"Mitre Attack Dataset for Knowledge Graph-Enhanced RAG Cyber Threat Intelligence"

"The Attack-Technique-Dataset represents a comprehensive cybersecurity intelligence repository systematically compiled from MITRE ATT&CK framework and Advanced Persistent Threat (APT) group sources. This structured dataset aggregates critical threat intelligence from attack.mitre.org, encompassing detailed attack technique descriptions, threat actor profiles, and associated research documentation. The collection was developed through Python-based web scraping methodologies, employing sophisticated data parsing techniques to extract and organize cybersecurity intelligence from MITRE ATT&CK enterprise techniques and APT group profiles.The dataset's architecture utilizes a Neo4j graph database infrastructure, comprising 1,427 nodes and 2,543 relationships, which enables dynamic representation of complex cybersecurity entity interconnections. Unlike conventional relational database approaches, this graph-based structure facilitates comprehensive mapping of APT groups to their employed attack techniques, supported by extensive research references. The dataset provides both summarized and detailed explanations of attack methodologies, creating a robust foundation for threat intelligence analysis, security research, and defensive strategy development.This resource addresses the critical need for structured cybersecurity threat intelligence by offering researchers, security professionals, and analysts a centralized, interconnected knowledge base that enhances understanding of threat actor behaviors, attack patterns, and cybersecurity threat landscapes through systematic data organization and relationship mapping."