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Analyze » Edelman Financial Engines » EDE1770317444

Incident Score: Analysis & Impact (EDE1770317444)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-84
Company Score Before Incident738 / 1000
Company Score After Incident654 / 1000
INCIDENT NUMBEREDE1770317444
Type of Cyber IncidentBreach
ATTACK VECTORNA
DATA EXPOSEDPersonally identifiable information (names, dates...
INCIDENT DATE06/01/2026
STATUSOngoing

Key Highlights From The Incident Analysis

  • Timeline of Edelman Financial Engines'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 Edelman Financial Engines 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 Edelman Financial Engines breach identified under incident ID EDE1770317444.

The analysis begins with a detailed overview of Edelman Financial Engines's information like the linkedin page: https://www.linkedin.com/company/edelman-financial-engines, the number of followers: 37712, the industry type: Financial Services and the number of employees: 1494 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 738 and after the incident was 654 with a difference of -84 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 Edelman Financial Engines and their customers.

On 07 January 2026, Edelman Financial Engines disclosed Data Breach issues under the banner "Edelman Financial Engines Data Breach Exposes Sensitive Client Information".

Edelman Financial Engines disclosed a data breach after detecting unauthorized access to client information.

The disruption is felt across the environment, and exposing Personally identifiable information (names, dates of birth, addresses, phone numbers, emails, financial planning details, Social Security numbers), with nearly 5083 records at risk.

In response, teams activated the incident response plan, moved swiftly to contain the threat with measures like Terminated unauthorized access, and stakeholders are being briefed through Notified affected clients in writing on January 28, 2026; filed disclosures with attorneys general of California and Maine.

The case underscores how Ongoing, with advisories going out to stakeholders covering Affected clients notified in writing on January 28, 2026; offered 24 months of complimentary credit and identity monitoring services through Kroll.

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 moderate to high confidence (80%), supported by evidence indicating detecting unauthorized access to client information and Exploit Public-Facing Application (T1190) with moderate confidence (50%), supported by evidence indicating breach exposed personally identifiable data via unauthorized access. Under the Credential Access tactic, the analysis identified Unsecured Credentials (T1552) with moderate to high confidence (70%), supported by evidence indicating unauthorized access to client information (PII, SSNs, financial details) and OS Credential Dumping (T1003) with moderate confidence (60%), supported by evidence indicating social Security numbers and financial planning details compromised. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating names, dates of birth, addresses, phone numbers, emails, SSNs exposed and Data from Information Repositories (T1213) with moderate to high confidence (80%), supported by evidence indicating financial planning details and client records compromised. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (70%), supported by evidence indicating 5,083 individuals data exposed; unauthorized access terminated and Transfer Data to Cloud Account (T1537) with moderate confidence (50%), supported by evidence indicating high sensitivity data (SSNs, financial details) compromised. Under the Impact tactic, the analysis identified Data Destruction (T1485) with lower confidence (30%), supported by evidence indicating no details on extent of breach or data integrity post-incident and Data Manipulation: Stored Data Manipulation (T1565.001) with lower confidence (40%), supported by evidence indicating financial planning details and PII compromised; potential fraud risk. 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 (80%)
Exploit Public-Facing Application (50%)
Credential Access
Unsecured Credentials (70%)
OS Credential Dumping (60%)
Collection
Data from Local System (90%)
Data from Information Repositories (80%)
Exfiltration
Exfiltration Over C2 Channel (70%)
Transfer Data to Cloud Account (50%)
Impact
Data Destruction (30%)
Data Manipulation: Stored Data Manipulation (40%)

Sources & References