CVE-2026-24770

Jan. 27, 2026, 10:15 p.m.

9.8
Critical

Description

RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine. In version 0.23.1 and possibly earlier versions, the MinerU parser contains a "Zip Slip" vulnerability, allowing an attacker to overwrite arbitrary files on the server (leading to Remote Code Execution) via a malicious ZIP archive. The MinerUParser class retrieves and extracts ZIP files from an external source (mineru_server_url). The extraction logic in `_extract_zip_no_root` fails to sanitize filenames within the ZIP archive. Commit 64c75d558e4a17a4a48953b4c201526431d8338f contains a patch for the issue.

Product(s) Impacted

Vendor Product Versions
Ragflow
  • Ragflow
  • <0.23.1, 0.23.1

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 ragflow ragflow <0.23.1 / / / / / / /
a ragflow ragflow 0.23.1 / / / / / / /

CVSS Score

9.8 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: Jan. 27, 2026, 10:15 p.m.
Last Modified: Jan. 27, 2026, 10:15 p.m.

Status : Received

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.