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Practical Threat Intelligence and Data-Driven Threat Hunting

You're reading from   Practical Threat Intelligence and Data-Driven Threat Hunting A hands-on guide to threat hunting with the ATT&CK™ Framework and open source tools

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781838556372
Length 398 pages
Edition 1st Edition
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Author (1):
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Valentina Costa-Gazcón Valentina Costa-Gazcón
Author Profile Icon Valentina Costa-Gazcón
Valentina Costa-Gazcón
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Toc

Table of Contents (21) Chapters Close

Preface 1. Section 1: Cyber Threat Intelligence
2. Chapter 1: What Is Cyber Threat Intelligence? FREE CHAPTER 3. Chapter 2: What Is Threat Hunting? 4. Chapter 3: Where Does the Data Come From? 5. Section 2: Understanding the Adversary
6. Chapter 4: Mapping the Adversary 7. Chapter 5: Working with Data 8. Chapter 6: Emulating the Adversary 9. Section 3: Working with a Research Environment
10. Chapter 7: Creating a Research Environment 11. Chapter 8: How to Query the Data 12. Chapter 9: Hunting for the Adversary 13. Chapter 10: Importance of Documenting and Automating the Process 14. Section 4: Communicating to Succeed
15. Chapter 11: Assessing Data Quality 16. Chapter 12: Understanding the Output 17. Chapter 13: Defining Good Metrics to Track Success 18. Chapter 14: Engaging the Response Team and Communicating the Result to Executives 19. Other Books You May Enjoy Appendix – The State of the Hunt

Updating the hunting process

For educational purposes, we are covering the topic of documentation after exemplifying how to hunt for the adversary using Mordor datasets, but it is a good practice to document as you go so that you can keep better track of what you are doing and also make adjustments to the whole process.

As stated in the previous section, by documenting your actions, you'll identify where there is room for improvement. Threat hunting should be a continuous improvement process. If you are carrying out hunts without learning any new, valuable lessons about your environment, your data, and your methodology, you are probably not doing something right. You should always strive for more.

If you decide to follow the model presented in this chapter, most of the information relevant for this phase will come from the "lessons learned" step. In my opinion, this step is crucial and you should not skip it, but in any case, you should always reflect on the process...

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