analyzing-windows-lnk-files-for-artifacts

Imported from mukul975/anthropic-cybersecurity-skills (skills/analyzing-windows-lnk-files-for-artifacts/SKILL.md). Install upstream with npx skills add mukul975/anthropic-cybersecurity-skills --skill analyzing-windows-lnk-files-for-artifacts. Copyright stays with the author (Apache-2.0).

Analyzing Windows LNK Files for Artifacts

When to Use

• When reconstructing user file access history from Windows shortcut files
• For tracking accessed files, network shares, and removable media
• During investigations to prove a user opened specific documents
• When correlating file access with other timeline artifacts
• For identifying accessed paths on remote systems or USB devices

Prerequisites

• Access to LNK files from forensic image (Recent, Desktop, Quick Launch)
• LECmd (Eric Zimmerman), python-lnk, or LnkParser for analysis
• Understanding of LNK file structure (Shell Link Binary format)
• Knowledge of LNK file locations on Windows systems
• Forensic workstation with analysis tools installed

Workflow

Step 1: Collect LNK Files from Forensic Image

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

mkdir -p /cases/case-2024-001/lnk/{recent,desktop,startup,custom}

# Copy Recent items LNK files (primary source)
cp /mnt/evidence/Users/*/AppData/Roaming/Microsoft/Windows/Recent/*.lnk \
   /cases/case-2024-001/lnk/recent/ 2>/dev/null

# Copy automatic destinations (Jump Lists)
cp /mnt/evidence/Users/*/AppData/Roaming/Microsoft/Windows/Recent/AutomaticDestinations/*.automaticDestinations-ms \
   /cases/case-2024-001/lnk/recent/ 2>/dev/null

# Copy custom destinations (pinned Jump List items)
cp /mnt/evidence/Users/*/AppData/Roaming/Microsoft/Windows/Recent/CustomDestinations/*.customDestinations-ms \
   /cases/case-2024-001/lnk/custom/ 2>/dev/null

# Copy Desktop shortcuts
cp /mnt/evidence/Users/*/Desktop/*.lnk /cases/case-2024-001/lnk/desktop/ 2>/dev/null

# Copy Startup folder shortcuts (persistence)
cp /mnt/evidence/Users/*/AppData/Roaming/Microsoft/Windows/Start\ Menu/Programs/Startup/*.lnk \
   /cases/case-2024-001/lnk/startup/ 2>/dev/null
cp "/mnt/evidence/ProgramData/Microsoft/Windows/Start Menu/Programs/Startup"/*.lnk \
   /cases/case-2024-001/lnk/startup/ 2>/dev/null

# Find all LNK files on the system
find /mnt/evidence/ -name "*.lnk" -type f 2>/dev/null > /cases/case-2024-001/lnk/all_lnk_locations.txt

# Count and hash
ls /cases/case-2024-001/lnk/recent/ | wc -l
sha256sum /cases/case-2024-001/lnk/recent/*.lnk > /cases/case-2024-001/lnk/lnk_hashes.txt 2>/dev/null

Step 2: Parse LNK Files with LECmd

# Using Eric Zimmerman's LECmd (Windows or via Mono)
# Process all LNK files in a directory
LECmd.exe -d "C:\cases\lnk\recent\" --csv "C:\cases\analysis\" --csvf lnk_analysis.csv

# Process a single LNK file with verbose output
LECmd.exe -f "C:\cases\lnk\recent\document.pdf.lnk"

# Process Jump List files
JLECmd.exe -d "C:\cases\lnk\recent\" --csv "C:\cases\analysis\" --csvf jumplist_analysis.csv

# Output includes:
# - Source file path
# - Target path (file that was accessed)
# - Target creation, modification, access timestamps
# - LNK creation and modification timestamps
# - Working directory
# - Command line arguments
# - Volume serial number and label
# - Drive type (Fixed, Removable, Network)
# - Machine ID (NetBIOS name)
# - MAC address (from tracker database)
# - File size of target

Step 3: Parse LNK Files with Python

pip install LnkParse3

python3 << 'PYEOF'
import LnkParse3
import os, json, csv
from datetime import datetime

lnk_dir = '/cases/case-2024-001/lnk/recent/'
results = []

for filename in sorted(os.listdir(lnk_dir)):
    if not filename.lower().endswith('.lnk'):
        continue

    filepath = os.path.join(lnk_dir, filename)
    try:
        with open(filepath, 'rb') as f:
            lnk = LnkParse3.lnk_file(f)
            info = lnk.get_json()

            parsed = {
                'lnk_file': filename,
                'target_path': '',
                'working_dir': '',
                'arguments': '',
                'target_created': '',
                'target_modified': '',
                'target_accessed': '',
                'file_size': '',
                'drive_type': '',
                'volume_serial': '',
                'volume_label': '',
                'machine_id': '',
                'mac_address': '',
            }

            # Extract header timestamps
            header = info.get('header', {})
            parsed['target_created'] = str(header.get('creation_time', ''))
            parsed['target_modified'] = str(header.get('modified_time', ''))
            parsed['target_accessed'] = str(header.get('accessed_time', ''))
            parsed['file_size'] = str(header.get('file_size', ''))

            # Extract link info
            link_info = info.get('link_info', {})
            if link_info:
                local_path = link_info.get('local_base_path', '')
                network_path = link_info.get('common_network_relative_link', {}).get('net_name', '')
                parsed['target_path'] = local_path or network_path

                vol_info = link_info.get('volume_id', {})
                if vol_info:
                    parsed['drive_type'] = str(vol_info.get('drive_type', ''))
                    parsed['volume_serial'] = str(vol_info.get('drive_serial_number', ''))
                    parsed['volume_label'] = str(vol_info.get('volume_label', ''))

