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Analyze » Social security Institution » SOC1770609457

Incident Score: Analysis & Impact (SOC1770609457)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-31
Company Score Before Incident816 / 1000
Company Score After Incident785 / 1000
Company LinkView Social security Institution Profile
INCIDENT NUMBERSOC1770609457
Type of Cyber IncidentBreach
ATTACK VECTORUnsecured Cloud Environment
DATA EXPOSEDNames, SSNs, Addresses
INCIDENT DATE04/02/2026
STATUSOngoing

Key Highlights From The Incident Analysis

  • Timeline of Social security Institution'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 Social security Institution 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 Social security Institution breach identified under incident ID SOC1770609457.

The analysis begins with a detailed overview of Social security Institution's information like the linkedin page: https://www.linkedin.com/company/social-security-institution, the number of followers: 0, the industry type: Insurance and the number of employees: 4661 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 816 and after the incident was 785 with a difference of -31 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 Institution and their customers.

Social Security Administration (SSA) recently reported "Potential Massive Social Security Data Breach", a noteworthy cybersecurity incident.

A whistleblower has raised alarms over a potential national security disaster involving the exposure of sensitive Social Security data for every American with or who ever had a Social Security number (SSN).

The disruption is felt across the environment, affecting SSA Database, and exposing Names, SSNs, Addresses, with nearly Potentially all Americans with an SSN records at risk.

Formal response steps have not been shared publicly yet.

The case underscores how Ongoing.

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 Valid Accounts (T1078) with high confidence (90%), supported by evidence indicating employees of the Department of Government Efficiency (DOGE) uploaded a copy and Phishing: Spearphishing Link (T1566.002) with lower confidence (30%), supported by evidence indicating no direct evidence, but possible vector for insider threat enablement. Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with high confidence (95%), supported by evidence indicating uploaded a copy of the SSA’s database to an unsecured cloud environment and Exfiltration Over C2 Channel (T1041) with moderate confidence (50%), supported by evidence indicating potential exfiltration if cloud environment was compromised post-upload. Under the Credential Access tactic, the analysis identified Unsecured Credentials: Cloud Instance Metadata API (T1552.005) with moderate to high confidence (70%), supported by evidence indicating unsecured cloud environment may have exposed credentials or keys. Under the Collection tactic, the analysis identified Data from Cloud Storage Object (T1213.003) with high confidence (90%), supported by evidence indicating sSA’s database...uploaded to an unsecured cloud environment and Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating copy of the SSA’s database...personal data, including names, SSNs, addresses. Under the Defense Evasion tactic, the analysis identified Hide Artifacts: Email Hiding Rules (T1564.008) with lower confidence (40%), supported by evidence indicating no public confirmation of breach; potential concealment of incident and Valid Accounts: Cloud Accounts (T1078.004) with moderate to high confidence (80%), supported by evidence indicating dOGE employees used legitimate access to upload database. Under the Impact tactic, the analysis identified Data Destruction (T1485) with lower confidence (30%), supported by evidence indicating potential long-term consequences for millions of Americans and Data Manipulation: Stored Data Manipulation (T1565.001) with lower confidence (40%), supported by evidence indicating vulnerable to fraud and exploitation; no confirmation of integrity checks. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Valid Accounts (90%)
Phishing: Spearphishing Link (30%)
Exfiltration
Transfer Data to Cloud Account (95%)
Exfiltration Over C2 Channel (50%)
Credential Access
Unsecured Credentials: Cloud Instance Metadata API (70%)
Collection
Data from Cloud Storage Object (90%)
Data from Local System (80%)
Defense Evasion
Hide Artifacts: Email Hiding Rules (40%)
Valid Accounts: Cloud Accounts (80%)
Impact
Data Destruction (30%)
Data Manipulation: Stored Data Manipulation (40%)

Sources & References