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Analyze » GitLab » GIT1785155190

Incident Score: Analysis & Impact (GIT1785155190)

The details regarding individual company incidents & reports gives you full view from every side.

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-4
Company Score Before Incident753 / 1000
Company Score After Incident749 / 1000
INCIDENT NUMBERGIT1785155190
Type of Cyber IncidentVulnerability
ATTACK VECTORMaliciously crafted Jupyter Notebook (.ipynb) files in commit-diff requests
DATA EXPOSEDRepositories, Secrets
INCIDENT DATE20/05/2026
STATUSCompleted

Key Highlights From The Incident Analysis

  • Timeline of GitLab's Vulnerability and lateral movement inside company's environment.
  • Overview of affected data sets, including SSNs and PHI, and why they materially increase incident severity.
  • How Rankiteo’s incident engine converts technical details into a normalized incident score.
  • How this cyber incident impacts GitLab Rankiteo cyber scoring and cyber rating.
  • Rankiteo’s MITRE ATT&CK correlation analysis for this incident, with associated confidence level.

Full Incident Analysis Transcript

In this Rankiteo incident briefing, we review the GitLab breach identified under incident ID GIT1785155190.

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: 1162783, the industry type: IT Services and IT Consulting and the number of employees: 3422 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 753 and after the incident was 749 with a difference of -4 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.

On 10 June 2026, GitLab disclosed Remote Code Execution (RCE) issues under the banner "Critical GitLab RCE Vulnerability Exploits Ruby JSON Parser Flaws".

A newly disclosed vulnerability in GitLab allows remote code execution (RCE) by chaining two long-standing memory-safety flaws in the Oj JSON parsing library, a high-performance Ruby dependency.

The disruption is felt across the environment, affecting GitLab CE/EE, and exposing Repositories and Secrets.

In response, moved swiftly to contain the threat with measures like Patches released for affected versions, and began remediation that includes Upgraded Oj gem to version 3.17.3 and Released GitLab patches (18.10.8, 18.11.5, 19.0.2).

The case underscores how Completed, teams are taking away lessons such as Risks in memory-unsafe Ruby extensions and the importance of timely patching for dependencies, and recommending next steps like Immediately upgrade GitLab to patched versions (18.10.8, 18.11.5, 19.0.2), Upgrade Oj gem to version 3.17.3 or later and Monitor for suspicious commit-diff requests involving .ipynb files, with advisories going out to stakeholders covering GitLab.com patched pre-disclosure; self-managed instances advised to upgrade immediately.

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.

MITRE ATT&CK® Correlation Analysis

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 Exploit Public-Facing Application (T1190) with high confidence (90%), with evidence including vulnerability in GitLab allows remote code execution (RCE), and targets default GitLab installations and Valid Accounts (T1078) with moderate to high confidence (80%), supported by evidence indicating authenticated user with standard push and diff-view permissions. Under the Execution tactic, the analysis identified Exploitation for Client Execution (T1203) with high confidence (90%), supported by evidence indicating execute arbitrary commands...via maliciously crafted notebooks and Command and Scripting Interpreter (T1059) with moderate to high confidence (80%), supported by evidence indicating gain code execution as the git system user. Under the Privilege Escalation tactic, the analysis identified Exploitation for Privilege Escalation (T1068) with moderate to high confidence (80%), with evidence including bypass Address Space Layout Randomisation (ASLR), and gain code execution as the git system user. Under the Defense Evasion tactic, the analysis identified Obfuscated Files or Information (T1027) with moderate to high confidence (70%), supported by evidence indicating maliciously crafted Jupyter Notebook (.ipynb) files and Impair Defenses: Disable or Modify Tools (T1562.001) with moderate confidence (60%), supported by evidence indicating bypass Address Space Layout Randomisation (ASLR). Under the Credential Access tactic, the analysis identified Unsecured Credentials: Credentials In Files (T1552.001) with moderate to high confidence (80%), supported by evidence indicating steal secrets...via its internal intranet system. Under the Collection tactic, the analysis identified Data from Information Repositories (T1213) with high confidence (90%), supported by evidence indicating access repositories, steal secrets. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (70%), supported by evidence indicating compromise internal services...via RCE. Under the Impact tactic, the analysis identified Resource Hijacking (T1496) with moderate to high confidence (70%), supported by evidence indicating compromise internal services. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Exploit Public-Facing Application (90%)
Valid Accounts (80%)
Execution
Exploitation for Client Execution (90%)
Command and Scripting Interpreter (80%)
Privilege Escalation
Exploitation for Privilege Escalation (80%)
Defense Evasion
Obfuscated Files or Information (70%)
Impair Defenses: Disable or Modify Tools (60%)
Credential Access
Unsecured Credentials: Credentials In Files (80%)
Collection
Data from Information Repositories (90%)
Exfiltration
Exfiltration Over C2 Channel (70%)
Impact
Resource Hijacking (70%)

Sources & References