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Threat Hunting with Elastic Stack

You're reading from Threat Hunting with Elastic Stack Solve complex security challenges with integrated prevention, detection, and response

Product type Paperback

Published in Jul 2021

Publisher Packt

ISBN-13 9781801073783

Length 392 pages

Edition 1st Edition

Tools

Kibana

Concepts

Cybersecurity

Author (1):

Andrew Pease

View More author details

Table of Contents (18) Chapters

Preface

1. Section 1: Introduction to Threat Hunting, Analytical Models, and Hunting Methodologies

2. Chapter 1: Introduction to Cyber Threat Intelligence, Analytical Models, and Frameworks FREE CHAPTER

3. Chapter 2: Hunting Concepts, Methodologies, and Techniques

4. Section 2: Leveraging the Elastic Stack for Collection and Analysis

5. Chapter 3: Introduction to the Elastic Stack

6. Chapter 4: Building Your Hunting Lab – Part 1

7. Chapter 5: Building Your Hunting Lab – Part 2

8. Chapter 6: Data Collection with Beats and Elastic Agent

9. Chapter 7: Using Kibana to Explore and Visualize Data

10. Chapter 8: The Elastic Security App

11. Section 3: Operationalizing Threat Hunting

12. Chapter 9: Using Kibana to Pivot Through Data to Find Adversaries

13. Chapter 10: Leveraging Hunting to Inform Operations

14. Chapter 11: Enriching Data to Make Intelligence

15. Chapter 12: Sharing Information and Analysis

16. Assessments

17. Other Books You May Enjoy

Further reading

To learn more about applied threat hunting methodologies as they relate to cyberspace, check out these resources:

Robert Clark, Intelligence Analysis: A Target-Centric Approach, SAGE Publications
Randolph H. Pherson, Richards Heuer. Structured Analytic Techniques for Intelligence Analysis, SAGE Publications
Rebekah Brown, Scott J Roberts, Intelligence-Driven Incident Response: Outwitting the Adversary, O'Riley Media, Incorporated

References for LOLBins:

Windows – https://lolbas-project.github.io
UNIX/Linux – https://gtfobins.github.io
Researcher Disclosure Tweet – https://twitter.com/mohammadaskar2/status/1301263551638761477
MpCmdRun LOLBin Detection Engine Alert – https://github.com/elastic/detection-rules/issues/246

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Authors (1)

Pease

Pease

Andrew Pease began his journey into information security in 2002. He has performed security monitoring, incident response, threat hunting, and intelligence analysis for various organizations from the United States Department of Defense, a biotechnology company, and co-founded a security services company called Perched, which was acquired by Elastic in 2019. Andrew is currently employed with Elastic as a Principal Security Research Engineer where he performs intelligence and analytics research to identify adversary activity on contested networks. He has been using Elastic for network and endpoint-based threat hunting since 2013, He has developed training on security workloads using the Elastic Stack since 2017, and currently works with a team of brilliant engineers that develop detection logic for the Elastic Security App.

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