RLS Policies in Supabase are a core security mechanism that gives developers precise control over which database rows users can view or modify. Because Supabase enables Row Level Security by default, developers — especially those using AI-driven builders like Lovable, Bolt.new, v0, and PromptXL — often run into errors when policies are missing or incorrectly configured. Understanding how these policies work is essential for building secure, scalable applications.
What RLS Policies in Supabase Actually Do
Row Level Security (RLS) is a PostgreSQL feature that allows you to enforce access control at the row level rather than the table level.
Without RLS
Any authenticated user with table access can see every row.
With RLS Policies in Supabase
Each row is filtered based on logical rules you define, ensuring strict and safe access.
This is crucial for applications where:
- users own their private data
- multi-tenant organizations share tables
- strict data privacy is required
- unauthorized access must be prevented
Supabase enables RLS by default to protect your data from accidental exposure.
Why RLS Policies in Supabase Matter for Security
Supabase enforces security at the database layer, not just through frontend or API code.
This means:
✔ Even if the frontend breaks, users cannot see others’ data
✔ Even if someone directly calls your API, RLS still protects your data
✔ Multi-tenant apps remain isolated at the row level
✔ Sensitive data stays secure even if the application logic fails
RLS is not optional for production — it is the foundation of Supabase security.
What Are RLS Policies in Supabase?
RLS policies are PostgreSQL rules that tell the database:
- which rows a user can read
- which rows a user can modify
- which rows a user can insert
- which rows a user can delete
Once RLS is enabled:
Every operation is blocked unless a policy explicitly allows it.
This is what makes RLS so powerful — and so strict.
How RLS Policies in Supabase Work
RLS policies rely on two core components:
1. USING Clause
Controls which rows a user can read, update, or delete.
2. WITH CHECK Clause
Controls which rows a user is allowed to insert or update.
Example
A policy allowing users to read only their own rows:
using (user_id = auth.uid())
This check is executed on every row returned by the query.
Example of Common RLS Policies in Supabase
Assume a tasks table with:
| Column | Description |
|---|---|
| id | Primary key |
| title | Task title |
| user_id | Owner of the task |
Here are the essential policies:
Task creation is validated against their identity, preventing inserts for other users.
create policy "Read own tasks"
on tasks
for select
using (user_id = auth.uid());
Users can insert tasks only for themselves, ensuring that each new task they add is tied to their own account.
create policy "Insert own tasks"
on tasks
for insert
with check (user_id = auth.uid());
Updating is restricted so that individuals may modify only the tasks they personally own.
create policy "Update own tasks"
on tasks
for update
using (user_id = auth.uid())
with check (user_id = auth.uid());
Reading access is filtered, allowing each user to view only the tasks associated with their own user ID.
create policy "Delete own tasks"
on tasks
for delete
using (user_id = auth.uid());
With these RLS policies in Supabase, your table becomes fully secure.
Why RLS Policies in Supabase Break AI-Generated Apps
If you use AI tools like:
- Lovable
- Bolt.new
- v0
- Petal
- PromptXL
- ChatGPT
…you’ve likely experienced immediate RLS errors.
AI tools generate working CRUD code — but they do NOT generate:
- RLS policies
- ownership columns
- authenticated queries
- correct JWT handling
- server-side service-role inserts
This means Supabase rejects all requests, causing the well-known:
❌ “new row violates row-level security”
This is the most common failure point for no-code, low-code, and AI-generated Supabase apps.
Why RLS Policies in Supabase Are Essential for Production
Even if your app is small, RLS provides real protection:
✔ Privacy
Every user sees only their own data.
✔ Multi-Tenant Architecture
Teams, organizations, and workspaces remain isolated.
✔ Defense Against API misuse
Even direct API calls cannot bypass RLS.
✔ Protection from malicious users
Client manipulation doesn’t matter — the database enforces rules.
✔ Easy scalability
Your app can safely support thousands of users.
If your app is public-facing, RLS is mandatory.
RLS Policies in Supabase for Multi-Tenant SaaS Apps
A multi-organization product may require filtering by org_id instead of user_id.
Example:
using (
org_id in (
select organization_id
from memberships
where user_id = auth.uid()
)
)
This ensures the user only sees data for organizations they belong to.
When to Enable RLS Policies in Supabase
This depends on your development stage:
✔ Production
RLS must always be enabled.
✔ Development
If using AI-generated code:
→ Disable RLS first
→ Build your app
→ Add user_id
→ Then enable policies
This avoids repeated RLS errors during development.
Best Practices for RLS Policies in Supabase
Follow these guidelines:
✔ Use user_id or org_id for ownership
✔ Add SELECT, INSERT, UPDATE, DELETE policies
✔ Test with real authenticated sessions
✔ Keep policies as simple as possible
✔ Never expose the service role key to the frontend
✔ Document everything
Correct RLS design gives your app a strong security foundation.
Conclusion: RLS Policies in Supabase Are the Core of Database Security
Supabase delivers strong security by enforcing access at the database level rather than relying solely on application code. Well-written policies ensure that users can access only the rows intended for them, making your application safe, compliant, and ready to scale.