Row-Level Security and AI: What You Must Validate

TL;DR

• AI must honor the same RLS rules as users.
• Test RLS with AI‑style queries.

The problem

• RLS changes what data is visible, which changes answers.
• AI can accidentally bypass expected security if not configured.

Why it matters

• Security breaches are critical risks.
• Inconsistent access erodes trust.

Symptoms

• Different users receive different answers unexpectedly.
• AI mentions data outside a user’s access.

Root causes

• RLS tested only in reports, not in AI flows.
• Complex role logic not documented.

What good looks like

• RLS tested with AI query patterns.
• Clear mapping of roles to data access.

How to fix

• Create RLS test scenarios for AI queries.
• Log and review AI responses for access boundaries.
• Document RLS rules in the model.

Pitfalls

• Assuming report RLS equals AI RLS.
• Testing with only one role.

Checklist

• RLS test suite for AI queries.
• Audit logs for access issues.
• Role documentation complete.

Framework placement

Primary ARF layer: Context Stability. Diagnostic bridge: data-movement-reliability, semantic-reliability, execution-reliability.