Skill UI

This skill analyzes Indicators of Compromise (IOCs)—such as IP addresses, domains, and file hashes—by querying multiple threat intelligence platforms (VirusTotal, AbuseIPDB, MISP). It determines maliciousness confidence, assigns blocking priorities, and attributes threats to campaigns, crucial for incident response, threat triage, and making informed security decisions.

This skill provides a comprehensive guide to using the Malpedia API for advanced malware intelligence analysis. Users can track malware family relationships, analyze variant evolution, extract associated YARA rules for detection, and map connections to specific threat actors. It is essential for security researchers and SOC analysts building robust threat models.

This skill provides a systematic methodology for mapping real-world threat actor Tactics, Techniques, and Procedures (TTPs) to the globally recognized MITRE ATT&CK framework. Users learn how to leverage tools like ATT&CK Navigator and Python libraries (e.g., attackcti, stix2) to analyze security incidents, visualize technical coverage heatmaps, identify critical detection gaps, and generate actionable intelligence reports linking observed Indicators of Compromise (IOCs) to specific adversary techniques across various platforms (Enterprise, Mobile, ICS).

This tool helps security analysts map Advanced Persistent Threat (APT) group tactics, techniques, and procedures (TTPs) to the MITRE ATT&CK framework. By utilizing the ATT&CK Navigator and the attackcti Python library, users can query STIX/TAXII data to visualize threat profiles, assess detection coverage gaps, and guide defensive planning for complex cyber incidents.

This tool provides comprehensive analysis of the cybersecurity threat landscape using the Malware Information Sharing Platform (MISP). It allows users to query event statistics, analyze attribute distributions (IPs, domains, hashes), identify top threat actors and malware families, and track temporal trends. It is essential for SOC analysts performing incident response, threat hunting, and building advanced detection rules.

A specialized tool for digital forensics investigators that parses the Windows Amcache.hve registry hive. It extracts crucial evidence regarding program execution history, application installation metadata, and loaded driver binaries. By correlating SHA-1 hashes and reconstructing timelines, users can determine which executables ran on a system, aiding in incident response and threat detection.

This skill provides a method to parse Windows Prefetch files (.pf) using Python, allowing security analysts to reconstruct detailed application execution histories. It is crucial for incident response, enabling the detection of renamed binaries, identifying suspicious execution patterns, and building accurate chronological timelines of system activity for deep forensic investigation.

This system automates the tracking and mapping of threat actor Command-and-Control (C2) networks. By leveraging passive DNS records, WHOIS data, certificate transparency logs, and IP enrichment, it helps security analysts perform infrastructure pivoting. It identifies shared hosting patterns, monitors domain reuse, and continuously maps adversary relationships for proactive threat intelligence.

This skill provides a systematic methodology for building comprehensive threat actor profiles using Open-Source Intelligence (OSINT). It involves gathering, correlating, and analyzing publicly available data from diverse sources (e.g., vendor reports, dark web forums, code repositories). Users can map adversary TTPs to MITRE ATT&CK, assess motivations, and build structured dossiers for proactive defensive strategies and attribution assessments.

This skill correlates disparate security incidents, Indicators of Compromise (IOCs), and adversary behaviors across time and organizations. It systematically identifies unified threat campaigns, attributes them to common threat actors, and extracts shared indicators for significantly improved detection capabilities. Ideal for cross-organizational threat intelligence sharing and building comprehensive campaign reports.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

A comprehensive guide to deploying and configuring osquery across diverse endpoints (Windows, macOS, Linux). This tool allows security teams to gather deep, SQL-based insights into endpoint state, including running processes, network connections, system configuration, and installed software. It is essential for threat hunting, compliance auditing, and building centralized fleet visibility.