Skill UI

A comprehensive guide for digital forensics analysts to investigate compromised Linux systems. This workflow details the collection and analysis of critical system artifacts, including authentication logs, shell histories, SSH keys, and system configurations. Use this methodology during incident response to detect rootkits, unauthorized persistence mechanisms, and reconstruct full attacker activity.

This skill details the forensic analysis of Windows LNK shortcut files and Jump Lists. These artifacts record critical user activity, including file access and program execution, even after the original source files have been deleted. It covers using specialized tools (LECmd, JLECmd) and Python parsing techniques to reconstruct user timelines, making it essential for incident response and deep digital forensics examinations.

This skill details advanced digital forensics techniques for recovering metadata and content of deleted files by analyzing the NTFS Master File Table ($MFT). It covers examining key system artifacts like $LogFile and $UsnJrnl, and analyzing MFT slack space. Use this when reconstructing file system timelines, investigating data loss, or detecting anti-forensic techniques like timestomping during a Windows forensic examination.

A comprehensive guide for deep packet inspection and network forensics using Wireshark and tshark. This skill is critical for incident response, where it allows users to capture, filter, and analyze network packet data to identify malicious command-and-control traffic, diagnose complex protocol issues, extract indicators of compromise (IOCs), and reconstruct data exfiltration paths. Use it for validating security rules and understanding network anomalies.

A comprehensive toolset for digital forensics investigators, enabling the parsing of proprietary Microsoft Outlook PST and OST files. It extracts critical evidence including full message content, detailed email headers (for message routing/tracing), attachments, and deleted items from the Recoverable Items folder. Essential for e-discovery, legal investigations, and security incident response to reconstruct communication patterns and analyze message metadata.

A dedicated tool for forensic analysis of Windows PowerShell Script Block Logs (Event ID 4104) captured in EVTX files. It reconstructs multi-block scripts, applying advanced detection heuristics such as entropy analysis and pattern matching to identify obfuscated commands, encoded payloads (Base64), download cradles, and AMSI bypass attempts, crucial for threat hunting and incident response.

This skill guides the process of analyzing Windows Prefetch (.pf) files to reconstruct a detailed program execution history. By parsing these system artifacts, users can determine which applications were run, how many times, and when. It is crucial for building forensic timelines, confirming suspicious binary execution during malware investigations, and localizing evidence in a Windows system.

A comprehensive guide utilizing Splunk Enterprise Security and SPL to conduct deep forensic analysis of security incidents. This skill covers correlating disparate sources like Windows event logs, firewall records, proxy data, and Sysmon logs to detect TTPs, reconstruct timelines, and identify anomalies, making it essential for incident response and threat hunting.

A comprehensive method for deep forensic analysis of NTFS disk images. It examines critical artifacts such as the Master File Table (MFT), USN Change Journal, Alternate Data Streams (ADS), and unallocated slack space. This is essential for recovering deleted file metadata, detecting hidden data, and reconstructing file system activities when standard recovery tools are insufficient.

This tool correlates multiple system artifacts, including Windows registry keys (USBSTOR, MountedDevices), Event Logs, and SetupAPI logs, to reconstruct a detailed timeline of USB device usage. It determines first/last connection timestamps, tracks device provenance, and maps drive letter assignments. Essential for digital forensics investigations, insider threat detection, and verifying compliance regarding removable media usage.

This guide details a comprehensive workflow for digital forensic investigations focusing on Amcache.hve registry hive. It teaches how to use AmcacheParser to extract evidence of program execution, application installation, and driver loading, including correlating SHA-1 hashes with threat intelligence and reconstructing timelines. This is crucial for DFIR work to identify deleted executables and malicious activity.

This skill parses Windows Prefetch (.pf) files to reconstruct detailed application execution history. It is crucial for digital forensics, allowing analysts to track execution timelines, identify suspicious or renamed binaries, and investigate potential malware activity or lateral movement during incident response. It uses Python to extract run counts and accessed file details.