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

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.

Detection types