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implementing-endpoint-detection-with-wazuh

implementing-endpoint-detection-with-wazuh▌

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

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-endpoint-detection-with-wazuh
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summary

Deploy and configure Wazuh SIEM/XDR for endpoint detection including agent management, custom decoder and rule XML creation, alert querying via the Wazuh REST API, and automated response actions.

skill.md
name
implementing-endpoint-detection-with-wazuh
description
Deploy and configure Wazuh SIEM/XDR for endpoint detection including agent management, custom decoder and rule XML creation, alert querying via the Wazuh REST API, and automated response actions.
domain
cybersecurity
subdomain
security-operations
tags
- siem - xdr - wazuh - endpoint-detection - custom-rules - incident-response
version
'1.0'
author
mahipal
license
Apache-2.0
nist_ai_rmf
- GOVERN-1.1 - MEASURE-2.7 - MANAGE-3.1 - MANAGE-2.4 - MEASURE-3.1
nist_csf
- DE.CM-01 - RS.MA-01 - GV.OV-01 - DE.AE-02

Implementing Endpoint Detection with Wazuh

Overview

Wazuh is an open-source SIEM and XDR platform for endpoint monitoring, threat detection, and compliance. This skill covers managing agents via the Wazuh REST API, creating custom decoders and rules in XML for organization-specific detections, querying alerts, and testing rule logic using the logtest endpoint.

When to Use

  • When deploying or configuring implementing endpoint detection with wazuh capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

Prerequisites

  • Wazuh Manager 4.x deployed with API enabled
  • Python 3.9+ with requests library
  • API credentials (username/password for JWT authentication)
  • Understanding of Wazuh decoder and rule XML syntax

Steps

Step 1: Authenticate to Wazuh API

Obtain JWT token via POST to /security/user/authenticate.

Step 2: List and Monitor Agents

Query agent status, versions, and last keep-alive via /agents endpoint.

Step 3: Query Security Alerts

Search alerts by rule ID, severity, agent, or time range.

Step 4: Test Custom Rules with Logtest

Use the /logtest endpoint to validate decoder and rule logic against sample log lines.

Expected Output

JSON report with agent inventory, alert statistics, rule coverage, and logtest validation results.

how to use implementing-endpoint-detection-with-wazuh

How to use implementing-endpoint-detection-with-wazuh on Cursor

AI-first code editor with Composer

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 implementing-endpoint-detection-with-wazuh
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/implementing-endpoint-detection-with-wazuh

The skills CLI fetches implementing-endpoint-detection-with-wazuh from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/implementing-endpoint-detection-with-wazuh

Reload or restart Cursor to activate implementing-endpoint-detection-with-wazuh. Access the skill through slash commands (e.g., /implementing-endpoint-detection-with-wazuh) or your agent's skill management interface.

⚠

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

Additional Resources

›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases▌

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

✓

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

✓

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

✓

Improve work quality by 30-40% with less effort

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

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.5★★★★★54 reviews
  • ★★★★★Amina Gonzalez· Dec 24, 2024

    implementing-endpoint-detection-with-wazuh reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • ★★★★★Advait Flores· Dec 24, 2024

    Keeps context tight: implementing-endpoint-detection-with-wazuh is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • ★★★★★Chinedu Rahman· Dec 4, 2024

    implementing-endpoint-detection-with-wazuh has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • ★★★★★Chinedu Choi· Dec 4, 2024

    We added implementing-endpoint-detection-with-wazuh from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • ★★★★★Naina Agarwal· Nov 23, 2024

    implementing-endpoint-detection-with-wazuh fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • ★★★★★Arya Khan· Nov 23, 2024

    implementing-endpoint-detection-with-wazuh is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★Zara Kapoor· Nov 23, 2024

    Solid pick for teams standardizing on skills: implementing-endpoint-detection-with-wazuh is focused, and the summary matches what you get after install.

  • ★★★★★Sakshi Patil· Nov 15, 2024

    implementing-endpoint-detection-with-wazuh is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★Arya Sethi· Nov 15, 2024

    I recommend implementing-endpoint-detection-with-wazuh for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • ★★★★★Yusuf Desai· Oct 14, 2024

    We added implementing-endpoint-detection-with-wazuh from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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