Skill UI

This comprehensive guide details advanced forensic techniques for detecting and analyzing sophisticated malware that operates at the system's deepest levels, such as the Master Boot Record (MBR), Volume Boot Record (VBR), and UEFI firmware. It covers boot sector disassembly, UEFI module inspection, and memory forensics (SSDT/DKOM). Use this when standard security tools fail or when investigating nation-state level compromises.

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.

A comprehensive methodology for detecting advanced system compromises, including rootkits, hidden processes, and kernel-level malware. It utilizes memory forensics, cross-view detection (comparing different system views), and integrity checking to identify manipulated kernel structures, hooked system calls (SSDT, IAT, IRP), and covert network connections. Ideal for deep forensic investigations where standard tools fail to reveal the true state of a compromised system.

This tool leverages the Rekall memory forensics framework to conduct deep analysis of memory dumps. It is designed to detect sophisticated threats such as process hollowing, injected code via VAD anomalies, hidden operating system processes, and rootkit presence. It applies key forensic plugins (pslist, malfind, vadinfo) essential for rigorous incident response and malware analysis.

A comprehensive guide for digital forensics professionals on analyzing volatile memory dumps using Volatility 3. Learn to extract critical evidence, including running processes, network connections, loaded DLLs, system credentials, and detecting advanced threats like process hollowing and rootkits. Essential for incident response and malware analysis.