Anthropic-Cybersecurity-Skills/skills/analyzing-windows-prefetch-with-python/SKILL.md

name, description, domain, subdomain, tags, version, author, license

name	description	domain	subdomain	tags	version	author	license
analyzing-windows-prefetch-with-python	Parse Windows Prefetch files using the windowsprefetch Python library to reconstruct application execution history, detect renamed or masquerading binaries, and identify suspicious program execution patterns.	cybersecurity	digital-forensics	digital-forensics windows prefetch execution-history incident-response malware-analysis	1.0	mahipal	MIT

Analyzing Windows Prefetch with Python

Overview

Windows Prefetch files (.pf) record application execution data including executable names, run counts, timestamps, loaded DLLs, and accessed directories. This skill covers parsing Prefetch files using the windowsprefetch Python library to reconstruct execution timelines, detect renamed or masquerading binaries by comparing executable names with loaded resources, and identifying suspicious programs that may indicate malware execution or lateral movement.

Prerequisites

• Python 3.9+ with windowsprefetch library (pip install windowsprefetch)
• Windows Prefetch files from C:\Windows\Prefetch\ (versions 17-30 supported)
• Understanding of Windows Prefetch file naming conventions (EXECUTABLE-HASH.pf)

Steps

Step 1: Collect Prefetch Files

Gather .pf files from target system's C:\Windows\Prefetch\ directory.

Step 2: Parse Execution History

Extract executable name, run count, last execution timestamps, and volume information.

Step 3: Detect Suspicious Execution

Flag known attack tools (mimikatz, psexec, etc.), renamed binaries, and unusual execution patterns.

Step 4: Build Execution Timeline

Reconstruct chronological execution timeline from all Prefetch files.

Expected Output

JSON report with execution history, suspicious executables, renamed binary indicators, and timeline reconstruction.