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Practical Threat Detection Engineering

Practical Threat Detection Engineering

By : Megan Roddie, Jason Deyalsingh, Gary J. Katz
4.7 (20)
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Practical Threat Detection Engineering

Practical Threat Detection Engineering

4.7 (20)
By: Megan Roddie, Jason Deyalsingh, Gary J. Katz

Overview of this book

Threat validation is the backbone of every strong security detection strategy—it ensures your detection pipeline is effective, reliable, and resilient against real-world threats. This comprehensive guide is designed for those new to detection validation, offering clear, actionable frameworks to help you assess, test, and refine your security detections with confidence. Covering the entire detection lifecycle, from development to validation, this book provides real-world examples, hands-on tutorials, and practical projects to solidify your skills. Beyond just technical know-how, this book empowers you to build a career in detection engineering, equipping you with the essential expertise to thrive in today’s cybersecurity landscape. By the end of this book, you'll have the tools and knowledge to fortify your organization’s defenses, enhance detection accuracy, and stay ahead of cyber threats.
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

Phase 4 – Develop

The goal of this phase is to take technical specifications from the Investigate phase, then design, develop, and test a technical implementation for the relevant detection. The following are the inputs and outputs associated with this phase:

  • Input: Detection of technical specifications
  • Output: Detection code

As with most development work, this step requires rigorous planning. New detections need to not only satisfy the requirements but must also integrate with the rest of the detections within the environment. Detections are often implemented in the form of a query that is run against a data source or multiple data sources. Depending on your environment and its capabilities, different languages may need to interact with different data sources, and data pipelines and intermediary data stores may need to be built. The development process develops and implements a suitable solution for each new detection requirement, keeping both short- and...

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