external/anthropic-cybersecurity-skills/skills/analyzing-windows-prefetch-with-python/SKILL.md
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.
npx skillsauth add seikaikyo/dash-skills analyzing-windows-prefetch-with-pythonInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
windowsprefetch library (pip install windowsprefetch)Gather .pf files from target system's C:\Windows\Prefetch\ directory.
Extract executable name, run count, last execution timestamps, and volume information.
Flag known attack tools (mimikatz, psexec, etc.), renamed binaries, and unusual execution patterns.
Reconstruct chronological execution timeline from all Prefetch files.
JSON report with execution history, suspicious executables, renamed binary indicators, and timeline reconstruction.
$ 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
development
拋棄式 HTML mockup 比稿:產出 2 到 3 個設計立場不同的變體(密度 / 版式 / 強調軸,不是換色),各附取捨說明,最後給有立場的對比結論。適用:「畫個草圖」「比較 A 版 B 版」「先看方向再做」「給我看幾種做法」。要 production 元件或設計已定案時不適用。
tools
需求不明時的意圖萃取訪談:一次一題、每題附上自己的猜測、聽出「真正想要 vs 覺得應該要」,直到能預測使用者反應(約 95% 信心)才動工。適用:需求缺少對象 / 動機 / 成功標準 / 約束,或使用者點名「訪談我」「先確認一下」「我們確定嗎」。明確自足的指示、純資訊查詢、機械性操作不適用。
development
對非平凡決策啟動新鮮 context 對抗審查(找碴不背書),在修正還便宜的時候抓出錯誤方向。適用:高風險改動(production、資安敏感邏輯、不可逆操作)、不熟的程式碼、要宣稱「這樣是安全的 / 可行的」之前。機械性操作與一行修改不適用。
testing
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