Text-to-SQL security is a distinct problem from classic parameterized-query hygiene. With an LLM in the loop, the query itself is generated from untrusted natural language, so a prompt injection can steer the model into producing SQL that is syntactically valid but unauthorized, destructive, or data-leaking.
Parameterization protects individual literals, but the LLM writes the whole statement — table names, joins, and clauses included. The real guardrail is a validation layer that inspects the generated SQL as structure, not text.
QueryShield applies all of these as a proxy in front of your database, and audit-logs every decision. Because the agent only ever talks to the proxy, it never sees connection strings or credentials to abuse in the first place.
A secure SQL proxy for AI agents: natural language in, SELECT-only validated SQL out, per-agent row-level security, and an append-only audit log. Your agents never see connection strings.