Automating Security Detection Engineering
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Automating Security Detection Engineering

A hands-on guide to implementing Detection as Code

About the Book

Today's global enterprise security programs grapple with constantly evolving threats. Even though the industry has released abundant security tools, most of which are equipped with APIs for integrations, they lack a rapid detection development work stream. This book arms you with the skills you need to automate the development, testing, and monitoring of detection-based use cases.

You’ll start with the technical architecture, exploring where automation is conducive throughout the detection use case lifecycle. With the help of hands-on labs, you’ll learn how to utilize threat-informed defense artifacts and then progress to creating advanced AI-powered CI/CD pipelines to bolster your Detection as Code practices. Along the way, you'll develop custom code for EDRs, WAFs, SIEMs, CSPMs, RASPs, and NIDS. The book will also guide you in developing KPIs for program monitoring and cover collaboration mechanisms to operate the team with DevSecOps principles. Finally, you'll be able to customize a Detection as Code program that fits your organization's needs.

By the end of the book, you'll have gained the expertise to automate nearly the entire use case development lifecycle for any enterprise.

About the Author

Packt Publishing Ltd
Packt Publishing Ltd

Packt Publishing are an established global technical learning content provider, founded in Birmingham, UK with over twenty years’ experience in delivering premium rich content from ground-breaking authors on a wide range of emerging and popular technologies. Our titles have global relevance our multimedia portfolio includes over 9,000 books, e-books, audiobooks and video courses. www.packtpub.com

Table of Contents

  1. Detection as Code Architecture and Lifecycle
  2. Scoping and Automating Threat-Informed Defense Inputs
  3. Developing Core CI/CD Pipeline Functions
  4. Leveraging AI for Use Case Development
  5. Implementing Logical Unit Tests
  6. Creating Integration Tests
  7. Leveraging AI for Testing
  8. Monitoring Detection Health
  9. Measuring Program Efficiency
  10. Operating Patterns by Maturity

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