Detecting Threats and Responding with KQL in Microsoft Sentinel

Strengthening Security Posture with KQL-based threat hunting

As a cloud-native SIEM and SOAR solution, Microsoft Sentinel leverages the power of Kusto Query Language (KQL) to enhance the process of effectively detecting and responding to digital threats to analyse log data, identify anomalies, and automate incident response. KQL was developed by Microsoft and is used primarily and beyond the Microsoft Ecosystem.

For Threat detection, security analysts can create detailed KQL queries to identify suspicious activities, such as network anomalies, beaconing patterns, and unauthorized access attempts.

Once threats are detected, response automation actions are initiated through custom playbooks and rules using KQL, triggering actions such as isolating endpoints, blocking malicious IPs via Azure Firewall, or alerting.

Below are some KQL use cases for various common applications and platforms in Microsoft:

• Microsoft Sentinel — Centralised log management and analytics for detecting suspicious activity. A cloud-native SIEM.
• Azure Security Center — Provides security management and threat protection across hybrid cloud environments.
• Azure Data Explorer — Facilitates real-time analytics on large datasets.
• Azure Monitor — Monitors applications and infrastructure, providing insights into performance and operational health.
• Microsoft Defender — Provides comprehensive threat protection across endpoints, identities and applications.
• Business intelligence Tools — Analyses business data for informed decision-making.
• Application Insights — Monitors performance and usage of applications to optimise user experience.

Developing Effective Detection Logic in Microsoft Sentinel

Detection Logic is based on specific patterns, behaviours, or anomalies.

Key features that…