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Analyze » GitHub » GIT1774874082

Incident Score: Analysis & Impact (GIT1774874082)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-30
Company Score Before Incident416 / 1000
Company Score After Incident386 / 1000
INCIDENT NUMBERGIT1774874082
Type of Cyber IncidentCyber Attack
ATTACK VECTORGitHub Discussions (social engineering, fake security alerts)
DATA EXPOSEDBrowser data, operating system details,...
INCIDENT DATE29/03/2026
STATUSOngoing (no malware or credential harvesting observed yet)

Key Highlights From The Incident Analysis

  • Timeline of GitHub'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 GitHub 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 GitHub breach identified under incident ID GIT1774874082.

The analysis begins with a detailed overview of GitHub's information like the linkedin page: https://www.linkedin.com/company/github, the number of followers: 5688458, the industry type: Software Development and the number of employees: 6007 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 416 and after the incident was 386 with a difference of -30 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 GitHub and their customers.

GitHub (developers and repositories) recently reported "Large-Scale Phishing Campaign Targets Developers via GitHub Discussions", a noteworthy cybersecurity incident.

A sophisticated phishing campaign is actively targeting developers on GitHub by exploiting the platform’s Discussions feature to distribute fake security alerts for Visual Studio Code (VS Code).

The disruption is felt across the environment, affecting Developer workstations (potential if malware is delivered in later phases), and exposing Browser data, operating system details, and other profiling information.

In response, and stakeholders are being briefed through Advisories to developers to scrutinize unsolicited security notifications.

The case underscores how Ongoing (no malware or credential harvesting observed yet), teams are taking away lessons such as GitHub’s Discussions feature is vulnerable to abuse due to lower moderation thresholds. Developers must verify security alerts, especially from new or low-activity accounts, and avoid external download links, and recommending next steps like GitHub should enhance moderation for Discussions, particularly for security-related posts, Developers should verify security advisories through official channels before acting and Organizations should educate developers on phishing tactics targeting code repositories, with advisories going out to stakeholders covering Developers and repository maintainers advised to scrutinize unsolicited security notifications and report suspicious activity.

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 (T1566.002) with high confidence (90%), with evidence including fake security alerts for VS Code with external download links, and urging users to download a supposed updated version and Spearphishing Link (T1192) with moderate to high confidence (80%), supported by evidence indicating attackers impersonate trusted maintainers or security researchers. Under the Execution tactic, the analysis identified User Execution: Malicious Link (T1204.001) with moderate to high confidence (80%), supported by evidence indicating victims land on a JavaScript-based profiling page upon clicking links. Under the Collection tactic, the analysis identified Data Staged: Local Data Staging (T1074.001) with moderate to high confidence (70%), supported by evidence indicating javaScript-based profiling page collects browser data, OS details and Automated Collection (T1119) with moderate to high confidence (70%), supported by evidence indicating profiling mechanism distinguishes real users from bots. Under the Defense Evasion tactic, the analysis identified Hide Artifacts: Hidden Users (T1564.002) with moderate to high confidence (70%), supported by evidence indicating newly created or low-activity accounts used to automate attack and Masquerading: Match Legitimate Name or Location (T1036.005) with moderate to high confidence (80%), supported by evidence indicating fake posts mimic legitimate security advisories with fabricated CVE IDs. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate confidence (60%), supported by evidence indicating profiling data collected suggests traffic distribution system. Under the Reconnaissance tactic, the analysis identified Active Scanning: Vulnerability Scanning (T1595.002) with moderate confidence (50%), supported by evidence indicating profiling page collects browser/OS details to filter targets. 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%)
Spearphishing Link (80%)
Execution
User Execution: Malicious Link (80%)
Collection
Data Staged: Local Data Staging (70%)
Automated Collection (70%)
Defense Evasion
Hide Artifacts: Hidden Users (70%)
Masquerading: Match Legitimate Name or Location (80%)
Exfiltration
Exfiltration Over C2 Channel (60%)
Reconnaissance
Active Scanning: Vulnerability Scanning (50%)

Sources & References