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)
Section 1: Cyber Threat Intelligence
Section 2: Understanding the Adversary
Section 3: Working with a Research Environment
Section 4: Communicating to Succeed
Appendix – The State of the Hunt

Improving data quality

Although interesting and an extensive area of expertise, we are not going to focus here on all the processes that a data governance team should take care of in order to ensure data quality. There are already several books out there about data management that can help you establish reliable processes to work with your data.

We are going to suppose that the organization has already performed data asset inventories and established baselines for the data dimensions that are going to be rated. Let's suppose too that the organization has a set of data quality rules to check data against the baselines and that the data management team makes regular assessments to measure the quality of the data and the subsequent process to improve it.

Roberto Rodriguez wrote a blog post about how to deal with these issues called Ready to hunt? First, show me your data, available at In this...