Case Studyllmmitre attackembeddingsdetection engineering
AI Workflow Accelerates Detection Coverage Analysis
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Relevance Score
The article outlines an AI-assisted workflow that helps security teams transform unstructured threat content into structured TTPs, maps them to the MITRE ATT&CK framework, and compares them against existing detection catalogs. It uses LLM prompts, Retrieval-Augmented Generation, vector similarity search, and LLM-based validation to prioritize likely coverage and gaps. The approach aims to shorten initial analysis from days to hours while retaining human-in-the-loop validation.



