IBAC vs RBAC vs ABAC vs ReBAC: Which access control model fits AI agents?

AI agents challenge traditional authorization models because their required access can emerge unpredictably during a task, creating a tradeoff between overly narrow permissions that halt work and broad standing access that increases risk. Role-based access control (RBAC), attribute-based access control (ABAC), and relationship-based access control (ReBAC) remain effective for organizational roles, contextual conditions, and resource-specific sharing, respectively, but each relies on permissions being knowable before execution. Intent-based access control (IBAC) addresses this gap by assessing whether an agent’s requested action aligns with its current task, potentially allowing, denying, escalating, or requesting clarification. The term IBAC has been used in several earlier contexts and now encompasses both inferred approaches, which use models to judge actions dynamically, and declared approaches, which enforce predefined scopes deterministically. Effective implementations may combine both approaches, enforce controls close to agents and service APIs, broker credentials so agents cannot bypass controls, and preserve auditable records. IBAC is presented not as a replacement for existing authorization systems but as an additional layer that narrows an agent’s access within the boundaries established by RBAC, ABAC, and ReBAC.

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