Incident Score: Analysis & Impact (FOR1772677952)
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Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of Forrester'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 Forrester 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 Forrester breach identified under incident ID FOR1772677952.
The analysis begins with a detailed overview of Forrester's information like the linkedin page: https://www.linkedin.com/company/forrester-research, the number of followers: 381189, the industry type: Research Services and the number of employees: 1689 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 749 and after the incident was 682 with a difference of -67 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 Forrester and their customers.
A newly reported cybersecurity incident, "Forrester Research Highlights Persistent Breach Risks Despite Rising Security Budgets", has drawn attention.
New findings from Forrester reveal that while organizations are increasing investments in security and privacy programs, breach frequency remains stubbornly high.
The disruption is felt across the environment, and exposing sensitive data.
Formal response steps have not been shared publicly yet.
The case underscores how teams are taking away lessons such as External attacks, insider incidents, and supply-chain vulnerabilities continue to dominate breach causes. Rapid AI adoption introduces new risks, and security/privacy teams often lag behind deployment. Detection and response remain critical, but visibility gaps, alert fatigue, and tool complexity limit effectiveness. Cloud complexity and fragmented policy frameworks further complicate security operations, and recommending next steps like Improve AI governance, Develop frameworks to assess privacy risks from generative AI systems and Prioritize detection and response.
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 moderate confidence (60%), supported by evidence indicating external attacks...continue to dominate breach causes and Supply Chain Compromise (T1195) with moderate to high confidence (70%), supported by evidence indicating supply-chain vulnerabilities continue to dominate breach causes. Under the Credential Access tactic, the analysis identified Valid Accounts (T1078) with moderate to high confidence (80%), supported by evidence indicating identity and access management (IAM) sees growing investment and Unsecured Credentials (T1552) with moderate confidence (50%), supported by evidence indicating visibility gaps, alert fatigue, and tool complexity limit effectiveness. Under the Persistence tactic, the analysis identified Account Manipulation (T1098) with moderate confidence (60%), supported by evidence indicating employee IAM rising from 22% to 25% year-over-year. Under the Collection tactic, the analysis identified Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating 67% of security decision-makers confirming sensitive data was compromised. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (70%), supported by evidence indicating sensitive data was compromised despite expanded defenses. Under the Defense Evasion tactic, the analysis identified Impair Defenses: Disable or Modify Tools (T1562.001) with moderate confidence (60%), supported by evidence indicating tool complexity limit the effectiveness of these efforts and Valid Accounts: Cloud Accounts (T1078.004) with moderate to high confidence (70%), supported by evidence indicating 63% of public cloud decision-makers planning to increase their number of providers. Under the Impact tactic, the analysis identified Data Destruction (T1485) with lower confidence (40%), supported by evidence indicating breach frequency remains stubbornly high. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- Forrester Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/forrester-research/incident/FOR1772677952
- Forrester CyberSecurity Rating page: https://www.rankiteo.com/company/forrester-research
- Forrester Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/for1772677952-forrester-research-breach-march-2025/
- Forrester CyberSecurity Score History: https://www.rankiteo.com/company/forrester-research/history
- Forrester CyberSecurity Incident Source: https://securitybrief.asia/story/ai-adoption-drives-security-spend-but-breaches-persist
- 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