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

Sigma rules

We covered Sigma rules in Chapter 5, Working with Data, but just to refresh your memory, Sigma rules are the YARA rules of log files. Sigma allows the community to share detection rules using a specific "language" that can be translated into different SIEM formats.

Now, let's learn how to use Sigma rules for our detections.

Important Note

One important thing to keep in mind while creating rules is that they shouldn't be so generic that they trigger without any malicious behaviour occurring. Rules have to be broad enough to capture procedure variations, but also not too broad that they start overloading the analyst with false positives.

Let's create a rule for our initial access file. Keep in mind that this rule will only be useful if we are completely sure that there are no screensavers in our environment that require internet connection, such as, for example, a screensaver connecting to a weather site.

The first thing we need to...