Skill UI

A comprehensive guide for threat hunters and incident responders to detect WMI-based persistence mechanisms (MITRE T1546.003). It details the analysis of Sysmon Event IDs 19, 20, and 21, cross-referencing these events with root\subscription namespaces and using tools like Autoruns and SIEM analysis for robust detection.

Monitors Windows process creation events to flag Living Off The Land Binary abuse by matching Event ID 4688/Sysmon 1 logs against LOLBAS database entries, supporting threat hunting and SIEM rule creation for fileless attacks.

This skill guides the deployment and configuration of the Dragos Platform for specialized Operational Technology (OT) and Industrial Control System (ICS) network monitoring. It leverages industrial protocol parsers and threat intelligence to detect sophisticated threats (e.g., VOLTZITE). It is essential for establishing OT Security Operations Centers (SOCs) or integrating dedicated ICS monitoring capabilities into enterprise SIEM solutions.

This methodology provides SOC teams with an adversary-centric framework to evaluate security detection capabilities against the MITRE ATT&CK framework. By systematically mapping existing SIEM rules and data sources, users can identify critical detection gaps, prioritize rule development efforts, and measure the overall maturity of their security operations center (SOC) defenses over time.

Learn how to implement Runtime Application Self-Protection (RASP) agents for Java and Python web applications. This skill covers deploying OpenRASP, detecting OWASP Top 10 attacks (SQLi, XSS, RCE), configuring security policies, and integrating real-time security alerts with SIEM platforms for comprehensive defense in depth.

This skill guides the process of designing, implementing, and validating advanced security detection use cases for Security Information and Event Management (SIEM) platforms like Splunk, Elastic, and Microsoft Sentinel. It focuses on mapping organizational threat profiles to the MITRE ATT&CK framework to build formal, high-fidelity detection rules, thereby strengthening Security Operations Center (SOC) coverage and reducing blind spots.

This skill provides a comprehensive guide on integrating Cyber Threat Intelligence (CTI) feeds using STIX 2.1 and TAXII 2.1 standards. It demonstrates how to build both consumer and producer capabilities in Python, covering server discovery, polling collections, and parsing complex STIX objects (Indicators, Malware, Threat Actors). Ideal for professionals building SIEM/TIP integrations or advanced security architectures.

Learn how to deploy and configure a TAXII 2.1 server using OpenTAXII and Medallion. This guide covers publishing STIX 2.1 bundles, managing collections for various threat feeds, and integrating the resulting data stream with SIEM/SOAR platforms to automate the exchange of cyber indicators between organizations.

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.

Implements a comprehensive incident ticketing system that connects SIEM alerts to major ITSM platforms like ServiceNow, Jira, or TheHive. This solution formalizes incident tracking, automates ticket creation, and manages critical processes such as Service Level Agreement (SLA) tracking, complex escalation workflows, and compliance documentation throughout the entire incident lifecycle.

This skill maps observed adversary behaviors, security alerts, and detection rules to the MITRE ATT&CK framework. It is essential for quantifying detection coverage, building ATT&CK heatmaps, tagging SIEM alerts, and prioritizing security controls based on known threat actor playbooks. Use it for comprehensive gap analysis and risk reporting.

This skill guides the systematic management of Indicators of Compromise (IOCs). It covers the entire lifecycle, from initial discovery and validation through enrichment (e.g., VirusTotal, Shodan) and deployment to SIEM/IDS. Key features include confidence decay over time, false positive tracking, and automated retirement policies, ensuring the threat intelligence database remains high-quality and actionable.