mukul975/anthropic-cybersecurity-skills/analyzing-windows-prefetch-with-python
Claude Code and agent skill by mukul975/anthropic-cybersecurity-skills
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Checking that the SKILL.md file is still in the repository.
Parse Windows Prefetch (.pf) files with the windowsprefetch Python
Install
npx vskill@latest install mukul975/anthropic-cybersecurity-skills/analyzing-windows-prefetch-with-pythonSKILL.md
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.
When to Use
- When investigating security incidents that require analyzing windows prefetch with python
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
Prerequisites
- Python 3.9+ with
windowsprefetchlibrary (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.
Example Output
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/analyzing-windows-prefetch-with-python/SKILL.md
Popularity
- Repository stars
- 33,552
- Repository forks
- 4,068
- 7-day trend score
- 52
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 16 Mar 2026, 7 months ago.
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