MCP servers are now the default way to connect AI to real systems, tools and data. In SOC scenarios, they are used to pull logs, run hunts, and automate response steps. It feels clean and simple: you ask the model, it calls the tool, you get what you were looking for. Reality is messier. MCP servers …

Jupyter Notebooks are remarkably versatile tools, even within Microsoft Sentinel’s data lake where current capabilities are limited. While Microsoft frequently highlights historical threat intelligence correlation and long-term threat hunting as use cases, notebooks unlock far more practical …

When discussing Microsoft Sentinel data lake, the narrative centers on immediate value: cheaper ingestion, long-term storage, and historical correlation. These benefits are real, but they don’t address some interesting options. Sentinel data lake with KQL Jobs and Notebooks transforms how SIEM …

In today’s big data landscape, establishing a proper data architecture is essential before you begin collecting data. As data generation continues to accelerate, making informed decisions about what to store, where to store it, and in what format become increasingly critical. In the age of AI, …

In today’s cybersecurity landscape, data models are crucial - they give data the structure and context it needs to be truly usable and effective. Standardized models act as a universal language, turning raw security data into actionable insights for rapid detection, efficient investigation, …

Microsoft has just introduced Sentinel Data Lake (SDL) in public preview, and there’s already a flurry of excitement in the cybersecurity world. Most community blog posts so far focus on how to turn it on and when you might want to use it, but very few delve into how it will change your …