Executive Summary

Baker University, a private university in Kansas, has disclosed a major data breach that occurred a year ago, impacting 53,624 individuals. According to the notification, unauthorized actors had access to the university's network for a 17-day period in December 2024. The attackers accessed and potentially exfiltrated a vast amount of highly sensitive personal, financial, and health information. Compromised data includes Social Security numbers, financial account details, passport numbers, and medical information. The university's one-year delay in notifying victims raises significant concerns about its incident response process. All affected individuals are being offered complimentary credit monitoring services.

Threat Overview

The security incident took place between December 2, 2024, and December 19, 2024, during which time an unauthorized party had persistent access to Baker University's network. The breach was first detected in December 2024 after a network outage prompted an investigation with external cybersecurity experts. However, the full scope and the notification to victims were not finalized until a year later.

The breach exposed a wide array of sensitive data, creating a high risk of identity theft and fraud for the victims. The compromised information includes:

• Names and dates of birth
• Social Security numbers (SSNs)
• Student and tax identification numbers
• Financial account information
• Health insurance and medical information
• Passport numbers

While the university states it has no evidence of the data being misused, the long exposure time and the value of the stolen information make misuse highly probable. The identity of the attackers and the specific vector of compromise have not been disclosed.

Technical Analysis

The long dwell time (17 days) suggests the threat actors were skilled at remaining undetected after their initial intrusion. This often involves using legitimate credentials and tools to blend in with normal network activity.

MITRE ATT&CK Techniques (Inferred)

• T1078 - Valid Accounts: Attackers likely used compromised credentials to gain initial access and move laterally within the network.
• T1003 - OS Credential Dumping: To escalate privileges and gain wider access, attackers would have targeted stored credentials on compromised systems.
• T1046 - Network Service Discovery: Once inside, the attackers would have scanned the network to identify servers containing valuable data, such as student information systems and financial databases.
• T1021 - Remote Services: Lateral movement was likely achieved by using remote services like RDP or SMB to access other systems on the network.
• T1567.002 - Exfiltration Over Web Service: The attackers would have staged and exfiltrated the stolen data, possibly over encrypted web channels to avoid detection.

Impact Assessment

The impact of this breach is critical for the 53,624 affected individuals. The combination of SSNs, financial data, and health information is a 'full package' for identity thieves, enabling them to open new lines of credit, file fraudulent tax returns, and commit medical fraud. The university faces severe reputational damage, particularly due to the one-year delay in notification, which may violate breach notification laws in various jurisdictions and could lead to regulatory fines and class-action lawsuits. The incident highlights a potential failure in the university's incident response and communication strategy.

Cyber Observables for Detection

To detect similar intrusions, organizations should monitor for:

Detection & Response

1. Endpoint Detection and Response (EDR): An EDR solution is essential for detecting the techniques used in such an attack, including credential dumping and lateral movement. It provides the visibility needed to spot malicious behavior that legacy antivirus would miss.
2. Log Aggregation and SIEM: Centralize logs from all critical systems (domain controllers, file servers, firewalls) into a SIEM. Create correlation rules to detect patterns of attack, such as a user logging in from multiple locations simultaneously or accessing an unusual number of sensitive files.
3. Incident Response Plan: The one-year notification delay indicates a potential gap in the IR plan. A well-defined plan must include clear timelines for investigation, containment, and communication, in compliance with all relevant regulations.
4. D3FEND Techniques: Utilize D3-PA - Process Analysis to detect suspicious command-line activity and D3-UBA - User Behavior Analysis to identify compromised accounts exhibiting anomalous behavior.

Mitigation

1. Multi-Factor Authentication (MFA): Enforce MFA across all services, especially for remote access and access to sensitive systems. This is one of the most effective controls against credential-based attacks.
2. Network Segmentation: Segment the network to prevent attackers from moving freely after an initial compromise. Isolate critical systems (like student databases) from the general user network.
3. Privileged Access Management (PAM): Implement PAM solutions to tightly control and monitor the use of administrative accounts. This helps prevent privilege escalation.
4. Data Backup and Recovery: While this was a data theft incident, having robust, offline backups is critical for recovering from a destructive attack that might accompany data exfiltration.
5. D3FEND Countermeasures: Implement D3-NI - Network Isolation to limit an attacker's lateral movement capabilities. Enforce a D3-SPP - Strong Password Policy and MFA to make initial access more difficult.