LLM SQL Guard Architecture: Parser, Catalog, Policy Engine, Audit Log
This article outlines an architecture for an "SQL Guard" designed to enhance the security and governance of Text-to-SQL and data analysis agent systems. The proposed architecture includes components for parsing SQL queries, binding them to a catalog, enforcing policies, scoring risks, and maintaining an audit log. The goal is to ensure that generated SQL queries undergo deterministic checks for semantics, permissions, and auditing before execution. AI
IMPACT Provides a technical framework for securing LLM-generated SQL queries, crucial for enterprise data governance.