Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:L/A:NSummary
CVE-2023-1177 is a critical-severity Path Traversal: '\..\filename' (CWE-29) vulnerability in Lfprojects Mlflow. Its CVSS base score is 9.3 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 0.7% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
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-2023-1177 is a path traversal vulnerability, identified as CWE-22 and CWE-29, that affects the MLflow machine learning platform in the GitHub repository mlflow/mlflow prior to version 2.2.1. The flaw permits directory traversal sequences such as '\..\filename' and carries a CVSS 3.1 score of 9.3 reflecting network attack vector, low complexity, and no required privileges or user interaction.
An unauthenticated remote attacker can exploit the issue to read arbitrary files on the server, resulting in high confidentiality impact and limited integrity impact within the affected MLflow deployment. The vulnerability is exposed through the application's handling of file paths, enabling direct access to sensitive data outside intended directories.
References to the fixing commit 7162a50c654792c21f3e4a160eb1a0e6a34f6e6e and the associated huntr.dev report confirm that the issue was resolved by the MLflow 2.2.1 release; practitioners should upgrade immediately and validate that path-handling logic no longer accepts traversal sequences.
The EPSS score remains elevated at a current value of 0.9331 with a peak of 0.9333, indicating sustained exploitation interest after disclosure for this MLflow component.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-0157
Vulnerability Data
Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.2.1.
- CWE(s)
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.
Secure SDLC practices directly require input validation and path sanitization that block this traversal vector.
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.
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.
Security testing can discover path-traversal flaws but does not itself prevent them in production code.
Secure SDLC mandates input validation and path sanitization that directly prevent path traversal.
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'.
Information access restriction limits which files an application may read or write.