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Analyze » Cyber Threat Intelligence ® » CYB1775831786

Incident Score: Analysis & Impact (CYB1775831786)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-63
Company Score Before Incident734 / 1000
Company Score After Incident671 / 1000
INCIDENT NUMBERCYB1775831786
Type of Cyber IncidentBreach
ATTACK VECTORCompromised VPN, Distributed Botnet Tools
DATA EXPOSEDOver 10 petabytes of sensitive...
INCIDENT DATE09/04/2026
STATUSOngoing, full verification pending

Key Highlights From The Incident Analysis

  • Timeline of Cyber Threat Intelligence ®'s Breach 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 Cyber Threat Intelligence ® 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 Cyber Threat Intelligence ® breach identified under incident ID CYB1775831786.

The analysis begins with a detailed overview of Cyber Threat Intelligence ®'s information like the linkedin page: https://www.linkedin.com/company/cyber-threat-intel, the number of followers: 213326, the industry type: Security and Investigations and the number of employees: 13 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 734 and after the incident was 671 with a difference of -63 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 Cyber Threat Intelligence ® and their customers.

National Supercomputing Center in Tianjin recently reported "Massive Alleged Data Breach Targets China’s Supercomputing Center, Exposing Sensitive Defense and Scientific Research", a noteworthy cybersecurity incident.

An alleged cyberattack on China’s National Supercomputing Center in Tianjin has resulted in the theft of over 10 petabytes of highly sensitive data, including defense-related documents, aerospace research, missile simulations, AI development, and nuclear fusion experiments.

The disruption is felt across the environment, affecting National Supercomputing Center in Tianjin, and exposing Over 10 petabytes of sensitive data.

Formal response steps have not been shared publicly yet.

The case underscores how Ongoing, full verification pending, teams are taking away lessons such as The breach underscores persistent weaknesses in perimeter defenses, even in advanced nations, and highlights the need for stronger segmentation, monitoring, and security in shared computing ecosystems critical to global research, and recommending next steps like Strengthen perimeter defenses, Implement network segmentation and Enhance monitoring for distributed data exfiltration.

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 External Remote Services (T1133) with high confidence (90%), supported by evidence indicating exploiting a compromised VPN to gain initial access. Under the Persistence tactic, the analysis identified Account Manipulation (T1098) with moderate to high confidence (70%), supported by evidence indicating attackers exploited a compromised VPN over several months. Under the Defense Evasion tactic, the analysis identified Automated Exfiltration (T1020) with moderate to high confidence (80%), supported by evidence indicating transferring files through multiple channels to evade security monitoring and Hide Artifacts: Hidden Window (T1564.003) with moderate to high confidence (70%), supported by evidence indicating distributed botnet tools to extract data in small, undetected chunks. Under the Credential Access tactic, the analysis identified Brute Force: Password Guessing (T1110.001) with moderate confidence (60%), supported by evidence indicating compromised VPN suggests potential credential compromise and Unsecured Credentials: Private Keys (T1552.004) with moderate confidence (50%), supported by evidence indicating exploited architectural flaws in perimeter defenses. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating defense-related documents, aerospace research, missile simulations compromised and Data from Information Repositories (T1213) with moderate to high confidence (80%), supported by evidence indicating nuclear fusion experiments and AI development data stolen. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating 10 petabytes of data exfiltrated via distributed botnet tools and Exfiltration Over Web Service: Exfiltration to Cloud Storage (T1567.002) with moderate to high confidence (70%), supported by evidence indicating samples surfaced on encrypted platforms like Telegram. Under the Impact tactic, the analysis identified Defacement: Internal Defacement (T1491.001) with moderate confidence (50%), supported by evidence indicating severe reputational damage to China’s cybersecurity posture and Financial Theft (T1657) with moderate to high confidence (80%), supported by evidence indicating data priced in hundreds of thousands of dollars, payable in cryptocurrency. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
External Remote Services (90%)
Persistence
Account Manipulation (70%)
Defense Evasion
Automated Exfiltration (80%)
Hide Artifacts: Hidden Window (70%)
Credential Access
Brute Force: Password Guessing (60%)
Unsecured Credentials: Private Keys (50%)
Collection
Data from Local System (90%)
Data from Information Repositories (80%)
Exfiltration
Exfiltration Over C2 Channel (90%)
Exfiltration Over Web Service: Exfiltration to Cloud Storage (70%)
Impact
Defacement: Internal Defacement (50%)
Financial Theft (80%)

Sources & References