Implementing Velociraptor for IR Collection

Overview

Velociraptor is an advanced open-source endpoint monitoring, digital forensics, and incident response platform developed by Rapid7. It uses the Velociraptor Query Language (VQL) to create custom artifacts that collect, query, and monitor almost any aspect of an endpoint. Velociraptor enables incident response teams to rapidly collect and examine forensic artifacts from across a network, supporting large-scale deployments with minimal performance impact. The client-server architecture with Fleetspeak communication enables real-time data collection from thousands of endpoints simultaneously, with offline endpoints picking up hunts when they reconnect.

Architecture

Components

• Velociraptor Server: Central management console with web UI and API
• Velociraptor Client (Agent): Lightweight agent deployed to endpoints
• Fleetspeak: Communication framework between client and server
• VQL Engine: Query language engine for artifact collection
• Filestore: Server-side storage for collected artifacts
• Datastore: Metadata storage for hunts, flows, and client information