Agent configuration is the set of rules, permissions, tool connections, and workflow settings that control how an AI assistant behaves. It determines what the agent can read, what actions it can take, which prompts or system instructions it follows, and how it chains steps together during a task.
In cyber security, agent configuration matters because small changes can create large risk. If an assistant has access to code repositories, shells, ticketing systems, or secret stores, a weak configuration may let it expose sensitive data, make unsafe edits, or follow malicious instructions hidden in content it processes. Good configurations limit privileges, separate trusted instructions from untrusted input, and require human approval for high-impact actions. Defenders also use configuration reviews and regression tests to verify that an agent still behaves safely after model swaps, tool changes, or prompt updates.