Security Setup
luongnv89/skills
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Agent skill
Analyzing Windows Prefetch With Python
Parse Windows Prefetch (.pf) files with the windowsprefetch Python library to reconstruct application execution history, run counts, and accessed file/volume lists.
Install Analyzing Windows Prefetch With Python
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-prefetch-with-python -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-windows-prefetch-with-python --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analyzing-windows-prefetch-with-python .claude/skills/analyzing-windows-prefetch-with-python && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "analyzing-windows-prefetch-with-python" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-prefetch-with-python into .claude/skills/analyzing-windows-prefetch-with-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-windows-prefetch-with-python", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-prefetch-with-pythonType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-prefetch-with-python -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-windows-prefetch-with-python --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/analyzing-windows-prefetch-with-python .agents/skills/analyzing-windows-prefetch-with-python && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "analyzing-windows-prefetch-with-python" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-prefetch-with-python into .agents/skills/analyzing-windows-prefetch-with-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-windows-prefetch-with-python", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-prefetch-with-python -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-windows-prefetch-with-python --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/analyzing-windows-prefetch-with-python .cursor/skills/analyzing-windows-prefetch-with-python && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "analyzing-windows-prefetch-with-python" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-prefetch-with-python into .cursor/skills/analyzing-windows-prefetch-with-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-windows-prefetch-with-python", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git --path skills/analyzing-windows-prefetch-with-python--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-prefetch-with-python -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-windows-prefetch-with-python --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/analyzing-windows-prefetch-with-python .gemini/skills/analyzing-windows-prefetch-with-python && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "analyzing-windows-prefetch-with-python" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-prefetch-with-python into .gemini/skills/analyzing-windows-prefetch-with-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-windows-prefetch-with-python", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-windows-prefetch-with-pythonInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-prefetch-with-python -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/analyzing-windows-prefetch-with-python .github/skills/analyzing-windows-prefetch-with-python && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "analyzing-windows-prefetch-with-python" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-prefetch-with-python into .github/skills/analyzing-windows-prefetch-with-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-windows-prefetch-with-python", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-prefetch-with-python -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-windows-prefetch-with-python --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/analyzing-windows-prefetch-with-python .opencode/skills/analyzing-windows-prefetch-with-python && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "analyzing-windows-prefetch-with-python" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-prefetch-with-python into .opencode/skills/analyzing-windows-prefetch-with-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyzing-windows-prefetch-with-python", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
analyzing-windows-prefetch-with-python- GitHub stars
- 34k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 211 words
- Files
- 4 (incl. scripts, references)
- Skills in repo
- 639
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Parse Windows Prefetch (.pf) files with the windowsprefetch Python library to reconstruct application execution history, run counts, and accessed file/volume lists.
- Works in 4 steps: Collect Prefetch Files → Parse Execution History → Detect Suspicious Execution → …
- Investigating renamed
- SKILL.md covers Overview, When to Use, Prerequisites and Steps, plus 2 more sections
- Runs Python scripts from its folder
What it does
Analyzing Windows Prefetch With Python is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Parse Windows Prefetch (.pf) files with the windowsprefetch Python library to reconstruct application execution history, run counts, and accessed file/volume lists. Use when investigating renamed or masquerading binaries, verifying program execution timelines, or hunting for suspicious execution patterns in incident response.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).
It sits in DevOps & Cloud, covering Incident response. It works with Python. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.
When your agent uses it
- Investigating renamed
- Masquerading binaries
- Verifying program execution timelines
- Hunting for suspicious execution patterns in incident response
Example prompts
- “/analyzing-windows-prefetch-with-python”
Requirements
- Python 3
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Analyzing Windows Prefetch With Python loads about 1.3k tokens when it runs, and up to ~1.7k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 211 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 211 words, ~1,258 tokens.
