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Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Clear out junk files and repair common Windows errorsFree Scan →Scan for outdated or missing drivers - takes under a minuteDriver Scan →A text-to-SQL agent should never decide what a caller is allowed to see. Authenticate the caller in trusted application or database context, limit the agent to task-specific tools and a least-privilege database role, and make the database enforce which rows and operations that identity can access. SQL parsing and table allowlists add defense in depth; they are not a substitute for database authorization.
Why letting the model choose tables creates an authorization risk
A text-to-SQL agent may choose tables, joins, filters, and operations based on a prompt. If it also receives a general SQL execution tool over data belonging to multiple users or tenants, the application is relying on the model to preserve the caller’s access limits in every generated query. That is not a dependable security boundary: a missing tenant filter, an unexpected join, or an altered query could expose data outside the caller’s entitlement.
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Google Cloud’s Cloud SQL guidance says, “Instructing the agent to enforce the access rules is typically not sufficient to protect data.” Its unsafe example gives an agent a general SQL tool over a table containing all users’ orders; the safer pattern uses a custom lookup tool whose user identity is set outside the agent’s control. The practical distinction is who controls the authorization context: the trusted application and database, or the model-generated query.
Does authorization have to run before SQL generation?
Not necessarily. The model may propose table names before the database evaluates a query. The security requirement is that an untrusted table or query choice cannot expand the data the caller may access, and that authorization is enforced before data is returned or changed.
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That does not imply a single query-rewriting sequence will work for every database or tenancy design. In one system, a backend may expose a user-scoped lookup tool instead of SQL. In another, the database may apply row policies using trusted session context. In either case, do not let the model supply or preserve the identity that determines its own access.
Build the authorization boundary in layers
- Authenticate outside the model. Verify the human or service caller in the application, then bind a stable user or tenant identity to trusted request state. Do not accept an identity from model-generated SQL or treat a prompt claim as proof of identity.
- Expose the narrowest useful tool. Prefer task-shaped operations, such as looking up the authenticated caller’s orders, over an unrestricted
execute_sqltool. The backend should apply the verified identity and allowed scope. Google Cloud’s agent-security guidance describes this user-scoped tool pattern. - Use a least-privilege database role. Give the normal request path only the required operations and database objects. Separate credentials where trust levels differ, and keep migration or administrative credentials out of ordinary agent requests. OWASP’s Database Security Cheat Sheet recommends least privilege and describes controls at database, table, column, and row levels, including restricted views where access to underlying tables is blocked. OWASP’s Secure Database Access guidance also discusses parameterization, validation, stored procedures, least privilege, and separating credentials by trust distinction.
- Enforce tenant scope in the database when appropriate. For shared tables, apply row restrictions using identity established in trusted context, and verify how the chosen engine handles owners, privileged roles, and policy bypass. A policy is only useful if the application’s runtime role is actually subject to it.
- Validate generated SQL as another guardrail. Parse statements where practical, allowlist accessible schemas and tables, and reject unsupported constructs. Apache Airflow’s agent-tool guidance treats parsing and table checks as strong application-level safeguards while identifying a least-privilege database role as the boundary that remains if parser checks fail.
- Test failure paths, not just successful prompts. Verify that another tenant’s row is inaccessible and that missing or malformed identity context fails closed. Include joins, subqueries, aggregates, views, and any elevated execution route that exists in the system.
Choose a tenant-isolation design deliberately
OWASP’s Multi Tenant Security Cheat Sheet discusses separate databases, separate schemas, shared tables with row-level policies, and hybrid arrangements. There is no universal winner: compare how the boundary is enforced, what operational overhead it creates, how grants and migrations are managed, and whether each request remains attributable to the caller.
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| Design | Where isolation is expressed | Trade-offs to evaluate |
|---|---|---|
| Separate databases | Database boundary and, depending on deployment, separate credentials or infrastructure. OWASP Multi Tenant Security Cheat Sheet. | Assess operational and cost overhead alongside the strength of credential, network, and backup separation required for the workload. OWASP Multi Tenant Security Cheat Sheet. |
| Separate schemas | Schema selection and grants within a database. OWASP Multi Tenant Security Cheat Sheet. | Assess schema/search-path controls, grants, and migration complexity; ensure each request is bound to the correct tenant rather than relying on model-selected schema names. OWASP Multi Tenant Security Cheat Sheet. |
| Shared tables with row-level policies | Database row predicates applied to shared data. OWASP Multi Tenant Security Cheat Sheet. | Assess policy coverage, trusted identity propagation, role bypass behavior, and the ease of proving that missing context fails closed. OWASP Multi Tenant Security Cheat Sheet. |
| Hybrid arrangement | A combination of database, schema, and/or row-level boundaries. OWASP Multi Tenant Security Cheat Sheet. | Can match different workload needs, but assess the added complexity of coordinating grants, policies, migrations, credentials, and negative-path tests. OWASP Multi Tenant Security Cheat Sheet. |
Make the isolation model explicit in the application design. In particular, determine how identity reaches the enforcement point on every request, which credentials can bypass that point, and how a test can show that absent or invalid identity does not return another tenant’s data.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsEngine-specific row-security behavior matters
PostgreSQL
PostgreSQL 18 documents that when row-level security is enabled, normal row access must be allowed by a policy; if no policy allows access, rows are denied by default. Table owners are typically exempt from these policies. Confirm that the application uses a role subject to the policies rather than assuming that an owner-level role is constrained.
SQL Server
SQL Server uses security policies with filter predicates to filter rows from reads and block predicates to reject writes that violate the policy. These are SQL Server mechanisms; do not assume another engine has the same behavior or bypass semantics. Check the relevant engine’s documentation and validate the runtime role and policy configuration you actually deploy.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What to verify before putting an agent on tenant data
- The caller is authenticated independently of the model, and the identity used for authorization comes from trusted backend state.
- The agent has no broader tool or credential path than its task requires; administrative and migration access is not available on the ordinary request path.
- Database permissions constrain the operations and objects the runtime role can use, even if application-side SQL checks fail.
- Tenant filtering is enforced at a boundary the agent cannot rewrite or omit, and the engine’s owner, superuser, and bypass-role behavior is understood.
- Tests cover cross-tenant reads, missing or malformed identity, joins, subqueries, aggregates, views, writes where applicable, and elevated execution paths.
No incident rate or benchmark is needed to justify this design. The failure is architectural: if the model can choose both the data source and the only restriction on whose data is returned, then the model’s query has been given more authority than a prompt can reliably secure.
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