Raw vector
CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:HSummary
CVE-2025-68472 is a high-severity Path Traversal (CWE-22) vulnerability in Mindsdb Mindsdb. Its CVSS base score is 8.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 3% 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 LLM Application Platforms; in the Privacy and Disclosure risk domain.
The strongest mitigations our analysis identified map to AC-3 (Access Enforcement) and SI-10 (Information Input Validation) — 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.
CVE-2025-68472 is an unauthenticated path traversal vulnerability in MindsDB, a platform for building artificial intelligence from enterprise data, affecting versions prior to 25.11.1. The flaw exists in the file upload API's PUT handler in file.py, which directly joins user-controlled data into a filesystem path when the request body is JSON and source_type is not "url". Multipart uploads and URL-sourced uploads receive sanitization via clear_filename or equivalent checks, but JSON uploads lack these protections, enabling attackers to read arbitrary files from the server filesystem and move them into MindsDB’s storage.
The vulnerability can be exploited by unauthenticated attackers with adjacent network access (AV:A), requiring low attack complexity (AC:L), no privileges (PR:N), and no user interaction (UI:N). Successful exploitation allows reading arbitrary files and relocating them into MindsDB storage, exposing sensitive data. It carries a CVSS v3.1 base score of 8.1 (AV:A/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H) and is associated with CWEs 22, 23, and 36.
MindsDB addressed the issue in version 25.11.1. Security practitioners should upgrade to this version or later. Additional mitigation details are available in the GitHub security advisory at https://github.com/mindsdb/mindsdb/security/advisories/GHSA-qqhf-pm3j-96g7 and the BlueRock analysis at https://www.bluerock.io/post/cve-2025-68472-mindsdb-file-upload-path-traversal.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-1922
Vulnerability Data
MindsDB is a platform for building artificial intelligence from enterprise data. Prior to version 25.11.1, an unauthenticated path traversal in the file upload API lets any caller read arbitrary files from the server filesystem and move them into MindsDB’s storage,…
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exposing sensitive data. The PUT handler in file.py directly joins user-controlled data into a filesystem path when the request body is JSON and source_type is not "url". Only multipart uploads and URL-sourced uploads receive sanitization; JSON uploads lack any call to clear_filename or equivalent checks. This vulnerability is fixed in 25.11.1.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Privacy and Disclosure
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: artificial intelligence
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V5.3.2
Mitigating Controls (NIST 800-53 r5) AI
Enforces the intended directory access authorizations that path traversal would otherwise bypass.
Input validation directly neutralizes special path elements before pathname construction occurs.
Information-flow rules can be configured to reject traversals that would move data outside an approved directory boundary.
Least privilege reduces the impact of any unauthorized file access obtained via traversal.
Secure-engineering principles require safe pathname construction and input neutralization before any file operation.
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 prevent relative traversal.
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 in development catches path traversal via static/dynamic analysis.
Secure SDLC mandates input validation and path sanitization that directly prevent path traversal.
Application security requirements include rules for safe file handling and canonicalization.
Secure architecture principles require least-privilege file access and directory isolation.
Secure coding standards explicitly forbid unsafe path construction and mandate safe APIs.
Information access restriction limits which files an application may read or write.