EQL Analytics Library
A library of event-based analytics written in EQL to detect adversary behaviors identified in MITRE ATT&CK, providing detection rules for the Elastic Stack.
EQL Analytics Library
A library of event-based analytics written in EQL to detect adversary behaviors identified in MITRE ATT&CK, providing detection rules for the Elastic Stack.
EQL Analytics Library Description
The EQL Analytics Library (eqllib) is a collection of event-based analytics written in Event Query Language (EQL) designed to detect adversary behaviors identified in the MITRE ATT&CK framework. The library provides detection rules in multiple query languages including EQL, KQL (Kibana Query Language), and Lucene, making it compatible with the Elastic Stack ecosystem. These analytics are specifically crafted to identify tactics, techniques, and procedures (TTPs) used by threat actors as documented in the MITRE ATT&CK knowledge base. The library has been integrated into the Detection Engine of Kibana, allowing security teams to leverage pre-built detection rules for threat hunting and security monitoring activities. The rules focus on event-based detection, analyzing security events and logs to identify suspicious patterns and behaviors that may indicate adversary activity within an environment.
EQL Analytics Library FAQ
Common questions about EQL Analytics Library including features, pricing, alternatives, and user reviews.
EQL Analytics Library is A library of event-based analytics written in EQL to detect adversary behaviors identified in MITRE ATT&CK, providing detection rules for the Elastic Stack. It is a Security Operations solution designed to help security teams with MITRE Attack, Detection Rules.
