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Analyze » 6sense » IQVCOM6SETELFIN1772188194

Incident Score: Analysis & Impact (IQVCOM6SETELFIN1772188194)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-184
Company Score Before Incident762 / 1000
Company Score After Incident578 / 1000
INCIDENT NUMBERIQVCOM6SETELFIN1772188194
Type of Cyber IncidentBreach
ATTACK VECTORExploitation of sensitive data collected by data brokers
DATA EXPOSEDDates of birth, addresses, Social...
INCIDENT DATE31/07/2025
STATUSOngoing

Key Highlights From The Incident Analysis

  • Timeline of 6sense'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 6sense 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 6sense breach identified under incident ID IQVCOM6SETELFIN1772188194.

The analysis begins with a detailed overview of 6sense's information like the linkedin page: https://www.linkedin.com/company/6sense, the number of followers: 113059, the industry type: Software Development and the number of employees: 1583 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 762 and after the incident was 578 with a difference of -184 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 6sense and their customers.

On 12 July 2024, Comscore disclosed Data Breach issues under the banner "Data Broker Breaches Leading to $20.9 Billion in Consumer Losses".

A minority report from the U.S.

The disruption is felt across the environment, and exposing Dates of birth, addresses, Social Security numbers, personally identifiable information, plus an estimated financial loss of $20.9 billion in consumer losses.

In response, moved swiftly to contain the threat with measures like Removal of 'no index' tags, improved opt-out accessibility, and began remediation that includes Comscore, Telesign, and 6Sense removed 'no index' codes; Telesign added footer links.

The case underscores how Ongoing, teams are taking away lessons such as Data brokers' lack of transparency and compliance poses significant financial and operational risks. Obscured opt-out tools and dark patterns exacerbate identity theft risks, and recommending next steps like Improve opt-out tool accessibility, enhance transparency, conduct third-party audits, and ensure compliance with privacy regulations.

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 Acquire Infrastructure: Domains (T1583.001) with moderate confidence (60%), supported by evidence indicating data brokers were hiding opt-out tools using no index instructions and Exploit Public-Facing Application (T1190) with moderate confidence (50%), supported by evidence indicating exploitation of sensitive data collected by data brokers. Under the Credential Access tactic, the analysis identified Gather Victim Identity Information: Credentials (T1589.001) with high confidence (90%), supported by evidence indicating dates of birth, addresses, and Social Security numbers exploited and Gather Victim Identity Information: Email Addresses (T1589.002) with moderate to high confidence (70%), supported by evidence indicating personally identifiable information compromised via data brokers. Under the Collection tactic, the analysis identified Data from Information Repositories (T1213) with high confidence (90%), supported by evidence indicating data brokers collect sensitive data including SSNs and addresses and Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating sensitive data exploited for personalized fraud schemes. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), supported by evidence indicating $20.9 billion in consumer losses tied to identity theft and Automated Exfiltration (T1020) with moderate confidence (60%), supported by evidence indicating scammers exploit sensitive data for fraud schemes. Under the Defense Evasion tactic, the analysis identified Hide Artifacts: Hidden Files and Directories (T1564.001) with high confidence (90%), supported by evidence indicating no index instructions used to hide opt-out tools from search engines and Masquerading: Match Legitimate Name or Location (T1036.005) with moderate to high confidence (70%), supported by evidence indicating opt-out links buried in lengthy privacy notices (>9,000 words). Under the Impact tactic, the analysis identified Data Destruction (T1485) with lower confidence (40%), supported by evidence indicating lack of transparency and compliance in data handling and Defacement: Internal Defacement (T1491.001) with moderate confidence (50%), supported by evidence indicating negative brand reputation impact due to obscured opt-out tools. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Acquire Infrastructure: Domains (60%)
Exploit Public-Facing Application (50%)
Credential Access
Gather Victim Identity Information: Credentials (90%)
Gather Victim Identity Information: Email Addresses (70%)
Collection
Data from Information Repositories (90%)
Data from Local System (80%)
Exfiltration
Exfiltration Over C2 Channel (80%)
Automated Exfiltration (60%)
Defense Evasion
Hide Artifacts: Hidden Files and Directories (90%)
Masquerading: Match Legitimate Name or Location (70%)
Impact
Data Destruction (40%)
Defacement: Internal Defacement (50%)