Are these policies optimized for database performance?

Yes, the templates follow best practices such as wrapping auth functions in subqueries and recommending specific indexes to minimize policy execution latency.

Does this skill support multi-tenant SaaS applications?

Yes, it includes specialized templates and scripts for organization-based isolation and team-based access control patterns.

Can I use this for AI and RAG applications?

Absolutely; it features specific patterns for securing conversation threads and protecting vector embeddings within RAG systems.

How does the security auditing feature work?

It provides an audit script that scans your database schema to identify tables lacking RLS or those that do not meet specific security requirements.

Supabase RLS Security Templates

Name: Supabase RLS Security Templates
Author: vanman2024

byvanman2024

安全与测试

Implements production-ready Row Level Security (RLS) policies and security audits for Supabase applications.

关于

This skill provides a comprehensive library of Row Level Security (RLS) templates designed to secure Supabase databases, focusing on multi-tenancy, user isolation, and specialized AI patterns like RAG and chat systems. It enables developers to automatically apply, test, and audit security policies through a standardized CLI workflow, ensuring data integrity and tenant isolation. By leveraging optimized PostgreSQL patterns and automated auditing scripts, it helps maintain a secure-by-default posture while minimizing performance overhead in production environments.

主要功能

AI-specific security patterns for chat histories and vector embeddings
Automated security auditing scripts to detect missing RLS configurations
Testing suite to validate policy enforcement across different user and org contexts
Performance-optimized policy patterns using JWT claims and efficient indexing
0 GitHub stars
Pre-configured templates for user isolation and multi-tenant SaaS architectures

使用场景

Building a multi-tenant SaaS where users must only access their organization's data
Securing a RAG-based AI application with user-specific document embeddings
Performing a security audit on an existing Supabase project to ensure full RLS coverage

关于

主要功能

AI-specific security patterns for chat histories and vector embeddings
Automated security auditing scripts to detect missing RLS configurations
Testing suite to validate policy enforcement across different user and org contexts
Performance-optimized policy patterns using JWT claims and efficient indexing
0 GitHub stars
Pre-configured templates for user isolation and multi-tenant SaaS architectures

使用场景

Building a multi-tenant SaaS where users must only access their organization's data
Securing a RAG-based AI application with user-specific document embeddings
Performing a security audit on an existing Supabase project to ensure full RLS coverage