Skill UI

This skill automates the process of parsing Cyber Threat Intelligence (CTI) reports to extract adversary behaviors. It maps these behaviors to MITRE ATT&CK techniques and structures them as STIX 2.1 Attack Pattern objects. The resulting library supports detection engineering by generating rule templates (Sigma, YARA) for proactive defense and threat-informed security control implementation.

This system deploys advanced AI, NLP, and behavioral analytics to detect sophisticated Business Email Compromise (BEC) attacks. Unlike traditional filters that rely on malicious links, this solution analyzes writing style, tone, grammatical patterns, and contextual anomalies to identify pure social engineering impersonation, providing a robust defense layer against advanced phishing and fraud.

This guide demonstrates how to use the pycti Python client to model complex cyber threat intelligence within the OpenCTI platform. It structures threat actors, intrusion sets, campaigns, and TTPs into a unified STIX 2.1 knowledge graph. The skill is essential for correlating fragmented data from multiple sources (IOCs, reports) into a comprehensive, queryable adversary picture, supporting advanced threat hunting and detection engineering.