GitLab Breach Incident Score: Analysis & Impact (GIT5234552111325)

In this Rankiteo incident briefing, we review the GitLab breach identified under incident ID GIT5234552111325.

The analysis begins with a detailed overview of GitLab's information like the linkedin page: https://www.linkedin.com/company/gitlab-com, the number of followers: 1051242, the industry type: IT Services and IT Consulting and the number of employees: 3111 employees

After the initial compromise, the video explains how Rankiteo's incident engine converts technical details into a normalized incident score. The incident score before the incident was 784 and after the incident was 779 with a difference of -5 which is could be a good indicator of the severity and impact of the incident.

In the next step of the video, we will analyze in more details the incident and the impact it had on GitLab and their customers.

GitLab Inc. recently reported "GitLab Critical Security Patches Addressing Multiple Vulnerabilities Including Prompt-Injection Flaw in GitLab Duo", a noteworthy cybersecurity incident.

GitLab has released critical security patches addressing nine vulnerabilities across Community Edition (CE) and Enterprise Edition (EE), including a particularly concerning prompt-injection flaw in GitLab Duo that could expose sensitive information from confidential issues.

The disruption is felt across the environment, affecting GitLab Community Edition (CE), GitLab Enterprise Edition (EE) and GitLab Duo (AI-powered review feature), and exposing Sensitive information from confidential issues (CVE-2025-6945), Confidential branch names (CVE-2025-7000) and Restricted branch names (CVE-2025-6171).

In response, teams activated the incident response plan, moved swiftly to contain the threat with measures like Release of security patches (versions 18.5.2, 18.4.4, 18.3.6) and Immediate upgrade recommendation for self-managed installations, and began remediation that includes Patching prompt-injection flaw in GitLab Duo, Fixing XSS vulnerability in Kubernetes proxy and Addressing authorization bypass in workflows, and stakeholders are being briefed through Public security advisory, Urgent upgrade notification for self-managed customers and Transparency about affected versions and vulnerabilities.

The case underscores how Resolved (patches released), teams are taking away lessons such as AI-powered features (e.g., GitLab Duo) introduce new attack surfaces requiring robust input validation, Stored XSS vulnerabilities in proxy functionalities can have broad impact across integrated systems (e.g., Kubernetes) and Access control mechanisms require continuous review to prevent authorization bypasses and information disclosure, and recommending next steps like Immediately upgrade self-managed GitLab instances to patched versions (18.5.2, 18.4.4, or 18.3.6), Review and harden input validation for AI-powered features to prevent prompt-injection attacks and Audit Kubernetes proxy configurations to mitigate XSS risks, with advisories going out to stakeholders covering Urgent upgrade notification for self-managed customers and Security advisory detailing vulnerabilities and mitigations.

Finally, we try to match the incident with the MITRE ATT&CK framework to see if there is any correlation between the incident and the MITRE ATT&CK framework.

The MITRE ATT&CK framework is a knowledge base of techniques and sub-techniques that are used to describe the tactics and procedures of cyber adversaries. It is a powerful tool for understanding the threat landscape and for developing effective defense strategies.

Rankiteo's analysis has identified several MITRE ATT&CK tactics and techniques associated with this incident, each with varying levels of confidence based on available evidence. Under the Initial Access tactic, the analysis identified Valid Accounts: Cloud Accounts (T1078.004) with high confidence (95%), supported by evidence indicating authenticated attackers/users exploiting GitLab Duo (CVE-2025-6945) and Kubernetes proxy (CVE-2025-11224). Under the Credential Access tactic, the analysis identified Unsecured Credentials: Credentials In Files (T1552.001) with moderate to high confidence (70%), supported by evidence indicating exposure of confidential issues via hidden prompts in merge request comments (CVE-2025-6945). Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), with evidence including leak sensitive information from confidential issues (CVE-2025-6945), and access confidential information through GraphQL (CVE-2025-2615) and Data from Information Repositories: Confluence/SharePoint/GitLab (T1213.001) with high confidence (95%), supported by evidence indicating unauthorized access to proprietary code, internal discussions, and project metadata. Under the Exfiltration tactic, the analysis identified Exfiltration Over Command and Control Channel (T1041) with moderate to high confidence (85%), supported by evidence indicating exfiltrate sensitive data from confidential issues via hidden prompts (CVE-2025-6945) and Automated Exfiltration: Traffic Duplication (T1020.001) with moderate to high confidence (75%), supported by evidence indicating graphQL WebSocket subscriptions enabling data access (CVE-2025-2615). Under the Persistence tactic, the analysis identified Server Software Component: Web Shell (T1505.003) with moderate to high confidence (80%), supported by evidence indicating stored XSS in Kubernetes proxy (CVE-2025-11224) enabling persistent script execution. Under the Privilege Escalation tactic, the analysis identified Exploitation for Privilege Escalation (T1068) with moderate to high confidence (85%), supported by evidence indicating incorrect authorization in workflows (CVE-2025-11865) allowing removal of others Duo workflows. Under the Defense Evasion tactic, the analysis identified Obfuscated Files or Information: Indicator Removal from Tools (T1027.005) with moderate to high confidence (70%), supported by evidence indicating hidden prompts in merge request comments (CVE-2025-6945) evading detection and Command and Scripting Interpreter: JavaScript (T1059.007) with high confidence (90%), supported by evidence indicating stored XSS in Kubernetes proxy (CVE-2025-11224) using JavaScript for evasion. Under the Impact tactic, the analysis identified Data Destruction (T1485) with moderate confidence (60%), supported by evidence indicating denial of Service in markdown (CVE-2025-12983) risking system disruption and Endpoint Denial of Service: Application or System Exploitation (T1499.004) with moderate confidence (65%), supported by evidence indicating denial of Service in markdown processing (CVE-2025-12983). These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.