CVE-2025-24808

March 27, 2025, 4:45 p.m.

4.3
Medium

Description

Discourse is an open-source discussion platform. Prior to versions `3.3.4` on the `stable` branch and `3.4.0.beta5` on the `beta` branch, someone who is about to reach the limit of users in a group DM may send requests to add new users in parallel. The requests might all go through ignoring the limit due to a race condition. The patch in versions `3.3.4` and `3.4.0.beta5` uses the `lock` step in service to wrap part of the `add_users_to_channel` service inside a distributed lock/mutex in order to avoid the race condition.

Product(s) Impacted

Vendor Product Versions
Discourse
  • Discourse
  • <3.3.4, <3.4.0.beta5

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-362
Concurrent Execution using Shared Resource with Improper Synchronization ('Race Condition')
The product contains a code sequence that can run concurrently with other code, and the code sequence requires temporary, exclusive access to a shared resource, but a timing window exists in which the shared resource can be modified by another code sequence that is operating concurrently.

*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 <3.3.4 / / / / / / /
a discourse discourse <3.4.0.beta5 / / / / / / /

CVSS Score

4.3 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: March 26, 2025, 2:15 p.m.
Last Modified: March 27, 2025, 4:45 p.m.

Status : Awaiting Analysis

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

More info

Source

security-advisories@github.com

*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.