Skill UI

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.

A comprehensive tool for security professionals to enumerate and analyze malware persistence mechanisms across critical Windows Auto-Start Extensibility Points (ASEPs). It systematically scans registry run keys, scheduled tasks, services, drivers, and startup locations. Ideal for incident response, threat hunting, and validating the complete removal of malicious autostart entries.

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.

This tool is designed for advanced threat hunting and digital forensics. It analyzes Windows Event Logs (specifically Script Block Logging 4104 and Module Logging 4103) to detect artifacts left by the PowerShell Empire post-exploitation framework. Detection patterns include default launchers, Base64 payloads (WebClient, FromBase64String), known module invocations (e.g., Invoke-Mimikatz), and staging URL patterns, helping confirm C2 activity and lateral movement.

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.

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.

A comprehensive toolkit using Splunk's SPL language to analyze Windows Security, System, and Sysmon event logs. It maps advanced detection queries to specific MITRE ATT&CK techniques, enabling SOC analysts to investigate authentication attacks (e.g., brute force, password spraying), detect privilege escalation, locate persistence mechanisms, and trace lateral movement for detailed forensic timeline analysis.

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.

This comprehensive guide details the systematic extraction and analysis of Windows Registry hives (SAM, SYSTEM, SOFTWARE, NTUSER.DAT) from forensic images. It demonstrates how to use specialized tools like RegRipper and Python scripts to uncover critical artifacts, including user activity history, persistence mechanisms (autorun keys), installed software records, and evidence of system compromise, which is crucial for digital forensics investigations.