| name | analyzing-windows-prefetch-with-python |
| description | 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. |
| domain | cybersecurity |
| subdomain | digital-forensics |
| tags | ["digital-forensics","windows","prefetch","execution-history","incident-response","malware-analysis"] |
| version | 1.0 |
| author | mahipal |
| license | Apache-2.0 |
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.
