Enterprise AI Security
Access Control in RAG & Vector DBs: Preventing Cross-Tenant Data Leaks
Implement metadata filtering, role-based access control (RBAC), and document-level ACLs to ensure users only retrieve authorized embeddings.
Pre-Filter Security Constraints
Always enforce tenant ID and role filters (`filter: { tenant_id: user.tenant_id }`) directly at the database query level to prevent accidental cross-tenant vector leakage.
Related Technical Guides
Deepen your understanding with these closely related production architectures and tutorials:
Defending Against Prompt Injection & Jailbreaks: Indirect Attacks & Guardrails
Protect your enterprise AI agents from direct and indirect prompt injections, adversarial suffixes, and untrusted user input.
NVIDIA NeMo Guardrails: Programmable Dialog Rails, Safety Policies & Colang
Enforce safety boundaries on LLM outputs using NVIDIA NeMo Guardrails: input rails, dialog flow constraints, and output validation.
PII Masking & Privacy-Compliant AI: Microsoft Presidio & Real-Time Redaction
Anonymize credit cards, government IDs, and health data before sending prompts to external LLMs using Microsoft Presidio and reversible tokenization.