analyzing-windows-prefetch-with-python

# 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 `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. ## Example Output ```text $ 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 ```