Download SKILL.mdSave it as
.claude/skills/analyzing-windows-prefetch-with-python/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- analyzing-windows-prefetch-with-python
- description
- Parse Windows Prefetch (.pf) files with the windowsprefetch Python library to reconstruct application execution history, run counts, and accessed file/volume lists. Use when investigating renamed or masquerading binaries, verifying program execution timelines, or hunting for suspicious execution patterns in incident response.
- domain
- cybersecurity
- subdomain
- digital-forensics
- tags
- digital-forensics, windows, prefetch, execution-history, incident-response, malware-analysis
- mitre_attack
- T1036.005, T1070.004, T1070, T1003.001, T1057
- version
- 1.0
- author
- mahipal
- license
- Apache-2.0
- nist_csf
- RS.AN-03, DE.AE-02, RS.MA-01
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
$ python3 prefetch_analyzer.py --dir /evidence/Windows/Prefetch --output /analysis/prefetch_report
Windows Prefetch Analyzer v2.1
================================
Source: /evidence/Windows/Prefetch/
Prefetch Format: Windows 10 (MAM compressed, version 30)
Files Found: 234
--- Execution Timeline (Incident Window: 2024-01-15 to 2024-01-18) ---
Last Executed (UTC) | Run Count | Filename | Hash | Path
------------------------|-----------|-----------------------------|----------|------------------------------------------
2024-01-15 14:33:15 | 1 | Q4_REPORT.XLSM-2A1B3C4D.pf | 2A1B3C4D | C:\Users\jsmith\Downloads\Q4_Report.xlsm
2024-01-15 14:35:44 | 1 | POWERSHELL.EXE-A2B3C4D5.pf | A2B3C4D5 | C:\Windows\System32\WindowsPowerShell\v1.0\powershell.exe
2024-01-15 14:36:30 | 3 | UPDATE_CLIENT.EXE-B3C4D5E6.pf| B3C4D5E6| C:\ProgramData\Updates\update_client.exe
2024-01-15 15:10:22 | 1 | NETSCAN.EXE-C4D5E6F7.pf | C4D5E6F7 | C:\Users\jsmith\Downloads\netscan.exe
2024-01-16 02:28:00 | 1 | PROCDUMP64.EXE-D5E6F7A8.pf | D5E6F7A8 | C:\Windows\Temp\procdump64.exe
2024-01-16 02:30:15 | 2 | MIMIKATZ.EXE-E6F7A8B9.pf | E6F7A8B9 | C:\Windows\Temp\mimikatz.exe
2024-01-16 02:40:00 | 4 | PSEXEC.EXE-F7A8B9C0.pf | F7A8B9C0 | C:\Users\jsmith\AppData\Local\Temp\psexec.exe
2024-01-17 02:45:00 | 1 | SDELETE64.EXE-A8B9C0D1.pf | A8B9C0D1 | C:\Windows\Temp\sdelete64.exe
2024-01-18 03:00:45 | 1 | WEVTUTIL.EXE-B9C0D1E2.pf | B9C0D1E2 | C:\Windows\System32\wevtutil.exe
--- Renamed Binary Detection ---
ALERT: UPDATE_CLIENT.EXE loaded DLLs consistent with Cobalt Strike beacon:
Referenced DLLs: wininet.dll, ws2_32.dll, advapi32.dll, dnsapi.dll, netapi32.dll
Volume: \VOLUME{01d94f2a3b5c7d8e-A4E73F21} (C:)
Directories referenced:
C:\ProgramData\Updates\
C:\Windows\System32\
--- Execution Frequency Analysis ---
Most Executed (Top 5):
1. SVCHOST.EXE (267 runs)
2. CHROME.EXE (189 runs)
3. EXPLORER.EXE (156 runs)
4. RUNTIMEBROKER.EXE (134 runs)
5. OUTLOOK.EXE (98 runs)
First-Time Executions (Never seen before incident window):
6 executables first run between 2024-01-15 and 2024-01-18
Summary:
Total prefetch files: 234
Suspicious executables: 6
Renamed binary indicators: 1 (update_client.exe)
Anti-forensics tools: 2 (sdelete64.exe, wevtutil.exe)
JSON report: /analysis/prefetch_report/prefetch_timeline.json© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (scripts, references) in skills/analyzing-windows-prefetch-with-python of mukul975/Anthropic-Cybersecurity-Skills.
