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Log-based cyber threat hunting has emerged as an important solution tocounter sophisticated cyber attacks. However, existing approaches requirenon-trivial efforts of manual query construction and have overlooked the richexternal knowledge about threat behaviors provided by open-source Cyber ThreatIntelligence (OSCTI). To bridge the gap, we build ThreatRaptor, a system thatfacilitates cyber threat hunting in computer systems using OSCTI. Built uponmature system auditing frameworks, ThreatRaptor provides (1) an unsupervised,light-weight, and accurate NLP pipeline that extracts structured threatbehaviors from unstructured OSCTI text, (2) a concise and expressivedomain-specific query language, TBQL, to hunt for malicious system activities,(3) a query synthesis mechanism that automatically synthesizes a TBQL queryfrom the extracted threat behaviors, and (4) an efficient query executionengine to search the big system audit logging data.

A System for Efficiently Hunting for Cyber Threats in Computer Systems Using Threat Intelligence