Microsoft Sentinel Capabilities Demo - Unified Security Platform and Threat Investigation

Explore Microsoft Sentinel's evolution into a unified security platform through this comprehensive 46-minute conference presentation that demonstrates how security practitioners can manage and investigate threats across their entire digital estate from a single console. Learn about the core principle that since attackers think in graphs and move across domains, defenders need a consolidated, cross-domain view delivered through the Microsoft Defender console, which brings together tools for identity, endpoints, email, and cloud infrastructure. Discover the proactive exposure management capability powered by the Sentinel Graph that visualizes attack paths from internet-exposed assets to critical data, enabling teams to prioritize patching the most crucial vulnerabilities first and move beyond simple vulnerability scanning to understand true organizational risk. Understand how the platform offers a unified incident queue that reduces alert fatigue by correlating alerts from both Microsoft and third-party sources into a single coherent narrative, with the Sentinel Graph stitching together alerts and calculating potential blast radius to show analysts where attackers could pivot next. Examine how this graph-based approach transforms threat hunting, allowing analysts to perform traditional Kusto Query Language (KQL) queries on recent data while also conducting "posture hunting" directly on the graph to proactively find overprivileged access or risky configurations before exploitation. Delve into the Sentinel Data Lake architecture that decouples storage and compute for cost-effective, long-term retention of high-volume data like syslogs and cloud trails in an open Delta Parquet format, enabling multiple forms of analysis on a single copy of data including KQL queries for retro-hunts spanning years and deep big-data analysis using Spark and Python directly within VS Code. Experience how AI enhancement through the Sentinel MCP server and GitHub Copilot enables "vibe hunting" where analysts can use natural language to ask questions, discover relevant data tables, and have AI generate entire Python analysis notebooks, dramatically upskilling SOC teams and making sophisticated data science accessible to every team member.