CVE-2023-6023
Path Traversal in Vertaai Modeldb
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:NSummary
CVE-2023-6023 is a high-severity Path Traversal: '\..\filename' (CWE-29) vulnerability in Vertaai Modeldb. 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 14% 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 Privacy and Disclosure 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-2023-6023 is a local file inclusion vulnerability present in the ModelDB server. It stems from improper handling of the artifact_path URL parameter, which permits an attacker to read arbitrary files from the underlying server filesystem. The flaw is tracked under CWE-22 and CWE-29 and carries a CVSS 3.1 score of 7.5.
Remote attackers require no authentication or user interaction to exploit the issue, enabling them to retrieve any readable file on the host and resulting in high confidentiality impact without affecting integrity or availability.
The vulnerability was reported via huntr.com bounties. Its EPSS score reached a peak of 0.5119 and currently stands at 0.4794.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-58283
Vulnerability Data
An attacker can read any file on the filesystem on the server hosting ModelDB through an LFI in the artifact_path URL parameter.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Other AI Platforms
- Risk Domain
- Privacy and Disclosure
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- ModelDB is an open-source ML model management and metadata store platform, fitting 'Other Platforms' as it handles ML experiments, models, and artifacts, and the vulnerability is reported on an AI/ML bug bounty platform (huntr).
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.