Skill UI

A comprehensive guide detailing the entire workflow for analyzing embedded firmware. It covers hardware-level extraction methods (UART, JTAG, SPI dump), filesystem analysis (SquashFS, JFFS2), binary reverse engineering using tools like Ghidra, and identifying common vulnerabilities (Buffer Overflow, Command Injection). Ideal for security researchers and embedded systems engineers.

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.

Guides medical device teams through preparing ISO 13485:2016 Quality Management System documentation by combining gap analysis, requirements references, templates, and step-by-step creation workflows for manuals, procedures, and compliance artifacts.

This comprehensive guide provides advanced troubleshooting workflows for complex, microservices-based environments running on Kubernetes. It covers diagnosing issues like CrashLoopBackOff, cascade failures, resource pressure (CPU/Memory), and detailed Redis state analysis, ensuring systematic root cause identification across multiple services.

This skill provides a comprehensive workflow for identifying, unpacking, and analyzing packed malware samples, especially those utilizing the UPX format. It details methods for standard UPX decompression and advanced techniques for repairing modified PE headers or magic bytes that prevent automated extraction. The process supports preparing samples for deep static analysis and dynamic debugging.

This guide details the comprehensive workflow for conducting memory forensics using Volatility 3. It covers the entire incident response lifecycle, from acquiring raw RAM dumps to analyzing processes, detecting rootkits, investigating network connections, and extracting sensitive artifacts like credentials and injected code. Essential for live memory analysis in cybersecurity investigations.

This skill provides a comprehensive workflow to extract Indicators of Compromise (IOCs) from malware samples and analysis reports. It covers file hashes (SHA256, MD5), network artifacts (IPs, domains, URLs from strings and PCAPs), and host-based indicators (registry keys, file paths, mutexes) from sandbox reports. It is essential for threat intelligence sharing, building blocklists, and creating detection signatures (YARA, Snort).

A comprehensive guide for SOC analysts and digital forensics experts. This skill covers the entire lifecycle of a phishing incident, from initial user report and header analysis (SPF, DKIM, DMARC) to detonating malicious URLs/attachments in sandboxes. It guides users on scoping the attack, identifying impacted users via SIEM/proxy logs, and executing containment measures like email purges.

CAPE is an open-source sandbox built for automated malware analysis, derived from Cuckoo. It provides advanced behavioral monitoring, payload dumping, and configuration extraction using over 70 parsers for known malware families (e.g., Emotet, Cobalt Strike). It captures network IOCs, dropped files, and detects anti-evasion techniques, making it ideal for security assessments and incident response workflows via its robust API.

This comprehensive guide outlines a structured workflow for conducting digital forensics investigations across major cloud providers, including AWS, Azure, and GCP. It covers critical steps such as evidence preservation (snapshots, metadata capture), systematic log collection (CloudTrail, Activity Logs, Audit Logs, VPC Flow Logs), and advanced analysis techniques to trace unauthorized accesses and identify root causes of security breaches.

This skill provides a comprehensive, multi-stage guide for investigating insider threats. It covers the entire lifecycle, from receiving an allegation and ensuring legal authorization, to covert evidence collection (DLP logs, endpoint forensics), advanced user behavior pattern analysis, and reconstructing a detailed activity timeline for potential legal action. Essential for security incident response.

This comprehensive guide outlines the end-to-end workflow for mobile device forensics, covering data acquisition and analysis for both iOS and Android platforms. It details techniques using commercial tools like Cellebrite UFED and open-source utilities (ALEAPP, iLEAPP, ADB). This methodology is critical for investigating deleted messages, call logs, location data, and application artifacts in legal or corporate investigations.