This n8n workflow supercharges your SOC by fully automating triage, analysis, and notification for Wazuh alerts—blending event-driven automation, OpenAI-powered contextual analysis, and real-time collaboration for incident response.
Instantly filters Wazuh alerts by severity to focus analyst effort on the signals that matter.
Uses OpenAI's GPT-4o-mini to auto-generate context-rich incident reports, including:
Delivers clean, actionable reports directly to your SOC team via Telegram. Easily extendable to Slack, Outlook, Gmail, Discord, or any other preferred channel.
Eliminates alert fatigue using smart filters and custom AI prompts that suppress false positives and highlight real threats.
Tweak severity thresholds, update prompt logic, or integrate additional data sources and channels — all with minimal effort
Webhook
Listens for incoming Wazuh alerts in real time.
If Condition
Filters based on severity (1 low
, 2 medium
, etc.) or other logic you define.
AI Investigation (LangChain + OpenAI)
Summarizes full alert logs and context using custom prompts to generate:
Notification Delivery
The report is parsed, cleaned, and sent to your SOC team in real-time, enabling rapid response — even during high-alert volumes.
No-Op Path
Efficiently discards irrelevant alerts without breaking the flow.
Traditional alert triage is manual, slow, and error-prone — leading to analyst burnout and missed critical threats.
This workflow shows how combining workflow automation with a tailored AI model enables your SOC to shift from reactive to proactive. Analysts can now:
⚠️ Note: We learned that generic AI isn’t enough. Context-rich prompts and alignment with your actual SOC processes are key to meaningful, scalable automation.
Clone this workflow, adapt it to your processes, and never miss a critical alert again.
📬 Contributions welcome!
Feel free to raise PRs, suggest new enhancements, or fork for your own use cases.
Created by Mariskarthick M
Senior Security Analyst | Detection Engineer | Threat Hunter | Open-Source Enthusiast