extracting-windows-event-logs-artifacts

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/extracting-windows-event-logs-artifacts
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summary

Extract, parse, and analyze Windows Event Logs (EVTX) using Chainsaw, Hayabusa, and EvtxECmd to detect lateral movement, persistence, and privilege escalation.

skill.md
name
extracting-windows-event-logs-artifacts
description
Extract, parse, and analyze Windows Event Logs (EVTX) using Chainsaw, Hayabusa, and EvtxECmd to detect lateral movement, persistence, and privilege escalation.
domain
cybersecurity
subdomain
digital-forensics
tags
- forensics - windows-event-logs - evtx - chainsaw - hayabusa - sigma-rules - incident-response
version
'1.0'
author
mahipal
license
Apache-2.0
nist_csf
- RS.AN-01 - RS.AN-03 - DE.AE-02 - RS.MA-01

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

ConceptDescription
EVTX formatBinary XML-based Windows Event Log format introduced in Vista/Server 2008
Event IDNumeric identifier for specific event types (e.g., 4624 = successful logon)
Logon typesClassification of authentication methods (2=interactive, 3=network, 10=RDP)
Sigma rulesGeneric detection signatures that map to specific SIEM/log queries
SysmonMicrosoft system monitoring driver providing detailed process and network events
Audit policyGPO settings controlling which events Windows records
Event forwarding (WEF)Windows mechanism for centralized event log collection
EVTX channelsSeparate log files for different event categories and applications

Tools & Systems

ToolPurpose
ChainsawSigma-based EVTX analysis and threat hunting tool
HayabusaFast Windows Event Log forensic timeline generator
EvtxECmdEric Zimmerman command-line EVTX parser with CSV/JSON output
python-evtxPython library for EVTX file parsing
LogParserMicrosoft SQL-like query engine for Windows logs
Event Log ExplorerGUI tool for browsing and analyzing EVTX files
KAPEAutomated triage collection including event logs
VelociraptorEndpoint 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
how to use extracting-windows-event-logs-artifacts

How to use extracting-windows-event-logs-artifacts on Cursor

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1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add extracting-windows-event-logs-artifacts
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/extracting-windows-event-logs-artifacts

The skills CLI fetches extracting-windows-event-logs-artifacts from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

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Verify installation

Confirm successful installation by checking the skill directory location:

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Reload or restart Cursor to activate extracting-windows-event-logs-artifacts. Access the skill through slash commands (e.g., /extracting-windows-event-logs-artifacts) or your agent's skill management interface.

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Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ 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.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

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Ratings

4.774 reviews
  • Naina Robinson· Dec 28, 2024

    extracting-windows-event-logs-artifacts has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Naina Martinez· Dec 24, 2024

    extracting-windows-event-logs-artifacts reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Naina Verma· Dec 24, 2024

    Useful defaults in extracting-windows-event-logs-artifacts — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Michael Patel· Dec 20, 2024

    Registry listing for extracting-windows-event-logs-artifacts matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Soo Kapoor· Dec 12, 2024

    Solid pick for teams standardizing on skills: extracting-windows-event-logs-artifacts is focused, and the summary matches what you get after install.

  • Fatima Thomas· Dec 4, 2024

    extracting-windows-event-logs-artifacts is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Aditi Shah· Dec 4, 2024

    extracting-windows-event-logs-artifacts fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Evelyn Malhotra· Nov 23, 2024

    extracting-windows-event-logs-artifacts fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Hana Smith· Nov 23, 2024

    extracting-windows-event-logs-artifacts is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Hana Huang· Nov 23, 2024

    extracting-windows-event-logs-artifacts has been reliable in day-to-day use. Documentation quality is above average for community skills.

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