Parse Windows LNK shortcut files to extract target paths, timestamps, volume information, and machine identifiers for forensic timeline reconstruction.
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| name | analyzing-windows-lnk-files-for-artifacts |
| description | Parse Windows LNK shortcut files to extract target paths, timestamps, volume information, and machine identifiers for forensic timeline reconstruction. |
| 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-01 - RS.AN-03 - DE.AE-02 - RS.MA-01 |
# 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
# 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
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
# 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
| Concept | Description |
|---|---|
| Shell Link (.lnk) | Windows shortcut file format containing target path, timestamps, and metadata |
| Target timestamps | Creation, modification, and access times of the file the shortcut points to |
| Volume serial number | Unique identifier of the drive volume where the target file resides |
| Machine ID | NetBIOS name embedded by the Distributed Link Tracking service |
| MAC address | Network adapter MAC from the machine that created the LNK file |
| Jump Lists | Recent and pinned file lists per application (contain embedded LNK data) |
| Automatic Destinations | System-managed Jump List entries for recently opened files |
| Custom Destinations | User-pinned Jump List items that persist until manually removed |
| Tool | Purpose |
|---|---|
| LECmd | Eric Zimmerman command-line LNK file parser with CSV/JSON output |
| JLECmd | Eric Zimmerman Jump List parser |
| LnkParse3 | Python library for programmatic LNK file analysis |
| lnk_parser | Alternative Python LNK parsing tool |
| Autopsy | Forensic platform with LNK file analysis module |
| KAPE | Automated LNK and Jump List artifact collection |
| Plaso | Timeline tool with LNK file parser for super-timeline creation |
| LNK Explorer | GUI tool for interactive LNK file examination |
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.
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
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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analyzing-windows-lnk-files-for-artifacts fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for analyzing-windows-lnk-files-for-artifacts matched our evaluation — installs cleanly and behaves as described in the markdown.
We added analyzing-windows-lnk-files-for-artifacts from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
analyzing-windows-lnk-files-for-artifacts reduced setup friction for our internal harness; good balance of opinion and flexibility.
Keeps context tight: analyzing-windows-lnk-files-for-artifacts is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend analyzing-windows-lnk-files-for-artifacts for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: analyzing-windows-lnk-files-for-artifacts is focused, and the summary matches what you get after install.
analyzing-windows-lnk-files-for-artifacts is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added analyzing-windows-lnk-files-for-artifacts from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
analyzing-windows-lnk-files-for-artifacts fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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