker can supply a crafted URL to the mounted dbfs endpoint and retrieve arbitrary files from the underlying filesystem without requiring user interaction or credentials.
The referenced commit 7791b8cdd595f21b5f179c7b17e4b5eb5cbbe654 addresses the flaw, and the issue was disclosed via the Huntr platform.
MLflow’s role in machine-learning pipelines makes the dbfs configuration relevant to AI/ML deployments; the EPSS score reached a peak of 0.2692.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-6887
Vulnerability Data
A path traversal vulnerability exists in mlflow/mlflow version 2.15.1. When users configure and use the dbfs service, concatenating the URL directly into the file protocol results in an arbitrary file read vulnerability. This issue occurs because only the path part…
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of the URL is checked, while parts such as query and parameters are not handled. The vulnerability is triggered if the user has configured the dbfs service, and during usage, the service is mounted to a local directory.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Machine Learning Libraries
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: mlflow
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Input validation directly neutralizes the '\..\filename' sequence before pathname resolution occurs.
Access enforcement denies requests that resolve outside the intended directory even when the traversal sequence is present.
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.
Secure SDLC practices directly require input validation and path sanitization that block this traversal vector.
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 discover path-traversal flaws but does not itself prevent them in production code.
Application security requirements can mandate input validation and path canonicalization to block traversal sequences.
Secure architecture principles include directory sandboxing and safe file-access design that mitigate path traversal.
Secure coding standards directly require neutralizing path traversal sequences such as '\..\filename'.