CVE-2026-3176
GitLab vulnerability analysis and mitigation

Overview

CVE-2026-3176 is a Missing Authorization vulnerability in GitLab Enterprise Edition (EE) that allows authenticated users with limited permissions to access project information under certain conditions due to insufficient authorization checks. It affects GitLab EE versions 18.6 through 18.11.5, 19.0 through 19.0.2, and 19.1.0, and was disclosed on June 25, 2026. The vulnerability carries a CVSS v3.1 base score of 3.1 (Low) (GitHub Advisory, GitLab Patch Release).

Technical details

The root cause is classified as CWE-862 (Missing Authorization), where the application fails to perform adequate authorization checks when an authenticated user attempts to access project information under specific conditional operations. The attack vector is network-based, requires low privileges (an authenticated account), and has high attack complexity, meaning exploitation is not straightforward and depends on specific conditions being met. No public technical write-ups or proof-of-concept code have been identified (GitHub Advisory, GitLab Patch Release).

Impact

Successful exploitation results in a limited confidentiality breach, allowing an authenticated user with restricted permissions to view project information they are not authorized to access. There is no impact on integrity or availability. The scope is limited to the affected GitLab EE instance, and lateral movement potential is low given the constrained nature of the information disclosure (GitHub Advisory).

Mitigation and workarounds

GitLab has released patched versions addressing this vulnerability: 18.11.6, 19.0.3, and 19.1.1. Administrators should upgrade GitLab EE to one of these versions as soon as possible. As a post-remediation step, GitLab recommends reviewing access logs to identify any potential exploitation and auditing project access permissions to ensure they reflect intended authorization levels (GitLab Patch Release, GitHub Advisory).

Additional resources


SourceThis report was generated using AI

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