Individual skill
implementing-velociraptor-for-ir-collection
Deploy and configure Velociraptor for scalable endpoint forensic artifact collection during incident response using VQL queries, hunts, and pre-built artifact packs across Windows, Linux, and macOS environments.
internal/tools/skills/data/incident-response/implementing-velociraptor-for-ir-collection/SKILL.md
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- cybersecurity Repository topic
- security Repository topic
- bug-bounty Repository topic
- automation Repository topic
- autonomous-pentesting Repository topic
- ai-agent Repository topic
- ai-security Repository topic
- ethical-hacking Repository topic
- golang Repository topic
- penetration-testing Repository topic
- velociraptor Declared skill tag
- dfir Declared skill tag
- endpoint-collection Declared skill tag
- vql Declared skill tag
- forensic-artifacts Declared skill tag
- rapid7 Declared skill tag
- threat-hunting Declared skill tag
- incident-response Declared skill tag
- security Derived category
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# 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.
## When to Use
- When deploying or configuring implementing velociraptor for ir collection capabilities in your environment
- When establishing security controls aligned to compliance requirements
- When building or improving security architecture for this domain
- When conducting security assessments that require this implementation
