implementing-endpoint-detection-with-wazuh
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.
Works with
0
total installs
0
this week
8.6K
GitHub stars
0
upvotes
Install Skill
Run in your terminal
0
installs
0
this week
8.6K
stars
Installation Guide
How to use implementing-endpoint-detection-with-wazuh on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
implementing-endpoint-detection-with-wazuh
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches implementing-endpoint-detection-with-wazuh from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate implementing-endpoint-detection-with-wazuh. Access via /implementing-endpoint-detection-with-wazuh in your agent's command palette.
Security 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 environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
| 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
requestslibrary - 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.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
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
Steps
- 1Install skill using provided installation command
- 2Test with simple use case relevant to your work
- 3Evaluate output quality and relevance
- 4Iterate on prompts to improve results
- 5Integrate 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
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Related Skills
implementing-soar-playbook-with-palo-alto-xsoar
3mukul975/Anthropic-Cybersecurity-Skills
performing-cryptographic-audit-of-application
5mukul975/Anthropic-Cybersecurity-Skills
exploiting-deeplink-vulnerabilities
3mukul975/Anthropic-Cybersecurity-Skills
analyzing-network-traffic-with-wireshark
2mukul975/Anthropic-Cybersecurity-Skills
scanning-docker-images-with-trivy
2mukul975/Anthropic-Cybersecurity-Skills
generating-threat-intelligence-reports
2mukul975/Anthropic-Cybersecurity-Skills
Reviews
- AAmina Gonzalez★★★★★Dec 24, 2024
implementing-endpoint-detection-with-wazuh reduced setup friction for our internal harness; good balance of opinion and flexibility.
- AAdvait 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.
- CChinedu 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.
- CChinedu 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.
- NNaina Agarwal★★★★★Nov 23, 2024
implementing-endpoint-detection-with-wazuh fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- AArya Khan★★★★★Nov 23, 2024
implementing-endpoint-detection-with-wazuh is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ZZara 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.
- SSakshi Patil★★★★★Nov 15, 2024
implementing-endpoint-detection-with-wazuh is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- AArya 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.
- YYusuf 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.
showing 1-10 of 54
Discussion
Comments — not star reviews- No comments yet — start the thread.