Book Image

Practical Threat Intelligence and Data-Driven Threat Hunting

By : Valentina Costa-Gazcón
Book Image

Practical Threat Intelligence and Data-Driven Threat Hunting

By: Valentina Costa-Gazcón

Overview of this book

Threat hunting (TH) provides cybersecurity analysts and enterprises with the opportunity to proactively defend themselves by getting ahead of threats before they can cause major damage to their business. This book is not only an introduction for those who don’t know much about the cyber threat intelligence (CTI) and TH world, but also a guide for those with more advanced knowledge of other cybersecurity fields who are looking to implement a TH program from scratch. You will start by exploring what threat intelligence is and how it can be used to detect and prevent cyber threats. As you progress, you’ll learn how to collect data, along with understanding it by developing data models. The book will also show you how to set up an environment for TH using open source tools. Later, you will focus on how to plan a hunt with practical examples, before going on to explore the MITRE ATT&CK framework. By the end of this book, you’ll have the skills you need to be able to carry out effective hunts in your own environment.
Table of Contents (21 chapters)
1
Section 1: Cyber Threat Intelligence
5
Section 2: Understanding the Adversary
9
Section 3: Working with a Research Environment
14
Section 4: Communicating to Succeed
Appendix – The State of the Hunt

Using MITRE CALDERA

In this chapter, we are going to elaborate on our own adversary emulation plan and deploy it using the MITRE CALDERA framework, which was designed to perform "breach-and-simulation exercises and run autonomous red team engagements or automated incident responses."

CALDERA makes it easy for us to build a specific adversary with the characteristics we want so that we can deploy it in our environment and run our emulations. The first thing we need to understand about CALDERA is how it structures this information and what degrees of customization are possible. One of the best things about this framework is that it is flexible enough to allow you to build on top of it as much as you want.

CALDERA also allows you to automate the whole process, running it automatically, or to set up when you want the process to stop for you to make decisions instead of letting CALDERAS's machine learning algorithms make the decisions for you. You can learn more about...