SIEM: Aggregates log data generated by applications, endpoints and network devices. Support for big data and real-time event analysis. Supports machine learning and behavioral analytics plugins to create baselines of normal user and device behavior. Rely heavily on siloed security products, which can lead to alerts based on incomplete or poorly correlated information. Limited incident response and visualization. Collects event data but requires manual effort. Sheer volume of alerts overloaded security teams. Demands tools to enhance the quality of alerts and automate responses.
SOAR: Aims to enrich event data, simplify the identification of critical incidents and automate response actions to specific events or triggers. Main goal is to speed up remediation and only escalate threats when human intervention was required. Rely heavily on siloed security products, which can lead to alerts based on incomplete or poorly correlated information. Maintaining visibility across an entire network remains a problem as modern IT infrastructures continue to sprawl. Ingest data from multiple sources, which requires integration with other security tools, and still demands custom alert levels and response measures.
XDR: Centralizes and normalizes data from all connected sources, including users, the network, and wherever data and applications reside. Main goal is to correlate all security data and alerts and provide a centralized incident detection and response. Integrates a range of investigative tools, behavioral analytics and automated remediation capabilities into a single platform. Strong focus on advanced threat detection and tailored responses, has comprehensive monitoring across the entire attack surface. Does not have the log management, retention and compliance capabilities of SIEM, so needs to be able to integrate with existing security controls.