Book Image

Threat Hunting with Elastic Stack

By : Andrew Pease
5 (1)
Book Image

Threat Hunting with Elastic Stack

5 (1)
By: Andrew Pease

Overview of this book

Threat Hunting with Elastic Stack will show you how to make the best use of Elastic Security to provide optimal protection against cyber threats. With this book, security practitioners working with Kibana will be able to put their knowledge to work and detect malicious adversary activity within their contested network. You'll take a hands-on approach to learning the implementation and methodologies that will have you up and running in no time. Starting with the foundational parts of the Elastic Stack, you'll explore analytical models and how they support security response and finally leverage Elastic technology to perform defensive cyber operations. You’ll then cover threat intelligence analytical models, threat hunting concepts and methodologies, and how to leverage them in cyber operations. After you’ve mastered the basics, you’ll apply the knowledge you've gained to build and configure your own Elastic Stack, upload data, and explore that data directly as well as by using the built-in tools in the Kibana app to hunt for nefarious activities. By the end of this book, you'll be able to build an Elastic Stack for self-training or to monitor your own network and/or assets and use Kibana to monitor and hunt for adversaries within your network.
Table of Contents (18 chapters)
Section 1: Introduction to Threat Hunting, Analytical Models, and Hunting Methodologies
Section 2: Leveraging the Elastic Stack for Collection and Analysis
Section 3: Operationalizing Threat Hunting

Generating tailored detection logic

It's great that we've identified a good search query to identify this type of malicious activity, but let's take that a step further to generate detection events in the Security app so that we aren't continually having to run a query in the Discover app.

Using what we learned in the Creating detection rules section of Chapter 8, The Elastic Security App, we can create a custom query detection rule to identify this activity:

Figure 9.16 – Tailored detection logic for an observed activity

In the preceding screenshot, we can see the completed detection rule that will generate an event when this activity is observed in the future:

Figure 9.17 – Tailored detection logic for an observed activity

In the preceding screenshot, we can see that the detection rule was triggered based on the persistence detection logic that we just created.

In this section, we created tailored detection logic based on the information...