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Learn Azure Sentinel

Learn Azure Sentinel

By : Richard Diver, Gary Bushey
5 (3)
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Learn Azure Sentinel

Learn Azure Sentinel

5 (3)
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)
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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

Summary

Now, you have learned about how to start doing threat hunting in Azure Sentinel. You learned about the Hunting page and the Notebooks page with its Jupyter Notebooks, and got a brief introduction on how to perform a threat-hunting investigation.

We looked at the tools that Azure Sentinel provides to assist with threat hunting. This includes queries that only get run periodically, either due to factors such as needing to look for a specific piece of information, or the fact that they would return too many results to be useful on a scheduled basis.

Another tool that can be used is the hosted instances of Jupyter Notebooks. These notebooks allow you to combine text, code, and output into one location to make hunting easier and repeatable. In addition, notebooks can query not only Azure Sentinel logs but also third-party information through the use of programming languages, including F# and Python.

In the next chapter, we will look at using Azure Sentinel playbooks to...

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