- SKILL.md
- LICENSE
- references/api-reference.md
- scripts/agent.py
Open the folder on GitHubat commit 54a7988
Compare with similar skills
Analyzing Windows Prefetch With Python next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Analyzing Windows Prefetch With Python this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Security Setupluongnv89/skills | 131 | — | ~4.5k | Automated safety check: Pass | MIT | |
| Devops AgentLeoYeAI/openclaw-master-skills | 2.2k | — | ~5.3k | Automated safety check: Notes | MIT | |
| Alibabacloud Ecs Sec Userspacealiyun/alibabacloud-ecs-troubleshoot-skills | 148 | — | ~2.6k | Automated safety check: Notes | Apache-2.0 | |
| Incident Responsehypnguyen1209/offensive-claude | 386 | — | ~2.5k | Automated safety check: Pass | MIT | |
| Incident Responsealirezarezvani/claude-skills | 28k | — | ~3.8k | Automated safety check: Pass | MIT |
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Works with
Categories
Questions about Analyzing Windows Prefetch With Python
What does Analyzing Windows Prefetch With Python do?
Parse Windows Prefetch (.pf) files with the windowsprefetch Python library to reconstruct application execution history, run counts, and accessed file/volume lists. Analyzing Windows Prefetch With Python is an agent skill from mukul975/Anthropic-Cybersecurity-Skills.pf) files with the windowsprefetch Python library to reconstruct application execution history, run counts, and accessed file/volume lists.
When should I use Analyzing Windows Prefetch With Python?
Analyzing Windows Prefetch With Python fits situations like: investigating renamed; masquerading binaries; verifying program execution timelines; hunting for suspicious execution patterns in incident response.
How do I install Analyzing Windows Prefetch With Python in Claude Code?
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-prefetch-with-python -a claude-code`. Or copy the skill folder (skills/analyzing-windows-prefetch-with-python in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/analyzing-windows-prefetch-with-python in your project. Claude Code loads it when a task matches its description.
How do I install Analyzing Windows Prefetch With Python in Codex?
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-prefetch-with-python -a codex`. Or copy the skill folder (skills/analyzing-windows-prefetch-with-python in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/analyzing-windows-prefetch-with-python in your project. Codex loads it when a task matches its description.
Can I use Analyzing Windows Prefetch With Python in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-windows-prefetch-with-python -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyzing-windows-prefetch-with-python, .gemini/skills/analyzing-windows-prefetch-with-python, .github/skills/analyzing-windows-prefetch-with-python and .opencode/skills/analyzing-windows-prefetch-with-python in your project.
What does Analyzing Windows Prefetch With Python need to run?
Going by SKILL.md and its folder, Analyzing Windows Prefetch With Python needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Analyzing Windows Prefetch With Python access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Analyzing Windows Prefetch With Python safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Analyzing Windows Prefetch With Python use?
Analyzing Windows Prefetch With Python is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Analyzing Windows Prefetch With Python use?
About 1.3k tokens (SKILL.md is roughly 5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 443 tokens, read only when the agent opens those files.
What are the alternatives to Analyzing Windows Prefetch With Python?
Skills that share tags, products or a category with Analyzing Windows Prefetch With Python: Security Setup (luongnv89/skills, 131 stars), Devops Agent (LeoYeAI/openclaw-master-skills, 2.2k stars), Alibabacloud Ecs Sec Userspace (aliyun/alibabacloud-ecs-troubleshoot-skills, 148 stars) and Incident Response (hypnguyen1209/offensive-claude, 386 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Analyzing Windows Prefetch With Python?
mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 33,870 GitHub stars. The repository holds 639 skills in this directory. The repository was last updated on August 31, 2026.
Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.