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Analyze » GitLab » GITGAL1770201332

Incident Score: Analysis & Impact (GITGAL1770201332)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-1
Company Score Before Incident782 / 1000
Company Score After Incident781 / 1000
INCIDENT NUMBERGITGAL1770201332
Type of Cyber IncidentVulnerability
ATTACK VECTORCI Lint API
DATA EXPOSEDPotential data exposure
INCIDENT DATE31/12/2020
STATUSpublished

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 GITGAL1770201332.

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: 1101919, the industry type: IT Services and IT Consulting and the number of employees: 3318 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 782 and after the incident was 781 with a difference of -1 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 recently reported "Critical GitLab SSRF Vulnerability Under Active Exploitation, CISA Warns", a noteworthy cybersecurity incident.

CISA has added CVE-2021-39935, a severe server-side request forgery (SSRF) vulnerability in GitLab Community and Enterprise Editions, to its Known Exploited Vulnerabilities (KEV) catalog after confirming active exploitation in the wild.

The disruption is felt across the environment, affecting GitLab Community and Enterprise Editions, and exposing Potential data exposure.

In response, moved swiftly to contain the threat with measures like Patch or mitigate the vulnerability, discontinue use of affected instances if unable to patch, and began remediation that includes Upgrade to patched versions, review CI Lint API configurations, monitor logs for suspicious activity.

The case underscores how teams are taking away lessons such as The incident highlights the growing threat of SSRF attacks, which can evade traditional security measures by leveraging trusted servers as proxies for malicious activity, and recommending next steps like Upgrade immediately to patched versions, review CI Lint API configurations, monitor logs for suspicious activity, and adhere to BOD 22-01 guidance for securing cloud services, with advisories going out to stakeholders covering Federal Civilian Executive Branch (FCEB) agencies must patch or mitigate the vulnerability by February 24, 2026.

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%), supported by evidence indicating severe server-side request forgery (SSRF) vulnerability in GitLab Community and Enterprise Editions and External Remote Services (T1133) with moderate to high confidence (80%), supported by evidence indicating cI Lint API allowing unauthenticated attackers to manipulate the server. Under the Execution tactic, the analysis identified Exploitation for Client Execution (T1203) with moderate to high confidence (70%), supported by evidence indicating manipulate the server into making unauthorized requests to internal systems. Under the Credential Access tactic, the analysis identified Cloud Instance Metadata API (T1552.005) with moderate confidence (60%), supported by evidence indicating unauthorized access to cloud metadata or internal infrastructure. Under the Lateral Movement tactic, the analysis identified Exploitation of Remote Services (T1210) with moderate to high confidence (80%), supported by evidence indicating potentially move laterally within compromised networks. Under the Collection tactic, the analysis identified Data from Information Repositories (T1213) with moderate to high confidence (70%), supported by evidence indicating data exposure, supply chain compromise via CI/CD pipeline manipulation. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate confidence (60%), supported by evidence indicating potential data exposure via unauthorized requests to internal systems. Under the Defense Evasion tactic, the analysis identified Code Signing (T1553.002) with moderate confidence (50%), supported by evidence indicating supply chain compromise via CI/CD pipeline manipulation and Exploit Public-Facing Application (T1190) with moderate to high confidence (70%), supported by evidence indicating bypass perimeter defenses via SSRF vulnerability. 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%)
External Remote Services (80%)
Execution
Exploitation for Client Execution (70%)
Credential Access
Cloud Instance Metadata API (60%)
Lateral Movement
Exploitation of Remote Services (80%)
Collection
Data from Information Repositories (70%)
Exfiltration
Exfiltration Over C2 Channel (60%)
Defense Evasion
Code Signing (50%)
Exploit Public-Facing Application (70%)