Skill UI

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.

This comprehensive forensic workflow guides investigators through the extraction and detailed analysis of Windows Registry hives (SAM, SYSTEM, SOFTWARE, etc.). It is used during incident response to uncover critical artifacts, including user activity history, malware persistence mechanisms (autorun keys), installed software records, and evidence of system compromise.

Builds a comprehensive, automated pipeline for malware submission and analysis. It collects suspicious files from multiple sources (EDR, email gateways), automatically submits them to sandbox environments and multi-engine scanners, and generates detailed verdicts and Indicators of Compromise (IOCs). Essential for SOC teams needing to scale high-volume malware triage and incident response.

This framework provides structured templates for managing communications during malware incidents. It generates tailored reports for various stakeholders, including C-level executives, technical IT teams, and regulatory bodies. The system accounts for severity levels (P1-P4) and different threat types, ensuring consistent, timely, and compliant information dissemination during a crisis.

This guide details the deployment and usage of MISP (Malware Information Sharing Platform) to centralize, correlate, and distribute threat intelligence. It covers architectural concepts, integrating diverse OSINT and commercial feeds (like abuse.ch, AlienVault OTX), and automating the flow of Indicators of Compromise (IOCs) into SIEM and SOAR systems via Docker and Python APIs.

MISP (Malware Information Sharing Platform) is an open-source platform designed for gathering, storing, and correlating Indicators of Compromise (IOCs). This skill guides users through deploying MISP using Docker, configuring various threat feeds (MISP, TAXII, CSV), and utilizing the PyMISP Python API. It enables the building of automated pipelines to aggregate diverse threat data, such as IP addresses, domains, and hashes, for enhanced security operations.

Guides responders through detecting, scoping, containing, analyzing, eradicating, and recovering from malware incidents on enterprise endpoints, using EDR, sandboxing, threat intel, and MITRE mapping for thorough remediation.

This guide details the process of implementing Zscaler Private Access (ZPA) to replace legacy VPNs with a modern Zero Trust Network Access (ZTNA) framework. It covers deploying App Connectors, defining application segments, and establishing granular access policies based on user identity, organizational user groups, and detailed device posture checks (e.g., compliance, anti-malware status).

A comprehensive toolkit designed for cybersecurity professionals to deobfuscate malicious JavaScript code. It reverses complex encoding layers (Base64, Hex, Unicode), eval chains, and control flow obfuscation techniques found in phishing pages, web skimmers, and dropper scripts, revealing the original malicious logic for thorough forensic analysis and threat intelligence gathering.

This skill provides systematic methods and advanced techniques to deobfuscate multi-layered PowerShell malware. It utilizes Abstract Syntax Tree (AST) analysis, dynamic execution tracing, and specialized tools to reveal hidden payloads, C2 infrastructure, and the original malicious logic. It is essential for security analysts, red teamers, and incident response teams performing deep malware analysis.

This skill provides comprehensive guidance and detection rules for identifying fileless malware, in-memory attacks, and living-off-the-land techniques. It covers detecting PowerShell exploitation, reflective DLL injection, WMI abuse, and registry-resident threats, enabling security teams to build robust detections when traditional antivirus fails.

This script detects and analyzes sophisticated fileless malware techniques that operate entirely in system memory. It specializes in identifying threats that utilize Living Off the Land Binaries (LOLBins), WMI event subscriptions, and registry-resident payloads, bypassing traditional file-based security controls. It is ideal for forensic investigations, threat hunting, and building advanced detection rules in modern enterprise environments.