Real world business tracks leading towards Azure Services
In this post I explore using Sentinel to detect, and respond to threats using custom analytics rules using Kusto Query Language (KQL). This allows you to tailor threat detection to your organization’s specific needs, ensuring that no threat goes unnoticed and tuning the detections to exclude low value and noisy results that clutter up the incident queue.
Join me in exploring the essential topic of integrating Microsoft threat intelligence within Microsoft Sentinel. In an era where cyber threats are becoming increasingly sophisticated, having a robust strategy to ingest and leverage threat intelligence is crucial for any SOC team. Understanding how to implement and utilize threat intelligence in Sentinel, you can significantly enhance your security posture, enabling faster detection and mitigation of potential threats before they escalate.
Join me as we walk through creating a custom Microsoft Sentinel Analytics Rule using KQL to identify suspicious login patterns based on failed attempts. We will explore the different components of creating these custom rules, what tuning looks like, and creating incidents from the rules.
Join me for the final article in the min-series on Enhancing Microsoft Sentinel. Today, we review ongoing optimizations and how to stay ahead of emerging threats.
Join me for Part 2 of 3 where we review advanced customizations in Microsoft Sentinel. We review some of the steps to advance your threat hunting and better protect your environment.
Join me for Part 1 of 3 where we review Building a Stronger Foundation in Microsoft Sentinel. We review the steps to help review and build a stronger SIEM solution together.
