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Analyze » GitHub » AMAVERGITSTR1775204764

Incident Score: Analysis & Impact (AMAVERGITSTR1775204764)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-14
Company Score Before Incident323 / 1000
Company Score After Incident309 / 1000
INCIDENT NUMBERAMAVERGITSTR1775204764
Type of Cyber IncidentCyber Attack
ATTACK VECTORRemote Code Execution (RCE)
DATA EXPOSEDDatabase credentials, SSH keys, AWS...
INCIDENT DATE02/04/2026
STATUSpublished

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 AMAVERGITSTR1775204764.

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 323 and after the incident was 309 with a difference of -14 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.

A newly reported cybersecurity incident, "Massive Credential Theft Campaign Exploits React2Shell Flaw in Next.js Applications", has drawn attention.

Cybersecurity researchers at Cisco Talos have uncovered a large-scale automated credential theft campaign orchestrated by the hacker group UAT-10608, which has compromised over 700 servers worldwide.

The disruption is felt across the environment, affecting Over 700 servers worldwide, and exposing Database credentials, SSH keys, AWS cloud tokens, Stripe payment keys, GitHub access tokens.

In response, and began remediation that includes Patch the React2Shell vulnerability, rotate exposed credentials.

The case underscores how teams are taking away lessons such as Urgent need for organizations using Next.js to patch the React2Shell vulnerability and rotate exposed credentials. Stolen data provides attackers with persistent access to critical systems, posing long-term security risks, and recommending next steps like Patch the React2Shell vulnerability (CVE-2025-55182) and rotate all exposed credentials, including database credentials, SSH keys, cloud tokens, payment keys, and GitHub access tokens.

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 (95%), supported by evidence indicating exploiting CVE-2025-55182 (React2Shell), a critical remote code execution (RCE) vulnerability. Under the Execution tactic, the analysis identified Exploitation for Client Execution (T1203) with high confidence (90%), supported by evidence indicating executing arbitrary commands without requiring authentication or user interaction and Command and Scripting Interpreter (T1059) with moderate to high confidence (85%), supported by evidence indicating deploys a malicious script that silently extracts sensitive data. Under the Credential Access tactic, the analysis identified Unsecured Credentials (T1552) with high confidence (95%), supported by evidence indicating extracts database credentials, SSH keys, AWS cloud tokens, Stripe payment keys, GitHub access tokens and Unsecured Credentials: Credentials In Files (T1552.001) with high confidence (90%), supported by evidence indicating over 90% of affected servers had database credentials stolen. Under the Lateral Movement tactic, the analysis identified Remote Services (T1021) with moderate to high confidence (80%), supported by evidence indicating nearly 80% lost private SSH keys, enabling lateral movement across networks. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating silently extracts sensitive data, including database credentials, SSH keys, AWS cloud tokens. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating nEXUS Listener recorded 766 compromised hosts in just 24 hours. Under the Command and Control tactic, the analysis identified Application Layer Protocol (T1071) with moderate to high confidence (85%), supported by evidence indicating custom web dashboard called the NEXUS Listener to manage the stolen data. Under the Persistence tactic, the analysis identified Account Manipulation (T1098) with moderate to high confidence (80%), supported by evidence indicating stolen data provides attackers with persistent access to critical systems and Server Software Component (T1505) with moderate to high confidence (75%), supported by evidence indicating malicious script deployed post-exploitation for credential extraction. Under the Impact tactic, the analysis identified Resource Hijacking (T1496) with moderate to high confidence (80%), supported by evidence indicating stolen cloud credentials could allow attackers to hijack entire cloud environments and Data Manipulation (T1565) with moderate to high confidence (70%), supported by evidence indicating compromised GitHub tokens risk malicious code injections into software updates. 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 (95%)
Execution
Exploitation for Client Execution (90%)
Command and Scripting Interpreter (85%)
Credential Access
Unsecured Credentials (95%)
Unsecured Credentials: Credentials In Files (90%)
Lateral Movement
Remote Services (80%)
Collection
Data from Local System (90%)
Exfiltration
Exfiltration Over C2 Channel (90%)
Command and Control
Application Layer Protocol (85%)
Persistence
Account Manipulation (80%)
Server Software Component (75%)
Impact
Resource Hijacking (80%)
Data Manipulation (70%)

Sources & References