Social Security Administration Breach Incident Score: Analysis & Impact (SSA1773182549)

In this Rankiteo incident briefing, we review the Social Security Administration breach identified under incident ID SSA1773182549.

The analysis begins with a detailed overview of Social Security Administration's information like the linkedin page: https://www.linkedin.com/company/ssa, the number of followers: 194555, the industry type: Government Administration and the number of employees: 46616 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 636 and after the incident was 574 with a difference of -62 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 Social Security Administration and their customers.

U.S. Social Security Administration (SSA) recently reported "Former DOGE Engineer Accused of Stealing Sensitive U.S. Citizen Data from Social Security Administration", a noteworthy cybersecurity incident.

A whistleblower complaint alleges that a former software engineer from Elon Musk’s Department of Government Efficiency (DOGE) stole highly sensitive personal data from the U.S.

The disruption is felt across the environment, affecting U.S. Social Security Administration (SSA) databases (Numident, Master Death File), and exposing Highly sensitive personal data (SSNs, birth details, citizenship status, race, ethnicity, parental information), with nearly 500+ million records at risk.

In response, and stakeholders are being briefed through SSA spokesperson denied allegations, calling the report 'fake news'.

The case underscores how Ongoing (SSA Inspector General investigating).

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 Initial Access tactic, the analysis identified Valid Accounts (T1078) with high confidence (90%), supported by evidence indicating former DOGE Engineer had God-level access to SSA systems. Under the Credential Access tactic, the analysis identified Unsecured Credentials: Credentials In Files (T1552.001) with moderate to high confidence (70%), supported by evidence indicating excessive privileges (God-level access) enabled unauthorized data extraction. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating numident and Master Death File databases accessed (500M+ records) and Data from Information Repositories (T1213) with high confidence (90%), supported by evidence indicating restricted SSA databases (Numident, Master Death File) targeted. Under the Exfiltration tactic, the analysis identified Exfiltration Over Physical Medium: Exfiltration over USB (T1052.001) with high confidence (90%), supported by evidence indicating data allegedly stored on a thumb drive and Exfiltration Over C2 Channel (T1041) with moderate confidence (50%), supported by evidence indicating potential cloud upload (prior DOGE-SSA incidents). Under the Defense Evasion tactic, the analysis identified Valid Accounts (T1078) with moderate to high confidence (80%), supported by evidence indicating god-level access used to bypass normal access controls and Hide Artifacts: Hidden Files and Directories (T1564.001) with moderate confidence (60%), supported by evidence indicating data stored on thumb drive (physical evasion). Under the Impact tactic, the analysis identified Data Manipulation: Stored Data Manipulation (T1565.001) with lower confidence (40%), supported by evidence indicating potential unauthorized access to 500M+ records. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.