What it does. Extract, parse, and analyze Windows Event Logs (EVTX) using Chainsaw, Part of mukul975/Anthropic-Cybersecurity-Skills (817 security skills) (mukul975/Anthropic-Cybersecurity-Skills).

Install

• npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill extracting-windows-event-logs-artifacts, or copy the skill folder into ~/.claude/skills/extracting-windows-event-logs-artifacts/.
• Raw file: curl -sL https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/HEAD/skills/extracting-windows-event-logs-artifacts/SKILL.md

SKILL.md (verbatim)

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-03
- DE.AE-02
- RS.MA-01
mitre_attack:
- T1005
- T1074
- T1119
- T1070
- T1021

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

Tools & Systems

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

Other files in this skill

• LICENSE
• references/api-reference.md
• scripts/agent.py

references/api-reference.md (verbatim)

API Reference: Windows Event Log Artifact Extraction Agent

Dependencies

CLI Usage

python scripts/agent.py \
  --evtx-dir /cases/case-001/evtx/ \
  --output-dir /cases/case-001/analysis/ \
  --output evtx_report.json

# Or specify individual files:
python scripts/agent.py \
  --evtx-files Security.evtx System.evtx \
  --output-dir /cases/analysis/

Functions

parse_evtx_file(evtx_path) -> list

Parses a single EVTX file using PyEvtxParser. Returns list of dicts with event_id, timestamp, channel, computer, event_data.

filter_critical_events(records) -> dict

Filters records to 15 critical Event IDs (4624, 4625, 4688, 4697, 1102, etc.) grouped by Event ID.

detect_lateral_movement(records) -> list

Identifies network logons (Type 3) and RDP (Type 10) from non-local IPs. Flags pass-the-hash indicators (Type 9 + NTLM).

detect_privilege_escalation(records) -> list

Detects special privilege assignment (4672), group membership changes (4728/4732/4756), and account creation (4720).

detect_suspicious_processes(records) -> list

Matches 4688 process creation events against a list of known attack tools (mimikatz, psexec, rubeus, etc.).

detect_log_clearing(records) -> list

Identifies audit log clearing events (Event ID 1102 and 104).

detect_persistence(records) -> list

Detects service installations (4697/7045) and scheduled task creation (4698).

generate_summary(records, findings) -> dict

Computes statistics: total records, top event IDs, alert counts per detection category.

export_timeline_csv(records, output_path)

Exports critical events as a sorted CSV timeline with timestamp, event_id, description, details.

analyze_evtx(evtx_paths, output_dir) -> dict

Orchestrates parsing of multiple EVTX files and runs all detection functions.

Critical Event IDs

Output Schema

{
  "files_analyzed": ["/cases/evtx/Security.evtx"],
  "summary": {
    "total_records": 245678,
    "lateral_movement_alerts": 12,
    "suspicious_processes": 3,
    "persistence": 5
  },
  "findings": {
    "lateral_movement": [{"user": "admin", "source_ip": "10.0.0.5", "logon_type": "Network"}],
    "suspicious_processes": [{"matched_pattern": "mimikatz", "process": "m.exe"}]
  }
}

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