Demonstrates enhanced cybersecurity analysis in Security Operations Centers, suggesting improved threat response.
The increasing sophistication of cyber threats demands faster and more efficient threat detection and response mechanisms within Security Operations Centers (SOCs). Traditional threat hunting approaches often require extensive manual effort in creating security queries, mapping threats to frameworks, and analyzing threat intelligence, resulting in delayed incident response. This paper presents HuntForge, an AI-powered threat hunting assistant that leverages Retrieval- Augmented Generation (RAG) and large language models to provide intelligent cybersecurity analysis through natural language interactions. The system integrates the MITRE ATT&CK framework, Sigma detection rules, and incident response playbooks to generate contextual threat insights, automated technique mapping, risk assessments, and remediation recommendations. HuntForge enhances analyst productivity, reduces investigation time, improves detection accuracy, and supports informed decision-making during cybersecurity operations, making advanced threat hunting more accessible and efficient for security teams.
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BHOOMIKA MANJUNATH (2026) studied this question.
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