Which Two Data Sources Support the Use of UEBA?

The two primary data sources that fundamentally support the use of User and Entity Behavior Analytics (UEBA) are event logs and network traffic. These sources provide crucial insights into user activities, system interactions, and network communications, enabling UEBA solutions to establish baselines of normal behavior and detect anomalies indicative of threats.

Understanding UEBA's Data Foundation

User and Entity Behavior Analytics (UEBA) is a cybersecurity solution that leverages machine learning and analytical models to detect anomalous behavior by users and other entities within an organization's IT environment. Its effectiveness hinges on its ability to collect and process vast amounts of diverse data, identifying deviations from established patterns that could signal insider threats, compromised accounts, or sophisticated cyberattacks.

Key Data Sources for UEBA

UEBA solutions require rich, continuous streams of data to build comprehensive behavioral profiles. While many sources contribute, event logs and network traffic stand out for their direct relevance to user and entity activities.

1. Event Logs

Event logs are a cornerstone for UEBA, capturing a historical record of actions and occurrences across various systems. These logs provide granular details about what happened, when it happened, and who or what initiated the action.

• Types of Event Logs:
  • Operating System Logs: Windows Event Logs, Linux syslog, detailing logins, process executions, system errors, and security events.
  • Application Logs: Records of user interactions within specific applications, database queries, and web server access logs.
  • Security Device Logs: Firewall logs, intrusion detection/prevention system (IDS/IPS) logs, and antivirus software logs that track security alerts and blockages.
• Insights for UEBA:
  • Unusual login patterns (e.g., logins from new geographical locations, outside working hours, excessive failed attempts).
  • Access to sensitive files or systems by unauthorized users or at atypical times.
  • Privilege escalation attempts or changes in user permissions.
  • Execution of suspicious commands or software installations.

2. Network Traffic

Network traffic data provides a unique perspective on the flow of information within and outside an organization's perimeter. It offers insights into communication patterns, data transfers, and potential command-and-control (C2) activities.

• Types of Network Data:
  • Flow Data (e.g., NetFlow, IPFIX): Summarized records of network conversations, including source/destination IP addresses, ports, protocols, and data volume.
  • Packet Captures: Detailed records of individual network packets, providing deep insights into the content and context of communications (though often used for forensics rather than continuous UEBA feeding due to volume).
  • DNS Queries: Records of domain name system requests, which can reveal communication with malicious domains.
  • Proxy Logs: Records of web browsing activity, indicating access to suspicious websites or unusual download patterns.
• Insights for UEBA:
  • Unusual outbound data transfers (e.g., data exfiltration).
  • Communication with known malicious IP addresses or domains.
  • Abnormal network scanning or reconnaissance activities.
  • Lateral movement within the network by an attacker.
  • Use of non-standard ports or protocols for communication.

Complementary Data Sources and Integration

While event logs and network traffic are fundamental, UEBA solutions enhance their accuracy by ingesting data from an even wider array of sources. The effectiveness of a UEBA solution is significantly boosted by its capability to collect data from diverse sources like endpoint devices and general repositories such as data warehouses or data lakes. These solutions often achieve this by fully integrating within a SIEM (Security Information and Event Management) solution, which acts as a centralized data aggregator, or by directly ingesting data from these large-scale repositories.

• Endpoint Devices: Data from individual workstations, servers, and mobile devices can provide context on processes running, file access, and application usage at the user's direct interaction point.
• Data Warehouses / Data Lakes: These large-scale repositories can store vast amounts of historical and real-time data, including HR data (employee roles, department changes), identity management data (user provisioning, access rights), and business application data, all of which enrich behavioral profiles.

Why Diverse Data Matters for UEBA

The power of UEBA lies in its ability to correlate disparate data points from various sources to form a holistic view of user and entity behavior. By combining insights from event logs, network traffic, and other sources, UEBA can:

• Establish Accurate Baselines: Build a more comprehensive understanding of "normal" behavior by cross-referencing activities across different systems.
• Enhance Anomaly Detection: Identify subtle deviations that might go unnoticed in individual data streams but become evident when correlated across multiple sources.
• Reduce False Positives: Validate suspicious activity by finding corroborating evidence from different data types, thereby minimizing alert fatigue.
• Improve Threat Context: Provide a richer context around detected anomalies, helping security teams understand the scope and potential impact of a threat more quickly.

The integration of these diverse data sources allows UEBA to provide continuous, adaptive security monitoring, making it a critical component in advanced threat detection strategies.