Analyzing Windows Prefetch With PythonSAFE

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The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
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 `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
```

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

Filesystem

none-observed

Network

declared (1 observation(s))

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (1)

"rubeus", "sharphound", "bloodhound", "cobalt", "beacon",

Gates applied: no_behavioural_pass.