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Version: VAST v3.0


Welcome to the VAST! If you have any questions, do not hesitate to join our community chat or open a GitHub discussion.

What is VAST?

VAST is the open-source pipeline and storage engine for security event data.

VAST offers dataflow pipelines for data acquisition, reshaping, routing, and integration of security tools. Pipelines transport richly typed data frames to enable efficient analytical high-bandwidth streaming workloads. VAST's open storage engine uses the same dataflow language to deliver a unified abstraction for batch and stream processing to drive a wide variety of security use cases.

A VAST node provides managed pipelines and storage as a continuously running service. You can run pipelines across multiple nodes to create a distributed security data architecture.

Consider VAST if you want to:

  • Filter, shape, aggregate, and enrich security events before they hit your SIEM or data lake
  • Normalize, enrich, and deduplicate events prior to passing them downstream
  • Store, compact, and search event data in an open storage format (Apache Parquet & Feather)
  • Perform high-bandwidth analytics with any data tool powered by Apache Arrow
  • Operationalize threat intelligence for live and retrospective detection
  • Build your own security data lake or federated XDR architecture

If you're unsure whether VAST is the right tool for your use case, keep reading.

What's Next?

The structure of the documentation follows the user journey:

  1. Try: tells you how to quickly get your hands on VAST to give it a shot. 👉 Begin here if you want to test-drive VAST.
  2. Setup: describes how you can download, install, and configure VAST in a variety of environments. 👉 Start here if you want to deploy VAST.
  3. Use: explains how to work with VAST, e.g., ingesting data, running queries, matching threat intelligence, or integrating it with other security tools. 👉 Go here if you have a running VAST, and want to explore what you can do with it.
  4. Understand: describes the system design and architecture, e.g., the pipeline language, the data model, and the implementation in terms actor model for concurrency and distribution. 👉 Read here if you want to know why VAST is built the way it is.
  5. Contribute: lays out our contribution guidelines and explains how to contribute to the code base, either in terms of documentation or source code. 👉 Read this if you want to become a contributor.
  6. Develop: provides developer-oriented resources to work on VAST, e.g., write own plugins or enhance the source code. 👉 Look here if you are ready to get your hands dirty and write code.