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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

Summary

In this chapter, we looked at how a detection pipeline can be used to automate and enforce your detection team’s processes. We examined the steps of a standard detection engineering pipeline and looked at some more complex examples to see how a pipeline can be modified based on individual use cases.

The Publishing a rule using Elastic’s detection-rules project lab was used to demonstrate how a team can build and leverage a set of capabilities to add structure and process to the creation of their detections. In this example, we performed the steps of our pipeline manually. These steps can be automated using a tool such as Jenkins, or a source repository site such as GitHub or GitLab can manage the pipeline as well.

The detection_rules package was built to support Elastic’s internal detection team. While this package can be used and modified to support your own team’s processes, you should choose the processes that align with your individual...

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