CVE-2026-92529 in GitLab
Summary
by MITRE • 09/24/2026
GitLab has remediated an issue in GitLab EE affecting all versions from 19.1 before 19.2.7, 19.3 before 19.3.3, and 19.4 before 19.4.1 that under certain conditions could have allowed an authenticated user with developer-role permissions to bypass admin-configured AI tool governance controls for workflows in namespaces they do not control due to improper authorization checks.
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Analysis
by VulDB Data Team • 09/24/2026
GitLab has addressed a critical security vulnerability within its Enterprise Edition, specifically impacting version ranges 19.1 prior to 19.2.7, 19.3 prior to 19.3.3, and 19.4 prior to 19.4.1. This flaw stems from an improper authorization check mechanism that governs access control for AI tool governance features. The vulnerability allows authenticated users possessing developer-level permissions in a specific namespace to circumvent administrative policies designed to restrict or manage the use of artificial intelligence tools within workflows. These restrictions are typically enforced at the project or group level by system administrators who configure governance controls to ensure compliance, security standards, and appropriate resource usage across the organization's development environment.
The core technical flaw lies in the logic that validates user permissions when interacting with AI-driven workflow features. Under normal circumstances, an administrator configures policies that dictate which users can access specific AI tools or how those tools are applied within certain namespaces. However, due to a lapse in authorization verification, developers who do not own or control the target namespace were able to trigger these AI functionalities despite being explicitly denied by the configured governance rules. This bypass occurs because the system failed to adequately cross-reference the user's role and permissions against the restrictive policies set for that specific context, effectively treating developer-level access as sufficient override authority over administrative constraints in this particular module.
The operational impact of this vulnerability is significant from a compliance and security posture perspective. Organizations rely on AI governance controls to prevent data leakage, ensure code quality standards, and manage computational costs associated with large language model integrations. By allowing unauthorized users to bypass these controls, the vulnerability exposes sensitive intellectual property and internal workflows to potential misuse or exposure through unvetted AI interactions. Furthermore, it undermines the principle of least privilege by granting lower-level roles capabilities that should be reserved for higher-privileged administrators or explicitly whitelisted entities. This could lead to unintended data exfiltration if the AI tools process confidential code snippets or proprietary information without proper oversight.
From a classification standpoint, this issue aligns with CWE-269, which denotes Improper Privilege Management, specifically involving authorization bypasses where users gain access to resources they are not permitted to use. In terms of attack vectors and tactics, it relates to ATT&CK techniques concerning privilege escalation or abuse of existing permissions within a trusted environment. The vulnerability highlights the complexity of enforcing granular security policies in complex software ecosystems where multiple layers of permission checks must interact correctly.
To mitigate this risk, organizations running affected versions should immediately upgrade GitLab Enterprise Edition to version 19.2.7, 19.3.3, or 19.4.1 and later, depending on their current release track. These patched releases contain the necessary code corrections to enforce proper authorization checks for AI tool governance controls. Until an upgrade is performed, administrators should closely monitor usage logs of AI-related features within namespaces where strict policies are in place, looking for anomalies that might indicate exploitation by developer-level accounts. Additionally, reviewing and tightening existing permission structures can help minimize the blast radius if similar vulnerabilities exist elsewhere in the platform. Regular audits of administrative configurations against actual user activity remain a best practice to detect any potential policy violations or unauthorized access attempts promptly.