Fine-tuning OpenAI Model for Cybersecurity Incident Classification in Microsoft Sentinel 

Discover how to level up your cybersecurity strategies with a customised OpenAI model in our latest tutorial. This step-by-step guide showcases how you can create, optimize, and implement your very own OpenAI model for Microsoft Sentinel, perfect for enhancing incident classification precision.
We begin by demonstrating how to effectively export incidents from Microsoft Sentinel, transforming them into a robust training dataset. Then, dive into the essential tools provided by OpenAI to optimize your training file, ensuring the utmost efficiency and effectiveness of your model.
The core of our tutorial involves training the model itself, where we demystify the complexities of fine-tuning an AI to meet your cybersecurity needs. Learn how to use the Azure OpenAI Studio (formerly known as Playground), a user-friendly platform for experimenting with and improving your customised AI.
Lastly, we'll integrate the model with a Logic App, a crucial step to streamline automation and improve your cybersecurity response.
Whether you're a seasoned security analyst or a newbie eager to enhance your cybersecurity prowess, this tutorial provides an in-depth understanding of incident classification in Microsoft Sentinel. We're featuring a demo case to illustrate how you can effectively distinguish between true positives and false positives, and much more.
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