How AI Agents Expose Database Security Assumptions

Traditional database security models assume predictable, predetermined access patterns—assumptions that break when LLM agents generate unpredictable queries dynamically. This forces a choice between granting overly broad permissions or relying on prompt instructions to enforce security, neither of which adequately protects data. As AI agents move into production, organizations must rethink database security architecture itself, as current tools were never designed to handle creative, autonomous data access patterns.