CVE-2025-9078

Sept. 16, 2025, 3:58 p.m.

4.3
Medium

Description

Mattermost versions 10.8.x <= 10.8.3, 10.5.x <= 10.5.8, 9.11.x <= 9.11.17, 10.10.x <= 10.10.1, 10.9.x <= 10.9.3 fail to properly validate cache keys for link metadata which allows authenticated users to access unauthorized posts and poison link previews via hash collision attacks on FNV-1 hashing

Product(s) Impacted

Vendor Product Versions
Mattermost
  • Mattermost Server
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-328
Use of Weak Hash
The product uses an algorithm that produces a digest (output value) that does not meet security expectations for a hash function that allows an adversary to reasonably determine the original input (preimage attack), find another input that can produce the same hash (2nd preimage attack), or find multiple inputs that evaluate to the same hash (birthday attack).

*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 mattermost mattermost_server / / / / / / / /
a mattermost mattermost_server / / / / / / / /
a mattermost mattermost_server / / / / / / / /
a mattermost mattermost_server / / / / / / / /
a mattermost mattermost_server / / / / / / / /

CVSS Score

4.3 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: Sept. 15, 2025, 10:15 a.m.
Last Modified: Sept. 16, 2025, 3:58 p.m.

Status : Analyzed

CVE is currently being analyzed by NVD staff, this process results in association of reference link tags, CVSS scores, CWE association, and CPE applicability statements.

More info

Source

responsibledisclosure@mattermost.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.