Case Study: RedOwl detects insider threats and accelerates investigations with Elastic

Detecting Insider Threat with Elastic

RedOwl, a security analytics company, needed to detect insider threats—ranging from disgruntled employees to blackmailed developers—across massive, unstructured event streams. Their original Hadoop-based analytics were resource‑intensive, hard to configure and interpret, and couldn’t provide the flexible, timely visibility required to surface risky human behaviors at scale.

They re‑architected around Elastic as part of a stack with NiFi, RabbitMQ, Redis, PostgreSQL and Node.js, scoring features at ingest and using runtime models and aggregations to define and surface risk by entity. The new approach is lighter, faster and more configurable, enabled rich dashboards and exploration, and in a global private‑equity customer uncovered negligent information sharing and deliberate data theft while delivering higher‑fidelity reporting and faster, more comprehensive investigations.

RedOwl

Russell Snyder

Principal Engineer