An endpoint visibility and collection tool using the Velociraptor Query Language (VQL) for host-based state information gathering.
Velociraptor is an endpoint visibility and collection tool designed for gathering host-based state information using the Velociraptor Query Language (VQL). It solves the problem of obtaining detailed forensic data from endpoints during security incidents, investigations, or continuous monitoring. The tool allows security teams to collect artifacts, run queries, and analyze system activities across multiple platforms.
Security professionals, incident responders, digital forensic investigators, and IT teams responsible for endpoint monitoring and threat hunting.
Developers choose Velociraptor for its powerful VQL language that provides fine-grained control over data collection, its extensible artifact system, and the ability to deploy it as a self-hosted solution for complete control over sensitive forensic data.
Digging Deeper....
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Built with Golang, it runs on Windows, Linux, and macOS, as highlighted in the README under 'Multi-Platform Support', ensuring broad endpoint coverage.
VQL allows fine-grained control over data collection, enabling custom forensic investigations, which is emphasized in the project's philosophy and artifact system.
Comes with built-in artifacts and a community-maintained exchange, as noted in the 'Artifact Exchange' section, providing ready-to-use collections for various scenarios.
Can be used as a standalone collector on a single machine, described in 'Running Velociraptor locally', making it useful for immediate forensic analysis without full deployment.
VQL is a custom language requiring significant training; the README mentions a 7-session training course, indicating complexity for new users.
Building from source requires multiple dependencies like Golang, gcc, make, and Node.js, as detailed in 'Building from source', which can be cumbersome.
As a self-hosted tool, it demands infrastructure management for large deployments, unlike cloud-based alternatives, though this is implied rather than explicitly stated.