Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Automating Security Detection Engineering

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

Arrow left icon
Product type Paperback
Published in Jun 2024
Publisher Packt
ISBN-13 9781837636419
Length 252 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Dennis Chow Dennis Chow
Author Profile Icon Dennis Chow
Dennis Chow
Arrow right icon
View More author details
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

Evaluating data security and ROI

An important topic of any development lifecycle is what threats and data security controls should be considered before using AI. We have been sending things to different systems, including the Poe.com platform, which then traverses our detections and log samples to other third-party systems. Like any other system we build, it should start with a design and go through an architectural review.

CI/CD pipelines and deploying detections to security tools are typically not going to catch the attention of your security architects. However, sending things to external systems via an API might. Compensating controls that can help make the case for introducing AI-augmented testing, and even general development, include the following:

  • Ensuring DLP or CASB is deployed at all developer endpoints including terminated TLS and SSH protocols for deep inspection
  • Using pre-commit hooks in any development environment looking for regex or keywords that should...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime