IAB Breach Incident Score: Analysis & Impact (INTYAHIAB1766434075)

In this Rankiteo incident briefing, we review the IAB breach identified under incident ID INTYAHIAB1766434075.

The analysis begins with a detailed overview of IAB's information like the linkedin page: https://www.linkedin.com/company/iab, the number of followers: 126086, the industry type: Advertising Services and the number of employees: 730 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 758 and after the incident was 699 with a difference of -59 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 IAB and their customers.

Yahoo recently reported "an incident", a noteworthy cybersecurity incident.

A cyber incident involving the storage and/or access of information on devices (cookies), use of precise geolocation data, IP addresses, browsing and search data for analytics, personalized advertising, content measurement, and audience research.

The disruption is felt across the environment, affecting Websites and apps owned and operated by Yahoo, AOL, Engadget, In The Know, Makers, and exposing Device information, geolocation data, IP addresses, browsing and search data.

In response, and stakeholders are being briefed through Privacy & Cookie Settings and Privacy Dashboard links provided for user consent management.

The case underscores how and recommending next steps like Users should review and manage their consent settings via 'Privacy & Cookie Settings' or 'Privacy Dashboard' links. Companies should ensure transparent data collection practices and provide clear opt-out mechanisms, with advisories going out to stakeholders covering Users can withdraw consent or change choices via 'Privacy & Cookie Settings' or 'Privacy Dashboard' links.

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.

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 Collection tactic, the analysis identified Data from Cloud Storage (T1530) with moderate to high confidence (80%), with evidence including storage and access of information on devices (cookies), and use of precise geolocation data, IP addresses, browsing and search data, Data from Information Repositories (T1213) with moderate to high confidence (70%), supported by evidence indicating collection of visitor counts, device types, browsers, and visit duration, and Input Capture (T1417) with moderate to high confidence (70%), supported by evidence indicating tracking of browsing history and search activity for analytics. Under the Initial Access tactic, the analysis identified Drive-by Compromise (T1189) with moderate confidence (60%), supported by evidence indicating data collection spans multiple platforms including Yahoo, AOL, Engadget. Under the Credential Access tactic, the analysis identified Steal Web Session Cookie (T1539) with moderate to high confidence (70%), supported by evidence indicating storage and access of device information (such as cookies). Under the Discovery tactic, the analysis identified Cloud Storage Object Discovery (T1619) with moderate confidence (60%), supported by evidence indicating extensive reach of data-sharing networks in digital advertising and Account Discovery (T1087) with moderate confidence (50%), supported by evidence indicating visitor counts, device types (iOS/Android), browser usage tracked. Under the Exfiltration tactic, the analysis identified Automated Exfiltration (T1020) with moderate confidence (60%), supported by evidence indicating data collection for analytics, personalized advertising, content measurement. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.