Extracting Windows Event Logs Artifacts

When to Use

• When investigating security incidents on Windows systems through event log analysis
• For detecting lateral movement, privilege escalation, and persistence mechanisms
• When performing threat hunting across Windows event log data
• During compliance audits requiring review of authentication and access events
• When building forensic timelines from Windows system activity

Prerequisites

• Windows Event Log files (EVTX format) from forensic image or live system
• Chainsaw, Hayabusa, or EvtxECmd for parsing and detection
• Sigma rules for automated threat detection
• Understanding of critical Windows Event IDs
• Python with python-evtx or evtx library for custom parsing
• PowerShell for live system analysis (if applicable)

Workflow

Step 1: Collect Windows Event Log Files

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

mkdir -p /cases/case-2024-001/evtx/
cp /mnt/evidence/Windows/System32/winevt/Logs/*.evtx /cases/case-2024-001/evtx/

# Key event logs to prioritize
# Security.evtx - Authentication, authorization, audit events
# System.evtx - System services, drivers, hardware events
# Application.evtx - Application errors and events
# Microsoft-Windows-Sysmon%4Operational.evtx - Detailed process/network monitoring
# Microsoft-Windows-PowerShell%4Operational.evtx - PowerShell activity
# Microsoft-Windows-TerminalServices-LocalSessionManager%4Operational.evtx - RDP sessions
# Microsoft-Windows-TaskScheduler%4Operational.evtx - Scheduled tasks
# Microsoft-Windows-WinRM%4Operational.evtx - Windows Remote Management
# Microsoft-Windows-Bits-Client%4Operational.evtx - BITS transfers
# Microsoft-Windows-Windows Defender%4Operational.evtx - AV detections

# List available log files and sizes
ls -lhS /cases/case-2024-001/evtx/ | head -20

# Hash for integrity
sha256sum /cases/case-2024-001/evtx/*.evtx > /cases/case-2024-001/evtx/evtx_hashes.txt

Step 2: Run Chainsaw for Sigma-Based Detection

# Install Chainsaw
wget https://github.com/WithSecureLabs/chainsaw/releases/latest/download/chainsaw_all_platforms+rules.zip
unzip chainsaw_all_platforms+rules.zip -d /opt/chainsaw

# Run Chainsaw with bundled Sigma rules
/opt/chainsaw/chainsaw hunt /cases/case-2024-001/evtx/ \
   -s /opt/chainsaw/sigma/rules/ \
   --mapping /opt/chainsaw/mappings/sigma-event-logs-all.yml \
   --output /cases/case-2024-001/analysis/chainsaw_results.txt

# Run with CSV output for easier analysis
/opt/chainsaw/chainsaw hunt /cases/case-2024-001/evtx/ \
   -s /opt/chainsaw/sigma/rules/ \
   --mapping /opt/chainsaw/mappings/sigma-event-logs-all.yml \
   --csv \
   --output /cases/case-2024-001/analysis/chainsaw_results/

# Run with JSON output
/opt/chainsaw/chainsaw hunt /cases/case-2024-001/evtx/ \
   -s /opt/chainsaw/sigma/rules/ \
   --mapping /opt/chainsaw/mappings/sigma-event-logs-all.yml \
   --json \
   --output /cases/case-2024-001/analysis/chainsaw_results.json

# Search for specific keywords
/opt/chainsaw/chainsaw search /cases/case-2024-001/evtx/ \
   -s "mimikatz" --json

# Search for specific event IDs
/opt/chainsaw/chainsaw search /cases/case-2024-001/evtx/ \
   -e 4688 --json | head -100

Step 3: Run Hayabusa for Fast Timeline Generation

# Install Hayabusa
wget https://github.com/Yamato-Security/hayabusa/releases/latest/download/hayabusa-linux-x64-musl.zip
unzip hayabusa-linux-x64-musl.zip -d /opt/hayabusa

# Generate CSV timeline with all detection rules
/opt/hayabusa/hayabusa csv-timeline \
   -d /cases/case-2024-001/evtx/ \
   -o /cases/case-2024-001/analysis/hayabusa_timeline.csv \
   -p verbose

# Generate JSON timeline
/opt/hayabusa/hayabusa json-timeline \
   -d /cases/case-2024-001/evtx/ \
   -o /cases/case-2024-001/analysis/hayabusa_timeline.json

# Run with only critical and high severity detections
/opt/hayabusa/hayabusa csv-timeline \
   -d /cases/case-2024-001/evtx/ \
   -o /cases/case-2024-001/analysis/hayabusa_critical.csv \
   -p verbose \
   --min-level critical

# Generate detection summary (metrics)
/opt/hayabusa/hayabusa metrics \
   -d /cases/case-2024-001/evtx/ \
   -o /cases/case-2024-001/analysis/hayabusa_metrics.csv

