Parse Windows LNK shortcut files to extract target paths, timestamps, volume information, and machine identifiers for forensic timeline reconstruction.
Parse Windows LNK shortcut files to extract target paths, timestamps, volume information, and machine identifiers for forensic timeline reconstruction.
Vendored verbatim from an external Apache-2.0 security-skill library, pinned by commit. Exceeds the internal 300-line skill guideline (agent-code-constraints.md) -- kept as-is because this is vendored reference material (forensics/threat-intel procedure), not Yana AI-authored content, and trimming would damage technical accuracy.
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
# 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 summaryprint(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 persistenceecho"=== 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
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
Tools & Systems
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
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.
