CVE-2026-27570

March 20, 2026, 1:39 p.m.

5.1
Medium

Description

Discourse is an open-source discussion platform. Prior to versions 2026.3.0-latest.1, 2026.2.1, and 2026.1.2, the onebox method in the SharedAiConversation model renders the conversation title directly into HTML without proper sanitization. Versions 2026.3.0-latest.1, 2026.2.1, and 2026.1.2 contain a patch. As a workaround, tighten access by changing the `ai_bot_public_sharing_allowed_groups` site setting.

Product(s) Impacted

Vendor Product Versions
Discourse
  • Discourse
  • <2026.3.0-latest.1, <2026.2.1, <2026.1.2

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 discourse discourse <2026.3.0-latest.1 / / / / / / /
a discourse discourse <2026.2.1 / / / / / / /
a discourse discourse <2026.1.2 / / / / / / /

CVSS Score

5.1 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: LOW
  • User Interaction: PASSIVE
  • Scope:
  • Confidentiality Impact: LOW
  • Integrity Impact: LOW
  • Availability Impact: NONE
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:P/VC:L/VI:L/VA:N/SC:N/SI:N/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: March 19, 2026, 9:17 p.m.
Last Modified: March 20, 2026, 1:39 p.m.

Status : Undergoing 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.