# Logon summary
/opt/hayabusa/hayabusa logon-summary \
   -d /cases/case-2024-001/evtx/ \
   -o /cases/case-2024-001/analysis/logon_summary.csv

Step 4: Parse Specific Critical Event IDs

# Extract authentication events with python-evtx
pip install evtx

python3 << 'PYEOF'
import json
from evtx import PyEvtxParser

parser = PyEvtxParser("/cases/case-2024-001/evtx/Security.evtx")

# Critical Event IDs mapping
critical_events = {
    '4624': 'Successful Logon',
    '4625': 'Failed Logon',
    '4634': 'Logoff',
    '4648': 'Explicit Credential Logon',
    '4672': 'Special Privileges Assigned',
    '4688': 'Process Created',
    '4689': 'Process Exited',
    '4697': 'Service Installed',
    '4698': 'Scheduled Task Created',
    '4720': 'User Account Created',
    '4724': 'Password Reset Attempted',
    '4728': 'Member Added to Global Group',
    '4732': 'Member Added to Local Group',
    '4756': 'Member Added to Universal Group',
    '1102': 'Audit Log Cleared',
    '4688': 'New Process Created'
}

results = {eid: [] for eid in critical_events}

for record in parser.records_json():
    data = json.loads(record['data'])
    event_id = str(data['Event']['System']['EventID'])

    if event_id in critical_events:
        event_data = data['Event'].get('EventData', {})
        results[event_id].append({
            'timestamp': data['Event']['System']['TimeCreated']['#attributes']['SystemTime'],
            'event_id': event_id,
            'description': critical_events[event_id],
            'data': event_data
        })

# Print summary
for eid, events in results.items():
    if events:
        print(f"\n[{eid}] {critical_events[eid]}: {len(events)} events")
        for e in events[:3]:
            print(f"  {e['timestamp']}: {json.dumps(e['data'], default=str)[:200]}")
        if len(events) > 3:
            print(f"  ... and {len(events)-3} more")

# Save full results
with open('/cases/case-2024-001/analysis/critical_events.json', 'w') as f:
    json.dump(results, f, indent=2, default=str)
PYEOF

Step 5: Detect Specific Attack Patterns

# Detect Pass-the-Hash (Logon Type 9 with NTLM)
python3 << 'PYEOF'
import json
from evtx import PyEvtxParser

parser = PyEvtxParser("/cases/case-2024-001/evtx/Security.evtx")

print("=== PASS-THE-HASH INDICATORS ===")
print("Looking for: Event 4624, Logon Type 9, NTLM authentication\n")

for record in parser.records_json():
    data = json.loads(record['data'])
    event_id = str(data['Event']['System']['EventID'])

    if event_id == '4624':
        event_data = data['Event'].get('EventData', {})
        logon_type = str(event_data.get('LogonType', ''))
        auth_package = str(event_data.get('AuthenticationPackageName', ''))
        logon_process = str(event_data.get('LogonProcessName', ''))

        # Pass-the-Hash indicators
        if logon_type == '9' and 'NTLM' in auth_package:
            timestamp = data['Event']['System']['TimeCreated']['#attributes']['SystemTime']
            target = event_data.get('TargetUserName', 'Unknown')
            source_ip = event_data.get('IpAddress', 'N/A')
            print(f"  [{timestamp}] PtH: User={target}, IP={source_ip}, Auth={auth_package}")

        # Network logon with NTLM (lateral movement)
        if logon_type == '3' and 'NTLM' in auth_package:
            timestamp = data['Event']['System']['TimeCreated']['#attributes']['SystemTime']
            target = event_data.get('TargetUserName', 'Unknown')
            source_ip = event_data.get('IpAddress', 'N/A')
            workstation = event_data.get('WorkstationName', 'N/A')
            print(f"  [{timestamp}] Network NTLM: User={target}, IP={source_ip}, WS={workstation}")
PYEOF

# Detect log clearing / anti-forensics
python3 << 'PYEOF'
import json
from evtx import PyEvtxParser

for log_file in ['Security.evtx', 'System.evtx']:
    path = f"/cases/case-2024-001/evtx/{log_file}"
    try:
        parser = PyEvtxParser(path)
        for record in parser.records_json():
            data = json.loads(record['data'])
            event_id = str(data['Event']['System']['EventID'])
            if event_id in ('1102', '104'):  # Security log cleared, System log cleared
                timestamp = data['Event']['System']['TimeCreated']['#attributes']['SystemTime']
                print(f"LOG CLEARED: [{timestamp}] EventID {event_id} in {log_file}")
    except Exception as e:
        print(f"Error parsing {log_file}: {e}")
PYEOF

Key Concepts

Concept	Description
EVTX format	Binary XML-based Windows Event Log format introduced in Vista/Server 2008
Event ID	Numeric identifier for specific event types (e.g., 4624 = successful logon)
Logon types	Classification of authentication methods (2=interactive, 3=network, 10=RDP)
Sigma rules	Generic detection signatures that map to specific SIEM/log queries
Sysmon	Microsoft system monitoring driver providing detailed process and network events
Audit policy	GPO settings controlling which events Windows records
Event forwarding (WEF)	Windows mechanism for centralized event log collection
EVTX channels	Separate log files for different event categories and applications

