Skill UI

A comprehensive, step-by-step guide for security professionals to perform deep-dive malware analysis. It covers methodologies for static analysis (disassemblers, imports), dynamic execution (sandboxing, monitoring), identifying Indicators of Compromise (IOCs), and structuring professional threat reports. Essential for incident response and threat intelligence.

This skill provides a systematic framework for analyzing cyber campaign attribution. It involves collecting, weighting, and correlating diverse indicators—such as infrastructure overlaps, TTP consistency, malware code similarities, and operational patterns—to determine the responsible threat actor. Utilizing structured methodologies like Analysis of Competing Hypotheses (ACH) and the Diamond Model, users can build confidence-weighted assessments to enhance threat intelligence accuracy.

Leverage Certificate Transparency (CT) logs via crt.sh and Certstream to proactively monitor for suspicious SSL/TLS certificates. This skill helps detect lookalike domains, unauthorized certificate issuance, and potential phishing infrastructure targeting your organization before attacks launch. Includes querying logic and threat intelligence integration.

A comprehensive guide and toolkit for analyzing malware Command-and-Control (C2) communication. This method helps security analysts reverse engineer network traffic captured from malware samples, identifying beaconing patterns, decoding custom protocols (HTTP, DNS, etc.), and mapping C2 infrastructure for advanced threat detection and threat intelligence gathering.

This skill analyzes intrusion activity against the Lockheed Martin Cyber Kill Chain framework. It identifies which attack phases an adversary has completed, points where defenses failed or succeeded, and recommends controls to disrupt the attack at earlier stages. It is essential for post-incident analysis, threat intelligence reporting, and designing robust defense-in-depth strategies.

This skill provides a comprehensive workflow for reverse engineering Go-compiled malware using Ghidra. It focuses on overcoming Go-specific binary challenges, such as non-null-terminated strings, complex metadata structures (pclntab), and function name recovery in stripped binaries. Users can extract build information, reconstruct dependencies, and analyze malicious capabilities essential for threat intelligence and incident response.

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 structured methodology and Python implementation for monitoring and analyzing data leak sites (DLS) associated with ransomware groups. It helps security analysts track victim postings, extract threat intelligence on group tactics, assess sector-specific risks, and understand evolving ransomware threat landscapes for proactive defense.

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 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 guides the creation of automated workflows for enriching raw Indicators of Compromise (IOCs) with multi-source threat intelligence context. It is designed for integration into SOAR platforms (e.g., Cortex XSOAR, Splunk SOAR) or Python pipelines. By automatically querying multiple sources like VirusTotal, AbuseIPDB, and MISP, it significantly reduces analyst mean time to triage (MTTT) and standardizes the resulting threat context and confidence scoring.