Incident Score: Analysis & Impact (TRIVER1786618728)
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Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of Tridium'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 Tridium 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 Tridium breach identified under incident ID TRIVER1786618728.
The analysis begins with a detailed overview of Tridium's information like the linkedin page: https://www.linkedin.com/company/tridium, the number of followers: 28486, the industry type: Software Development and the number of employees: 187 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 753 and after the incident was 751 with a difference of -2 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 Tridium and their customers.
A newly reported cybersecurity incident, "Thousands of Industrial Control Systems Exposed Near U.S. Data Centers, Raising Physical Security Risks", has drawn attention.
A recent internet-exposure analysis uncovered over 6,300 high-confidence industrial control system (ICS) and building automation devices accessible near 1,063 U.S.
The disruption is felt across the environment, affecting Industrial control systems (ICS), building automation systems, power-management systems.
In response, and began remediation that includes Identify and secure internet-reachable OT systems, enforce network segmentation, monitor for abnormal control traffic.
The case underscores how teams are taking away lessons such as Data center operators must secure all internet-reachable OT systems, enforce strict network segmentation, and monitor for abnormal control traffic to mitigate regional risks, and recommending next steps like Identify and secure all internet-reachable OT systems, Enforce strict network segmentation and Monitor for abnormal control traffic.
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 6,300 high-confidence industrial control system (ICS) and building automation devices accessible and External Remote Services (T1133) with moderate to high confidence (80%), supported by evidence indicating publicly reachable devices including BACnet controllers, Niagara Framework instances. Under the Credential Access tactic, the analysis identified Brute Force: Password Guessing (T1110.001) with moderate to high confidence (80%), supported by evidence indicating exploiting weak authentication and default credentials and Valid Accounts (T1078) with moderate to high confidence (70%), supported by evidence indicating default credentials, lack of network segmentation. Under the Lateral Movement tactic, the analysis identified Lateral Movement in OT Environments (T0866) with moderate to high confidence (70%), supported by evidence indicating 143 multi-protocol gateways acting as high-value aggregation points bridging HVAC, environmental, and electrical subsystems. Under the Impact tactic, the analysis identified Manipulation of Control (T0880) with high confidence (90%), supported by evidence indicating alter temperature setpoints, disrupt monitoring, lock out personnel, or trigger protective shutdowns and Loss of Availability (T0829) with high confidence (90%), supported by evidence indicating physical availability disruptions rather than just data loss. Under the Reconnaissance tactic, the analysis identified Active Scanning (T1595) with moderate to high confidence (80%), supported by evidence indicating shodan data used to identify publicly reachable devices and Gather Victim Network Information (T1590) with moderate to high confidence (70%), supported by evidence indicating geolocation data revealed clusters of exposed devices near hyperscale data centers. Under the Defense Evasion tactic, the analysis identified Indicator Removal from Tools (T0856) with moderate confidence (50%), supported by evidence indicating lack of monitoring for abnormal control traffic. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- Tridium Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/tridium/incident/TRIVER1786618728
- Tridium CyberSecurity Rating page: https://www.rankiteo.com/company/tridium
- Tridium Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/triver1786618728-tridium-vertiv-vulnerability-september-2024/
- Tridium CyberSecurity Score History: https://www.rankiteo.com/company/tridium/history
- Tridium CyberSecurity Incident Source: https://gbhackers.com/6330-internet-exposed-ics-devices/
- Rankiteo A.I CyberSecurity Rating methodology: https://www.rankiteo.com/Images/rankiteo_algo.pdf
- Rankiteo TPRM Scoring methodology: https://static.rankiteo.com/model/rankiteo_tprm_methodology.pdf