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

Expected data

As illustrated in the JA3 pie chart above, we can see the JA3 client fingerprint of 44d502d471cfdb99c59bdfb0f220e5a8 is Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.116 Safari/537.36, which is the User-Agent from the Chrome web browser.

On my network, that user-agent should only be on Darwin systems; if that JA3 fingerprint was later observed on a Windows or Red Hat system, that would be a deviation of the profile and could be something that a threat hunter may want to investigate to understand if there was a process attempting to mask its identity, a misconfiguration of some type, or if there was an update to the profile needed.

Following the HIPESR model, this is part of the feedback loop where observations collected by operators are analyzed by analysts and operators to understand what is happening and respond by updating or tuning the profile or beginning response operations.