A practical reference architecture for securing LLM-generated SQL before execution, covering parser, catalog binding, policy engine, risk scoring, repair loops, and audit logs.
Before a Text-to-SQL system reaches production, teams should validate more than SQL syntax. This checklist covers 10 risks: unsafe statements, hallucinated fields, PII exposure, permission bypass, high-cost queries, wrong joins, audit gaps, and more.
Enterprises should not let LLMs execute SQL directly because generated queries need deterministic validation, permission checks, risk scoring, and audit before reaching a database.
An LLM SQL Guard checks AI-generated SQL before execution and returns structured feedback that helps an LLM produce safer, more accurate queries.