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Automating Security Detection Engineering

You're reading from   Automating Security Detection Engineering A hands-on guide to implementing Detection as Code

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Product type Paperback
Published in Jun 2024
Publisher Packt
ISBN-13 9781837636419
Length 252 pages
Edition 1st Edition
Languages
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Author (1):
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Dennis Chow Dennis Chow
Author Profile Icon Dennis Chow
Dennis Chow
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Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1: Automating Detection Inputs and Deployments
2. Chapter 1: Detection as Code Architecture and Lifecycle FREE CHAPTER 3. Chapter 2: Scoping and Automating Threat-Informed Defense Inputs 4. Chapter 3: Developing Core CI/CD Pipeline Functions 5. Chapter 4: Leveraging AI for Use Case Development 6. Part 2: Automating Validations within CI/CD Pipelines
7. Chapter 5: Implementing Logical Unit Tests 8. Chapter 6: Creating Integration Tests 9. Chapter 7: Leveraging AI for Testing 10. Part 3: Monitoring Program Effectiveness
11. Chapter 8: Monitoring Detection Health 12. Chapter 9: Measuring Program Efficiency 13. Chapter 10: Operating Patterns by Maturity 14. Index 15. Other Books You May Enjoy

Setting up CI/CD runners

Creating the repository allows us to store our code and detections. We will now set up the logic and scripts that will implement our use cases. In traditional code development there might be an all-in-one build-and-deploy pipeline, or a separate pipeline for each. In detection engineering, we are primarily focused on scalable deployments. Let’s start with understanding how to integrate our CI with our target security tooling.

We’ll begin selecting existing SDKs in a supported scripting language in both the target deployment tool and the CI pipeline. Most modern CI solutions support a variety of popular languages. Security tooling API client wrapper support may vary, but it’s common to see Python, PowerShell, and GoLang. In the upcoming labs, we’ll build what is necessary for the CI runner in stages as we work towards an operational deployment pipeline. Let’s begin to apply this concept in Lab 3.2.

Detection engineering...

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