Agent skill

Extracting Windows Event Logs Artifacts

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

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

Apache-2.0Auto-check passedSecurity

Install Extracting Windows Event Logs Artifacts

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill extracting-windows-event-logs-artifacts -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills extracting-windows-event-logs-artifacts --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/extracting-windows-event-logs-artifacts .claude/skills/extracting-windows-event-logs-artifacts && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
extracting-windows-event-logs-artifacts
GitHub stars
34k
Token cost
~3.3k tokens
SKILL.md length
467 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

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

  • Works in 5 steps: Collect Windows Event Log Files → Run Chainsaw for Sigma-Based Detection → Run Hayabusa for Fast Timeline Generation → …
  • Tasks that involve Red teaming and adversary simulation
  • SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder; calls python3, wget and pip; reaches github.com

What it does

Extracting Windows Event Logs Artifacts is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Extract, parse, and analyze Windows Event Logs (EVTX) using Chainsaw, Hayabusa, and EvtxECmd to detect lateral movement, persistence, and privilege escalation.

Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).

It sits in Security, covering Red teaming and adversary simulation. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Red teaming and adversary simulation

Example prompts

  • “/extracting-windows-event-logs-artifacts”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Collect Windows Event Log Files
  2. Run Chainsaw for Sigma-Based Detection
  3. Run Hayabusa for Fast Timeline Generation
  4. Parse Specific Critical Event IDs
  5. Detect Specific Attack Patterns

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3
    • wget
    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Extracting Windows Event Logs Artifacts loads about 3.3k tokens when it runs, and up to ~4k if it reads all its reference files. Until then it costs about 50 tokens; SKILL.md has 467 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~50
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 467 words, ~3,265 tokens.

Download SKILL.mdSave it as .claude/skills/extracting-windows-event-logs-artifacts/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
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
bash
# 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
bash
# 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
bash
# 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
bash
# 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
bash
# 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
Show full SKILL.md (167 more words)Show less

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

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/extracting-windows-event-logs-artifacts of mukul975/Anthropic-Cybersecurity-Skills.

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

Open the folder on GitHubat commit 54a7988

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Categories

Questions about Extracting Windows Event Logs Artifacts

What does Extracting Windows Event Logs Artifacts do?

Extract, parse, and analyze Windows Event Logs (EVTX) using Chainsaw, Hayabusa, and EvtxECmd to detect lateral movement, persistence, and privilege escalation. Extracting Windows Event Logs Artifacts is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Extract, parse, and analyze Windows Event Logs (EVTX) using Chainsaw, Hayabusa, and EvtxECmd to detect lateral movement, persistence, and privilege escalation.

When should I use Extracting Windows Event Logs Artifacts?

Extracting Windows Event Logs Artifacts fits situations like: tasks that involve Red teaming and adversary simulation.

How do I install Extracting Windows Event Logs Artifacts in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill extracting-windows-event-logs-artifacts -a claude-code`. Or copy the skill folder (skills/extracting-windows-event-logs-artifacts in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/extracting-windows-event-logs-artifacts in your project. Claude Code loads it when a task matches its description.

How do I install Extracting Windows Event Logs Artifacts in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill extracting-windows-event-logs-artifacts -a codex`. Or copy the skill folder (skills/extracting-windows-event-logs-artifacts in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/extracting-windows-event-logs-artifacts in your project. Codex loads it when a task matches its description.

Can I use Extracting Windows Event Logs Artifacts in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill extracting-windows-event-logs-artifacts -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/extracting-windows-event-logs-artifacts, .gemini/skills/extracting-windows-event-logs-artifacts, .github/skills/extracting-windows-event-logs-artifacts and .opencode/skills/extracting-windows-event-logs-artifacts in your project.

What does Extracting Windows Event Logs Artifacts need to run?

Going by SKILL.md and its folder, Extracting Windows Event Logs Artifacts needs Python for the scripts in its folder and the command-line tools its instructions call (python3, wget and pip). Our summary lists: Python 3.

Does Extracting Windows Event Logs Artifacts access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Extracting Windows Event Logs Artifacts safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Extracting Windows Event Logs Artifacts use?

Extracting Windows Event Logs Artifacts is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Extracting Windows Event Logs Artifacts use?

About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 705 tokens, read only when the agent opens those files.

What are the alternatives to Extracting Windows Event Logs Artifacts?

Skills that share tags, products or a category with Extracting Windows Event Logs Artifacts: Authorization Bypass Detection (Tencent/AI-Infra-Guard, 6.8k stars), Run Assert Eval (responsibleai/ASSERT, 330 stars), Osint Methodology (elementalsouls/Claude-OSINT, 2.8k stars) and Lfd Design (elvisun/loss-function-development, 176 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Extracting Windows Event Logs Artifacts?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.