An AI agent framework is software for building systems that coordinate tasks, call tools, manage state, and automate multi-step AI workflows. Instead of a single model answering one prompt, the framework helps an agent decide what to do next, which APIs or data sources to use, and how to combine the results.
In cyber security, these frameworks matter because they often sit between an AI model and powerful internal resources. If misconfigured or vulnerable, they can expose credentials, allow unauthorized tool use, or become a path to remote code execution and data theft. Attackers may target the orchestration layer, prompt logic, or plugin interfaces to make the agent leak secrets or trigger unsafe actions. Defenders should treat these platforms like other high-value application infrastructure: limit tool permissions, isolate sensitive connectors, log agent actions, and patch quickly when flaws are found.