Multi-agent orchestration is an AI design in which one coordinating system assigns work to several smaller subagents. Each subagent may research, summarize, call tools, or handle a narrow step in a larger workflow, while the orchestrator tracks context and combines the results. This approach can make AI systems faster and more capable than a single monolithic model.
In cyber security, orchestration matters because every subagent may have different permissions, data access, and external connectors. If boundaries are weak, a mistake in one agent can expose secrets, trigger unsafe actions, or let an attacker pivot through shared state. Defenders therefore treat agent plans, tool access, and prompt inputs as security controls. In real deployments, secure orchestration uses least privilege, approval gates for sensitive actions, logging, and strict isolation between agents and shared resources.