Book Image

Learn Azure Sentinel

By : Richard Diver, Gary Bushey
Book Image

Learn Azure Sentinel

By: Richard Diver, Gary Bushey

Overview of this book

Azure Sentinel is a Security Information and Event Management (SIEM) tool developed by Microsoft to integrate cloud security and artificial intelligence (AI). Azure Sentinel not only helps clients identify security issues in their environment, but also uses automation to help resolve these issues. With this book, you’ll implement Azure Sentinel and understand how it can help find security incidents in your environment with integrated artificial intelligence, threat analysis, and built-in and community-driven logic. This book starts with an introduction to Azure Sentinel and Log Analytics. You’ll get to grips with data collection and management, before learning how to create effective Azure Sentinel queries to detect anomalous behaviors and patterns of activity. As you make progress, you’ll understand how to develop solutions that automate the responses required to handle security incidents. Finally, you’ll grasp the latest developments in security, discover techniques to enhance your cloud security architecture, and explore how you can contribute to the security community. By the end of this book, you’ll have learned how to implement Azure Sentinel to fit your needs and be able to protect your environment from cyber threats and other security issues.
Table of Contents (22 chapters)
1
Section 1: Design and Implementation
4
Section 2: Data Connectors, Management, and Queries
9
Section 3: Security Threat Hunting
14
Section 4: Integration and Automation
17
Section 5: Operational Guidance

Introduction to KQL commands

Unlike SQL, a query starts with the data source, which can be either a table or an operator that produces a table, followed by commands that transform the data into what is needed. Each command will be separated using the pipe ( | ) delimiter.

What does this mean? If you are familiar with SQL, you would write a statement such as Select * from table to get the values. The same query in KQL would just be table, where table refers to the name of the log. It is implied that you want all the columns and rows. Later, we will discuss how to minimize what information is returned.

We will only be scratching the surface of what KQL can do here, but it will be enough to get you started writing your own queries so that you can develop queries for Azure Sentinel.

The following table provides an overview of the commands, functions, and operators we will be covering in the rest of this chapter:

Note

For a complete list of all the...