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Analyze » GitLab » MOZPHAGITPROGOOGIT1780935989

Incident Score: Analysis & Impact (MOZPHAGITPROGOOGIT1780935989)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-18
Company Score Before Incident768 / 1000
Company Score After Incident750 / 1000
INCIDENT NUMBERMOZPHAGITPROGOOGIT1780935989
Type of Cyber IncidentCyber Attack
ATTACK VECTORMalicious emails with fake job offers and code-review requests, malicious GitHub/GitLab repositories
DATA EXPOSEDBrowser credentials, cryptocurrency wallet data,...
INCIDENT DATE31/03/2026
STATUSOngoing

Key Highlights From The Incident Analysis

  • Timeline of GitLab's Cyber Attack 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 MOZPHAGITPROGOOGIT1780935989.

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 768 and after the incident was 750 with a difference of -18 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.

A newly reported cybersecurity incident, "North Korean Threat Actor Targets Developers in Large-Scale Phishing Campaign", has drawn attention.

A likely North Korean threat actor conducted a sophisticated phishing campaign targeting nearly 100 organizations primarily in the U.S.

The disruption is felt across the environment, affecting macOS, Linux, Windows systems running VS Code or Cursor, and exposing Browser credentials, cryptocurrency wallet data, saved passwords, cookies, plus an estimated financial loss of Cryptocurrency wallet drainage.

Formal response steps have not been shared publicly yet.

The case underscores how Ongoing.

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 Phishing: Spearphishing Link (T1566.001) with high confidence (90%), supported by evidence indicating sent over 250 malicious emails with fake job offers and code-review requests and Phishing: Spearphishing Attachment (T1566.002) with moderate to high confidence (80%), supported by evidence indicating lure victims into cloning malicious GitHub or GitLab repositories. Under the Execution tactic, the analysis identified Command and Scripting Interpreter: JavaScript (T1059.007) with moderate to high confidence (80%), supported by evidence indicating windows ran JavaScript directly in the editor, leaving no disk footprint, User Execution: Malicious File (T1204.002) with moderate to high confidence (70%), supported by evidence indicating exploiting a legitimate editor feature via tasks.json file executed automatically, and Inter-Process Communication: Component Object Model (T1559.001) with moderate confidence (60%), supported by evidence indicating fake Google-themed VS Code extension ensuring persistence. Under the Persistence tactic, the analysis identified Event Triggered Execution: Installer Packages (T1546.016) with moderate to high confidence (80%), supported by evidence indicating fake Google-themed VS Code extension relaunching on macOS/Linux reopen and Boot or Logon Autostart Execution: Active Setup (T1547.014) with moderate to high confidence (70%), supported by evidence indicating malware installed a fake extension ensuring persistence. Under the Privilege Escalation tactic, the analysis identified Abuse Elevation Control Mechanism: Sudo and Sudo Caching (T1548.003) with moderate to high confidence (80%), supported by evidence indicating macOS/Linux displayed a fake password prompt to escalate privileges. Under the Defense Evasion tactic, the analysis identified Indicator Removal: File Deletion (T1070.004) with high confidence (90%), supported by evidence indicating after exfiltration, the malware deleted itself to evade detection, Deobfuscate/Decode Files or Information (T1140) with moderate confidence (60%), supported by evidence indicating malware likely used obfuscation to bypass security, and Hide Artifacts: Hidden Window (T1564.003) with moderate to high confidence (70%), supported by evidence indicating cursor ran the payload silently without user interaction. Under the Credential Access tactic, the analysis identified Credentials from Password Stores: Credentials from Web Browsers (T1555.003) with high confidence (90%), supported by evidence indicating targeted saved passwords & cookies from Chrome, Brave, Edge, and Firefox, Unsecured Credentials: Credentials In Files (T1552.001) with moderate to high confidence (80%), supported by evidence indicating dumped keychains on macOS/Linux using fake password prompt, and Steal Web Session Cookie (T1539) with moderate to high confidence (80%), supported by evidence indicating targeted browser cookies from Chrome, Brave, Edge, and Firefox. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating targeted cryptocurrency wallets and browser credentials and Automated Collection (T1119) with moderate to high confidence (70%), supported by evidence indicating malware targeted browser extensions and desktop wallets. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating go-based RAT from Overlord framework for remote access and Exfiltration Over Web Service: Exfiltration to Cloud Storage (T1567.002) with moderate confidence (60%), supported by evidence indicating malware likely exfiltrated data to attacker-controlled infrastructure. Under the Impact tactic, the analysis identified Resource Hijacking (T1496) with moderate to high confidence (80%), supported by evidence indicating cryptocurrency wallet drainage for financial gain. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Phishing: Spearphishing Link (90%)
Phishing: Spearphishing Attachment (80%)
Execution
Command and Scripting Interpreter: JavaScript (80%)
User Execution: Malicious File (70%)
Inter-Process Communication: Component Object Model (60%)
Persistence
Event Triggered Execution: Installer Packages (80%)
Boot or Logon Autostart Execution: Active Setup (70%)
Privilege Escalation
Abuse Elevation Control Mechanism: Sudo and Sudo Caching (80%)
Defense Evasion
Indicator Removal: File Deletion (90%)
Deobfuscate/Decode Files or Information (60%)
Hide Artifacts: Hidden Window (70%)
Credential Access
Credentials from Password Stores: Credentials from Web Browsers (90%)
Unsecured Credentials: Credentials In Files (80%)
Steal Web Session Cookie (80%)
Collection
Data from Local System (90%)
Automated Collection (70%)
Exfiltration
Exfiltration Over C2 Channel (90%)
Exfiltration Over Web Service: Exfiltration to Cloud Storage (60%)
Impact
Resource Hijacking (80%)