An AI agent swarm is a set of coordinated AI agents that split a larger task into smaller jobs, such as research, analysis, planning, and execution. Instead of one model doing everything, each agent handles a narrow role and passes results to the next step. This makes the system faster and more scalable, but also harder to supervise.
In cyber security, swarms matter because they can accelerate the pre-attack workflow: one agent can gather reconnaissance, another can profile targets, and a third can draft lures or prepare tools. That compression can reduce the time defenders have to detect suspicious activity and block abuse. The same architecture can also help defenders, for example by using multiple agents to triage alerts, compare indicators, or test controls. Security teams should treat agent swarms like privileged software: limit tool access, validate actions outside the model, isolate untrusted inputs, and require human approval for risky steps.