            # Extract string data
            string_data = info.get('string_data', {})
            parsed['working_dir'] = str(string_data.get('working_dir', ''))
            parsed['arguments'] = str(string_data.get('command_line_arguments', ''))

            # Extract tracker data (machine ID and MAC)
            extra = info.get('extra', {})
            tracker = extra.get('DISTRIBUTED_LINK_TRACKER_BLOCK', {})
            if tracker:
                parsed['machine_id'] = str(tracker.get('machine_id', ''))
                parsed['mac_address'] = str(tracker.get('mac_address', ''))

            results.append(parsed)

            # Print summary
            print(f"\n{filename}")
            print(f"  Target: {parsed['target_path']}")
            print(f"  Modified: {parsed['target_modified']}")
            print(f"  Drive: {parsed['drive_type']} (Serial: {parsed['volume_serial']})")
            if parsed['machine_id']:
                print(f"  Machine: {parsed['machine_id']}")

    except Exception as e:
        print(f"  Error parsing {filename}: {e}")

# Write results to CSV
with open('/cases/case-2024-001/analysis/lnk_analysis.csv', 'w', newline='') as f:
    writer = csv.DictWriter(f, fieldnames=results[0].keys() if results else [])
    writer.writeheader()
    writer.writerows(results)

print(f"\n\nTotal LNK files parsed: {len(results)}")
PYEOF

Step 4: Analyze for Investigative Value

# Identify files accessed from removable media
python3 << 'PYEOF'
import csv

with open('/cases/case-2024-001/analysis/lnk_analysis.csv') as f:
    reader = csv.DictReader(f)

    print("=== FILES ACCESSED FROM REMOVABLE MEDIA ===\n")
    removable = []
    network = []

    for row in reader:
        if 'DRIVE_REMOVABLE' in row.get('drive_type', '').upper() or \
           'removable' in row.get('drive_type', '').lower():
            removable.append(row)
            print(f"  {row['target_modified']} | {row['target_path']} | Vol: {row['volume_serial']}")

        if 'network' in row.get('drive_type', '').lower() or \
           row.get('target_path', '').startswith('\\\\'):
            network.append(row)

    print(f"\n=== FILES ACCESSED FROM NETWORK SHARES ===\n")
    for row in network:
        print(f"  {row['target_modified']} | {row['target_path']}")

    print(f"\nRemovable media files: {len(removable)}")
    print(f"Network share files: {len(network)}")

    # Check for unique machines (tracker data)
    machines = set()
    for row in [*removable, *network]:
        if row.get('machine_id'):
            machines.add(row['machine_id'])
    if machines:
        print(f"\nMachine IDs found: {machines}")
PYEOF

# Check Startup folder LNK files for persistence
echo "=== STARTUP FOLDER SHORTCUTS (PERSISTENCE) ===" > /cases/case-2024-001/analysis/startup_persistence.txt
for lnk in /cases/case-2024-001/lnk/startup/*.lnk; do
    python3 -c "
import LnkParse3
with open('$lnk', 'rb') as f:
    lnk = LnkParse3.lnk_file(f)
    info = lnk.get_json()
    target = info.get('link_info', {}).get('local_base_path', 'Unknown')
    args = info.get('string_data', {}).get('command_line_arguments', '')
    print(f'  $(basename $lnk): {target} {args}')
" >> /cases/case-2024-001/analysis/startup_persistence.txt 2>/dev/null
done

Key Concepts

Tools & Systems

Common Scenarios

Scenario 1: Data Exfiltration via USB Drive Analyze Recent folder LNK files for targets on removable drives, correlate volume serial numbers with USBSTOR registry entries, build a list of files accessed from USB devices, establish which documents were opened from the removable drive, correlate with file copy timestamps.

Scenario 2: Malware Persistence via Startup Shortcuts Examine Startup folder LNK files for malicious targets, check target path and arguments for encoded commands or suspicious executables, verify target file exists and examine it, correlate creation timestamp with initial compromise time.

Scenario 3: Network Share Access Investigation Filter LNK files with network paths (UNC targets), identify which network shares were accessed and when, correlate machine IDs with known corporate systems, check if sensitive file servers were accessed outside of normal duties, build access timeline for compliance investigation.

Scenario 4: Document Access Timeline for Legal Proceedings Extract all Recent folder LNK files, build chronological list of documents accessed by the user, identify specific files relevant to the case, present target timestamps showing when files were opened, correlate with email and communication timelines.

Output Format

LNK File Analysis Summary:
  User Profile: suspect_user
  Total LNK Files: 234 (Recent: 198, Desktop: 23, Startup: 5, Other: 8)

  File Access Statistics:
    Local drive (C:):    156 files
    Removable media:     23 files (3 unique volume serials)
    Network shares:      15 files (\\server01, \\fileserver)
    Other drives:        4 files

  Machine IDs Found: DESKTOP-ABC123, LAPTOP-XYZ789
  MAC Addresses: AA:BB:CC:DD:EE:FF, 11:22:33:44:55:66

  Removable Media Access:
    Volume Serial 1234-ABCD:
      2024-01-15 14:32 - E:\Confidential\financial_report.xlsx
      2024-01-15 14:45 - E:\Confidential\customer_database.csv
      2024-01-15 15:00 - E:\Projects\source_code.zip

  Startup Persistence:
    updater.lnk -> C:\ProgramData\svc\updater.exe (SUSPICIOUS)
    OneDrive.lnk -> C:\Users\...\OneDrive.exe (Legitimate)

  Timeline: /cases/case-2024-001/analysis/lnk_analysis.csv