Giving AI Agents the Same RBAC Rules as Your Users: Building a Laravel Permission Layer LLMs Actually Respect

Integrating LLMs into existing applications creates significant security risks, as AI agents often operate outside standard web middleware, bypassing traditional session-based authentication. This article argues that developers must treat LLMs as proxies for human users rather than independent entities. By explicitly binding the acting user's identity to the agent's execution context, developers can enforce Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) at the database level. The author demonstrates how to use Laravel's authorization gates, Eloquent scopes, and dynamic tool registries to ensure that agents only access data permitted to the specific user they represent. Key recommendations include filtering data via SQL rather than prompts, auditing agent actions with user-specific context, and utilizing advanced permission packages to handle complex hierarchical rules. This architectural approach prevents 'god-mode' data leaks and ensures that AI-driven tools remain compliant with enterprise security policies.