/analyzing-windows-lnk-files-for-artifacts
Parse Windows LNK shortcut files to extract target paths, MAC timestamps,
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/analyzing-windows-lnk-files-for-artifacts
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Parse Windows LNK shortcut files to extract target paths, MAC timestamps,
SKILL.md
analyzing-windows-lnk-files-for-artifacts.SKILL.mdname: analyzing-windows-lnk-files-for-artifacts
description: Parse Windows LNK shortcut files to extract target paths, MAC timestamps,
volume serial numbers, and machine identifiers for forensic timeline reconstruction.
Use when investigating recently-accessed files, tracking removable media or network
paths referenced by shortcuts, or building a DFIR timeline from LNK artifacts.
domain: cybersecurity
subdomain: digital-forensics
tags:
- forensics
- lnk-files
- windows-artifacts
- shortcut-analysis
- timeline-reconstruction
- evidence-collection
version: '1.0'
author: mahipal
license: Apache-2.0
nist_csf:
- RS.AN-03
- DE.AE-02
- RS.MA-01
mitre_attack:
- T1547.001
- T1204.002
- T1005
- T1025
- T1074.001
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/nullStep 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 dataRead more
name: analyzing-windows-lnk-files-for-artifacts description: Parse Windows LNK shortcut files to extract target paths, MAC timestamps, volume serial numbers, and machine identifiers for forensic timeline reconstruction. Use when investigating recently-accessed files, tracking removable media or network paths referenced by shortcuts, or building a DFIR timeline from LNK artifacts. domain: cybersecurity subdomain: digital-forensics tags: - forensics - lnk-files - windows-artifacts - shortcut-analysis - timeline-reconstruction - evidence-collection version: '1.0' author: mahipal license: Apache-2.0 nist_csf: - RS.AN-03 - DE.AE-02 - RS.MA-01 mitre_attack: - T1547.001 - T1204.002 - T1005 - T1025 - T1074.001
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/nullStep 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 data817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains · Apache 2.0
Repo: mukul975/Anthropic-Cybersecurity-Skills
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