CVE-2025-68472

Jan. 13, 2026, 2:03 p.m.

8.1
High

Description

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, 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.

Product(s) Impacted

Vendor Product Versions
Mindsdb
  • Mindsdb
  • <25.11.1

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-22
Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
The product uses external input to construct a pathname that is intended to identify a file or directory that is located underneath a restricted parent directory, but the product does not properly neutralize special elements within the pathname that can cause the pathname to resolve to a location that is outside of the restricted directory.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a mindsdb mindsdb <25.11.1 / / / / / / /

CVSS Score

8.1 / 10

CVSS Data - 3.1

  • Attack Vector: ADJACENT_NETWORK
  • Attack Complexity: LOW
  • Privileges Required: NONE
  • Scope: UNCHANGED
  • Confidentiality Impact: NONE
  • Integrity Impact: HIGH
  • Availability Impact: HIGH
  • CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H

    View Vector String

Timeline

Published: Jan. 12, 2026, 5:15 p.m.
Last Modified: Jan. 13, 2026, 2:03 p.m.

Status : Awaiting Analysis

CVE has been recently published to the CVE List and has been received by the NVD.

More info

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.