Tools & Systems

Tool	Purpose
Chainsaw	Sigma-based EVTX analysis and threat hunting tool
Hayabusa	Fast Windows Event Log forensic timeline generator
EvtxECmd	Eric Zimmerman command-line EVTX parser with CSV/JSON output
python-evtx	Python library for EVTX file parsing
LogParser	Microsoft SQL-like query engine for Windows logs
Event Log Explorer	GUI tool for browsing and analyzing EVTX files
KAPE	Automated triage collection including event logs
Velociraptor	Endpoint agent with EVTX collection and hunting artifacts

Common Scenarios

Scenario 1: Detecting Lateral Movement

Filter for Event 4624 with Logon Type 3 (network) and Type 10 (RDP), identify unusual source-destination pairs, check for Event 4648 (explicit credentials) indicating pass-the-hash, correlate with process creation events (4688) on target systems.

Scenario 2: Privilege Escalation Detection

Search for Event 4672 (special privileges assigned) for unexpected users, check for Event 4728/4732 (group membership changes) adding users to admin groups, look for Event 4697 (service installed) indicating new system-level access, correlate with 4720 (account creation).

Scenario 3: PowerShell Attack Detection

Analyze PowerShell Operational log for Script Block Logging (Event 4104), search for encoded commands in Event 4688 (process creation with command line), detect AMSI bypass attempts, identify download cradles and invocation of known attack tools.

Scenario 4: Ransomware Incident Reconstruction

Build timeline starting from initial access (4624 from external IP), trace privilege escalation through group membership changes, identify service installations for persistence, find process creation events for encryption executable, detect volume shadow copy deletion in System log.

Output Format

Windows Event Log Analysis Summary:
  System: DC01.corp.local (Windows Server 2019)
  Log Files Analyzed: 15 EVTX files
  Total Events: 2,456,789
  Analysis Period: 2024-01-10 to 2024-01-20

  Chainsaw Detections:
    Critical:  12 (Mimikatz usage, PsExec, log clearing)
    High:      34 (Network NTLM logons, encoded PowerShell)
    Medium:    89 (Unusual service installations, scheduled tasks)
    Low:       234 (Informational)

  Hayabusa Timeline:
    Total Alerts: 369
    Unique Rules Triggered: 45
    Top Rules:
      - Suspicious NTLM Authentication (34 hits)
      - PowerShell Download Cradle (12 hits)
      - Service Installation Suspicious Path (8 hits)

  Critical Findings:
    2024-01-15 14:32 - RDP brute force (234 failed, 1 success from 203.0.113.45)
    2024-01-15 14:45 - Admin account created (svcbackup) - Event 4720
    2024-01-16 02:30 - PsExec service installed on DC01 - Event 4697
    2024-01-18 03:00 - Security log cleared - Event 1102

  Reports:
    Chainsaw: /analysis/chainsaw_results/
    Hayabusa: /analysis/hayabusa_timeline.csv
    Critical Events: /analysis/critical_events.json

Verification Criteria

Confirm successful execution by validating:

• [ ] All prerequisite tools and access requirements are satisfied
• [ ] Each workflow step completed without errors
• [ ] Output matches expected format and contains expected data
• [ ] No security warnings or misconfigurations detected
• [ ] Results are documented and evidence is preserved for audit

Compliance Framework Mapping

This skill supports compliance evidence collection across multiple frameworks:

• SOC 2: CC7.3 (Incident Identification), CC7.4 (Incident Response)
• ISO 27001: A.16.1 (Security Incident Management), A.12.4 (Logging)
• NIST 800-53: AU-6 (Audit Review), IR-4 (Incident Handling), AU-9 (Audit Protection)
• NIST CSF: RS.AN (Analysis), RS.RP (Response Planning)

Claw GRC Tip: When this skill is executed by a registered agent, compliance evidence is automatically captured and mapped to the relevant controls in your active frameworks.

Deploying This Skill with Claw GRC

Agent Execution

Register this skill with your Claw GRC agent for automated execution:

# Install via CLI
npx claw-grc skills add extracting-windows-event-logs-artifacts

# Or load dynamically via MCP
grc.load_skill("extracting-windows-event-logs-artifacts")

Audit Trail Integration

When executed through Claw GRC, every step of this skill generates tamper-evident audit records:

• SHA-256 chain hashing ensures no step can be modified after execution
• Evidence artifacts (configs, scan results, logs) are automatically attached to relevant controls
• Trust score impact — successful execution increases your agent's trust score

Continuous Compliance

Schedule this skill for recurring execution to maintain continuous compliance posture. Claw GRC monitors for drift and alerts when re-execution is needed.