Automating Cybersecurity Operations with Models, Agents, and Orchestrators
Cybersecurity teams are automating more than ever, but many workflows are still rigid, manual, and hard to scale. This training introduces a simpler approach: using AI models, agents, orchestration, and MCP (Model Context Protocol) to build flexible, intelligent security workflows.
Participants will learn:
- How AI models can analyze alerts, logs, and security data
- How agents can decide what to do and take action
- How orchestrators connect tools, workflows, and human input
- How MCP enables secure, structured access between AI systems and external tools/data
Instead of static rules, this approach focuses on adaptive workflows that can respond to real situations.
Through real cybersecurity use cases participants will see how to combine traditional automation with AI-driven decision-making. The training uses practical examples and low-code tools to design workflows that are:
- Easier to build
- Easier to maintain
- Aligned with real-world security operations
By the end, participants will be able to design simple, scalable automations that reduce manual work, improve response time, and safely integrate AI into their security stack.
This training provides a practical introduction to cybersecurity automation using AI models, agents, orchestration, and MCP (Model Context Protocol). It is designed for security professionals who want to move beyond manual processes and basic scripting toward more flexible and scalable workflows.
Participants will learn how to break down common security tasks into simple, automated workflows where:
- AI models help analyze alerts, logs, and security data
- Agents make decisions and take actions
- Orchestrators connect tools, data, and people into reliable processes
- MCP enables secure, structured access between AI systems and external tools or data sources
Rather than focusing on theory, the course emphasizes practical design patterns and hands-on examples. Participants will see how low-code orchestration platforms (such as n8n-style workflow engines) can be used to build, test, and operate workflows with visibility, logging, and human approval steps when needed.
The goal is not just automation, but adaptive workflows that can respond to real-world situations while keeping humans in the loop.
By the end of the training, participants will be able to design simple, scalable automation workflows that reduce repetitive work, improve response time, and safely integrate AI into their security operations without losing control or oversight.