CVE-2026-23630

Jan. 21, 2026, 11:15 p.m.

6.3
Medium

Description

Docmost is open-source collaborative wiki and documentation software. In versions 0.3.0 through 0.23.2, Mermaid code block rendering is vulnerable to stored Cross-Site Scripting (XSS). The frontend can render attacker-controlled Mermaid diagrams using mermaid.render(), then inject the returned SVG/HTML into the DOM via dangerouslySetInnerHTML without sanitization. Mermaid per-diagram %%{init}%% directives allow overriding securityLevel and enabling htmlLabels, permitting arbitrary HTML/JS execution for any viewer. This issue has been fixed in version 0.24.0.

Product(s) Impacted

Vendor Product Versions
Docmost
  • Docmost
  • <0.24.0

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-79
Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
The product does not neutralize or incorrectly neutralizes user-controllable input before it is placed in output that is used as a web page that is served to other users.

*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 docmost docmost <0.24.0 / / / / / /

CVSS Score

6.3 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: LOW
  • User Interaction: PASSIVE
  • Scope:
  • Confidentiality Impact: NONE
  • Integrity Impact: NONE
  • Availability Impact: NONE
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:P/VC:N/VI:N/VA:N/SC:H/SI:H/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

    View Vector String

Timeline

Published: Jan. 21, 2026, 11:15 p.m.
Last Modified: Jan. 21, 2026, 11:15 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.