Skill UI

This skill provides a comprehensive framework for ingesting, normalizing, and enriching threat intelligence (CTI) from multiple structured and unstructured sources. It guides users through scoring feeds, converting heterogeneous IOC formats (like OpenIOC, YARA) into the standardized STIX 2.1 format, and enriching indicators using external services (e.g., VirusTotal, PassiveTotal). Ideal for building robust, automated threat detection pipelines for SIEM and EDR systems.

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 skill outlines the development of an automated pipeline to ingest raw Indicators of Compromise (IOCs) from various sources. It performs normalization, defanging (e.g., converting 'http://' to 'hxxp://'), and converts indicators into the standardized STIX 2.1 format. The processed, safe indicators can then be securely distributed via TAXII feeds, MISP, and other threat intelligence platforms.

This guide demonstrates how to programmatically create, validate, and exchange complex structured threat intelligence objects (Indicators, Malware, Campaigns) using the STIX 2.1 standard and the stix2 Python library. It covers the full lifecycle of intelligence sharing, including defining patterns and publishing data via TAXII 2.1, making it essential for building sophisticated Threat Intelligence Platforms (TIPs) and integrating with SIEM/SOAR systems.

This skill provides a comprehensive guide to integrating STIX (Structured Threat Information eXpression) and TAXII (Trusted Automated eXchange of Intelligence Information). It covers using Python to consume and produce cyber threat intelligence feeds, including server discovery, object fetching, and parsing of STIX 2.1 objects for integration into SIEM and TIP platforms.

This skill guides the deployment and configuration of a TAXII 2.1 server using OpenTAXII. It enables automated, standardized exchange of STIX-formatted cyber threat intelligence (CTI) indicators between organizations. Use cases include establishing secure threat sharing pipelines, integrating with SIEM/SOAR platforms, and meeting stringent compliance requirements.

Build a PyMISP-driven threat intelligence platform that ingests multiple IOC feeds, tags MITRE ATT&CK techniques, enriches data via VirusTotal and AbuseIPDB, and exports STIX 2.1 bundles for SIEM pipelines.

This skill provides a comprehensive workflow for analyzing malicious software to extract actionable Indicators of Compromise (IOCs). It covers static analysis (PE parsing, hashing, string extraction) and dynamic analysis techniques. Users learn how to identify file hashes, network indicators (C2 IPs, domains), registry modifications, and behavioral artifacts, ultimately formatting the findings into standard STIX 2.1 formats for sharing and incident response.

This skill demonstrates how to use PyMISP, the official Python library, to programmatically interact with the MISP threat intelligence platform. Users can create, enrich, and manage structured threat events, including adding Indicators of Compromise (IOCs), applying TLP/MITRE ATT&CK tags, and exporting data in STIX 2.1 format for cross-platform sharing, making it ideal for security assessments and incident response.

Processes STIX 2.1 threat intelligence bundles delivered via TAXII 2.1 servers. It normalizes various threat intelligence objects (indicators, actors) into platform-native schemas, enabling automated ingestion, validation, and routing to SIEM, TIP, and EDR systems. Ideal for integrating new ISAC feeds or building bi-directional intelligence pipelines.

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.