analyzing-prefetch-files-for-execution-history

Files (4)

• LICENSE
• SKILL.md
• api-reference.md · references/
• agent.py · scripts/

SKILL.md (first lines)

# Analyzing Prefetch Files for Execution History

## When to Use
- When determining which programs were executed on a Windows system and when
- During malware investigations to confirm execution of suspicious binaries
- For establishing a timeline of application usage during an incident
- When correlating program execution with other forensic artifacts
- To identify anti-forensic tools or unauthorized software that was run

## Prerequisites
- Access to Windows Prefetch directory (C:\Windows\Prefetch\) from forensic image
- PECmd (Eric Zimmerman), WinPrefetchView, or python-prefetch parser
- Understanding of Prefetch file format (versions 17, 23, 26, 30)
- Windows system with Prefetch enabled (default on client OS, disabled on servers)
- Knowledge of Prefetch naming conventions (APPNAME-HASH.pf)

## Workflow

### Step 1: Extract Prefetch Files from Forensic Image

```bash
# Mount the forensic image
mount -o ro,loop,offset=$((2048*512)) /cases/case-2024-001/images/evidence.dd /mnt/evidence

# Copy all prefetch files
mkdir -p /cases/case-2024-001/prefetch/
cp /mnt/evidence/Windows/Prefetch/*.pf /cases/case-2024-001/prefetch/

# Count and list prefetch files
ls -la /cases/case-2024-001/prefetch/ | wc -l
ls -la /cases/case-2024-001/prefetch/ | head -30

# Hash all prefetch files for integrity
sha256sum /cases/case-2024-001/prefetch/*.pf > /cases/case-2024-001/prefetch/pf_hashes.txt

# Note: Prefetch filename format is EXECUTABLE_NAME-XXXXXXXX.pf
# The hash (XXXXXXXX) is based on the executable path
# Same executable from different paths creates different prefetch files
```

### Step 2: Parse Prefetch Files with PECmd

```bash
# Using Eric Zimmerman's PECmd (Windows or via Mono/Wine on Linux)
# Download from https://ericzimmerman.github.io/

# Parse a single prefetch file
PECmd.exe -f "C:\cases\prefetch\POWERSHELL.EXE-A]B2C3D4.pf"

# Parse all prefetch files and output to CSV
PECmd.exe -d "C:\cases\prefetch\" --csv "C:\cases\analysis\" --csvf prefetch_results.csv

# Parse with JSON output
PECmd.exe -d "C:\cases\prefetch\" --json "C:\cases\analysis\" --jsonf prefetch_results.json

# Output includes for each file:
# - Executable name and path
# - Run count
# - Last run time (up to 8 timestamps in Windows 10)
# - Files and directories referenced during execution
# - Volume information (serial number, creation date)
# - Prefetch file creation time
```

### Step 3: Parse with Python for Linux-Based Analysis

```bash
pip install prefetch

python3 << 'PYEOF'
import os
import json
from datetime import datetime

# Parse prefetch files using python
import struct

def parse_prefetch(filepath):
    """Parse a Windows Prefetch file."""
    with open(filepath, 'rb') as f:
        data = f.read()

    # Check for MAM compressed format (Windows 10)
    if data[:4] == b'MAM\x04':
        import lznt1  # or use DecompressBuffer
        # Windows 10 prefetch files are compressed
        print(f"  [Compressed Win10 format - use PECmd for full parsing]")
        return None

    # Version 17 (XP), 23 (Vista/7), 26 (8.1), 30 (10)
    version = struct.unpack('<I', data[0:4])[0]
    signature = data[4:8]

    if signature != b'SCCA':
        print(f"  Invalid prefetch signature")
        return None

    file_size = struct.unpack('<I', data[8:12])[0]
    exec_name = data[16:76].decode('utf-16-le').strip('\x00')
    run_count = struct.unpack('<I', data[208:212])[0] if version >= 23 else struct.unpack('<I', data[144:148])[0]

    result = {
        'version': version,
        'executable': exec_name,
        'file_size': file_size,
        'run_count': run_count,
    }

    # Extract last execution timestamps
    if version == 23:  # Vista/7 - 1 timestamp
        ts = struct.unpack('<Q', data[128:136])[0]
        result['last_run'] = filetime_to_datetime(ts)
    elif version >= 26:  # Win8+ - up to 8 timestamps
        timestamps = []
        for i in range(8):
            ts = struct.unpack('<Q', data[128+i*8:136+i*8])[0]
            if ts > 0:
                timestamps.append(filetime_to_datetime(ts))
        result['last_run_times'] = timestamps

From mukul975/Anthropic-Cybersecurity-Skills, Apache-2.0.

More from mukul975/Anthropic-Cybersecurity-Skills