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Microsoft Sentinel in Action

Microsoft Sentinel in Action

By : Richard Diver, Gary Bushey
4.7 (3)
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Microsoft Sentinel in Action

Microsoft Sentinel in Action

4.7 (3)
By: Richard Diver, Gary Bushey

Overview of this book

Microsoft Sentinel is a security information and event management (SIEM) tool developed by Microsoft that helps you integrate cloud security and artificial intelligence (AI). This book will teach you how to implement Microsoft Sentinel and understand how it can help detect security incidents in your environment with integrated AI, threat analysis, and built-in and community-driven logic. The first part of this book will introduce you to Microsoft Sentinel and Log Analytics, then move on to understanding data collection and management, as well as how to create effective Microsoft Sentinel queries to detect anomalous behaviors and activity patterns. The next part will focus on useful features, such as entity behavior analytics and Microsoft Sentinel playbooks, along with exploring the new bi-directional connector for ServiceNow. In the next part, you’ll be learning how to develop solutions that automate responses needed to handle security incidents and find out more about the latest developments in security, 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 Microsoft Sentinel to fit your needs and protect your environment from cyber threats and other security issues.
Table of Contents (23 chapters)
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1
Section 1: Design and Implementation
4
Section 2: Data Connectors, Management, and Queries
9
Section 3: Security Threat Hunting
15
Section 4: Integration and Automation
18
Section 5: Operational Guidance

Chapter 5: Using the Kusto Query Language (KQL)

The Kusto Query Language (KQL) is a plain-text, read-only language that is used to query data stored in Azure Log Analytics workspaces. Much like SQL, it utilizes a hierarchy of entities that starts with databases, then tables, and finally columns. In this chapter, we will only concern ourselves with the table and column levels.

In this chapter, you will learn about a few of the many KQL commands that you can use to query your logs.

In this chapter, you will learn the following:

  • How to test your KQL queries
  • How to query a table
  • How to limit how many rows are returned
  • How to limit how many columns are returned
  • How to perform a query across multiple tables
  • How to graphically view the results

The chapter covers the following main topics:

  • Running KQL queries
  • Introduction to KQL commands
  • Query statements
  • Scalar functions
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