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Practical Threat Detection Engineering

Practical Threat Detection Engineering

By : Megan Roddie, Jason Deyalsingh, Gary J. Katz
4.7 (21)
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Practical Threat Detection Engineering

Practical Threat Detection Engineering

4.7 (21)
By: Megan Roddie, Jason Deyalsingh, Gary J. Katz

Overview of this book

Threat validation is an indispensable component of every security detection program, ensuring a healthy detection pipeline. This comprehensive detection engineering guide will serve as an introduction for those who are new to detection validation, providing valuable guidelines to swiftly bring you up to speed. The book will show you how to apply the supplied frameworks to assess, test, and validate your detection program. It covers the entire life cycle of a detection, from creation to validation, with the help of real-world examples. Featuring hands-on tutorials and projects, this guide will enable you to confidently validate the detections in your security program. This book serves as your guide to building a career in detection engineering, highlighting the essential skills and knowledge vital for detection engineers in today's landscape. By the end of this book, you’ll have developed the skills necessary to test your security detection program and strengthen your organization’s security measures.
Table of Contents (20 chapters)
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1
Part 1: Introduction to Detection Engineering
5
Part 2: Detection Creation
11
Part 3: Detection Validation
14
Part 4: Metrics and Management
16
Part 5: Detection Engineering as a Career

The Elastic Stack

The Elastic Stack is a set of tightly integrated products that are well suited to address the requirements of a DE lab. The Elastic Stack includes the following components:

  • Beats: A data shipper that is used to collect data from an endpoint and forward it to Elasticsearch or Logstash for pre-processing. Different packages exist for collecting different types of data from endpoints. While Beats is a core component of the Elastic Stack, in this book, we will use Elastic Agent to forward data from endpoints to Elasticsearch.
  • Logstash: A powerful tool for transforming data and forwarding it to different destination systems. It offers a high degree of control over re-shaping data and has plugins that support forwarding data to a significant variety of destinations.
  • Elasticsearch: This is the data storage component. While primarily designed for searching, it has evolved to become a capable data analysis engine.
  • Kibana: This is the Elasticsearch frontend...

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