Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2023-6831 is a high-severity Path Traversal: '\..\filename' (CWE-29) vulnerability in Lfprojects Mlflow. Its CVSS base score is 8.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Data Obfuscation (T1001); ranked in the top 12% 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 AI Platforms; in the Other ATLAS/OWASP Terms risk domain.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2023-6831 is a path traversal vulnerability, identified as CWE-29 and CWE-22, that affects the mlflow/mlflow GitHub repository in versions prior to 2.9.2. The flaw carries a CVSS 3.1 score of 8.1 and permits traversal sequences such as '\..\filename' that can be supplied over the network.
An authenticated attacker with low privileges can exploit the issue without user interaction to modify or delete files on the server, producing high integrity and availability impact while leaving confidentiality unaffected. The attack surface is network-reachable and requires only limited complexity to trigger.
References point to commits that resolve the traversal flaw and to the associated huntr.dev bounty report; these indicate that upgrading to MLflow 2.9.2 or later eliminates the exposure.
The EPSS score rose from lower values after disclosure to a peak of 0.8089 on 2025-12-11 before receding to the current 0.7398, demonstrating increased exploitation interest that warrants renewed attention for MLflow deployments.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-0154
Vulnerability Data
Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Other AI Platforms
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- MLflow is an open-source platform for managing the end-to-end machine learning lifecycle, including tracking experiments, packaging code, and deploying models, fitting under 'Other Platforms' as it is not a framework, library, or specialized AI tool.
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V5.3.2
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.
Validates pathnames and filenames to prevent traversal outside intended directories.
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.
Patching/maintenance can remediate known path-traversal flaws in deployed software (partial prevention of exploitability) but does nothing to stop the coding defect from being introduced in the first place.
Secure SDLC practices directly require input validation and path sanitization that block this traversal vector.
PR.AA-05 defines and reviews access policies but does not address code-level pathname neutralization, so neither direction prevents CWE-22.
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.