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Analyze » EPIC SYSTEMS INC » OUTEPIMICUMA1777660615

Incident Score: Analysis & Impact (OUTEPIMICUMA1777660615)

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

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-93
Company Score Before Incident749 / 1000
Company Score After Incident656 / 1000
INCIDENT NUMBEROUTEPIMICUMA1777660615
Type of Cyber IncidentBreach
ATTACK VECTORFraudulent third-party access via health information exchange
DATA EXPOSED300,000 medical records
INCIDENT DATE17/10/2023
STATUSOngoing

Key Highlights From The Incident Analysis

  • Timeline of EPIC SYSTEMS INC'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 EPIC SYSTEMS INC 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 EPIC SYSTEMS INC breach identified under incident ID OUTEPIMICUMA1777660615.

The analysis begins with a detailed overview of EPIC SYSTEMS INC's information like the linkedin page: https://www.linkedin.com/company/epicsystemsinc, the number of followers: 9494, the industry type: IT Services and IT Consulting and the number of employees: 23 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 749 and after the incident was 656 with a difference of -93 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 EPIC SYSTEMS INC and their customers.

On 13 January 2026, Michigan Medicine disclosed Data Breach issues under the banner "Massive Medical Records Breach Exposes 300,000 Patients, Including Michigan Medicine Patients".

A sophisticated cyber scheme has compromised nearly 300,000 medical records, including those of 551 Michigan Medicine patients, after a network of fraudulent entities posed as legitimate healthcare providers to access sensitive data.

The disruption is felt across the environment, affecting Michigan Medicine’s electronic health records (Epic Systems) and Health Gorilla’s health information network, and exposing 300,000 medical records, with nearly 300,000 records at risk.

In response, teams activated the incident response plan, moved swiftly to contain the threat with measures like Suspension of connections with implicated entities (Health Gorilla), and began remediation that includes Patient notifications, monitoring of lawsuit, regulatory reporting, and stakeholders are being briefed through Patient advisories, public statements, regulatory notifications.

The case underscores how Ongoing, teams are taking away lessons such as Vulnerabilities in health information exchanges can be exploited by fraudulent entities using fake credentials and shell companies. Need for stricter verification of third-party access to sensitive data, and recommending next steps like Enhance verification processes for third-party access to health information exchanges, Implement stricter monitoring of data access patterns and Improve detection of fraudulent entities posing as legitimate providers, with advisories going out to stakeholders covering Healthcare providers advised to review third-party access and monitor for suspicious activity.

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 Phishing: Spearphishing Link (T1566.002) with moderate confidence (60%), supported by evidence indicating fraudulent entities posed as legitimate healthcare providers, Valid Accounts: Cloud Accounts (T1078.004) with moderate to high confidence (80%), supported by evidence indicating exploiting a health information exchange via third-party companies, and Compromise Accounts (T1586) with moderate to high confidence (70%), supported by evidence indicating fake National Provider Identification (NPI) numbers to deceive systems. Under the Credential Access tactic, the analysis identified Gather Victim Identity Information: Credentials (T1589.001) with moderate to high confidence (70%), supported by evidence indicating fraudulent NPI numbers and shell companies used to access records and Forge Web Credentials: SAML Tokens (T1606.002) with moderate confidence (60%), supported by evidence indicating fake websites and shell companies to deceive healthcare systems. Under the Discovery tactic, the analysis identified Account Discovery: Local Account (T1087.001) with moderate to high confidence (70%), supported by evidence indicating unusual activity detected from third-party companies and Account Discovery: Cloud Account (T1087.004) with moderate to high confidence (80%), supported by evidence indicating exploitation of health information exchange systems. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating demographic details, clinical info, health insurance records compromised and Data from Information Repositories: Sharepoint (T1213.002) with moderate to high confidence (70%), supported by evidence indicating access to Michigan Medicine’s electronic health records. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), supported by evidence indicating 300,000 medical records compromised, potential sale to lawyers and Transfer Data to Cloud Account (T1537) with moderate confidence (60%), supported by evidence indicating monetized patient data without consent via Health Gorilla’s network. Under the Defense Evasion tactic, the analysis identified Hide Artifacts: Hidden Files and Directories (T1564.001) with moderate to high confidence (70%), supported by evidence indicating inserted false entries into medical records to mask activities and Masquerading: Task Masquerading (T1036.004) with moderate to high confidence (80%), supported by evidence indicating fraudulent entities posed as legitimate healthcare providers. Under the Impact tactic, the analysis identified Data Destruction (T1485) with moderate confidence (50%), supported by evidence indicating false entries inserted into medical records and Data Manipulation: Stored Data Manipulation (T1565.001) with moderate to high confidence (70%), supported by evidence indicating inserted false entries into medical records to mask activities. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Phishing: Spearphishing Link (60%)
Valid Accounts: Cloud Accounts (80%)
Compromise Accounts (70%)
Credential Access
Gather Victim Identity Information: Credentials (70%)
Forge Web Credentials: SAML Tokens (60%)
Discovery
Account Discovery: Local Account (70%)
Account Discovery: Cloud Account (80%)
Collection
Data from Local System (90%)
Data from Information Repositories: Sharepoint (70%)
Exfiltration
Exfiltration Over C2 Channel (80%)
Transfer Data to Cloud Account (60%)
Defense Evasion
Hide Artifacts: Hidden Files and Directories (70%)
Masquerading: Task Masquerading (80%)
Impact
Data Destruction (50%)
Data Manipulation: Stored Data Manipulation (70%)