Data Leak in Your App? Find and Close It

Reviewed by: Codersarts Security Engineering Team · Last updated: November 2026

What it means when your app has a data leak

A data leak means private information is reachable by people who shouldn't see it: one customer viewing another's invoices, a public link to a storage bucket of user uploads, or an API that returns full user records when the app only shows a name.

Most leaks aren't hacks. They're access checks that were never written. The app's interface hides the data, but the API or database still hands it to anyone who asks the right way.

Symptoms: you're in the right place if

• A user reported seeing someone else's data

• Changing a number in the URL or API request shows another record

• API responses contain email addresses, phone numbers or fields the app never displays

• Supabase's security advisor or Firebase warns that data is publicly accessible

• Files are stored in public buckets with guessable links

• Your app was built quickly or with AI tools and access rules were never reviewed

Business function

Business functions affected: Engineering, Product, Legal, and Customer Support.

Typical owner: CTO or lead engineer, with the founder involved if customers are affected.

Common stage: Early-stage and growth products, especially apps built with Supabase, Firebase or AI builders, and products that added teams or multi-tenancy later.

Is this the right help for you?

A good fit if:

• Users can see data that isn't theirs

• You use Supabase, Firebase or a custom API and aren't sure the rules are right

• You need to know exactly what was exposed and to whom

• You're adding organizations or multi-tenancy

Not the right fit if:

• Your systems were broken into by an attacker: see app got hacked

• You need legal advice on breach notification: involve a lawyer alongside us

First steps if you find a data leak

1. Confirm the leak with a test account, not real customer data

2. Restrict or disable the affected endpoint, table or bucket if you can do it safely

3. Check logs to estimate how long it was open and who accessed it

4. Rotate any service keys that were exposed

5. Check your notification duties under GDPR, the DPDP Act or customer contracts

Business impact: what it costs to leave it unfixed

• Privacy breach: personal or business data seen by the wrong people.

• Legal duties: GDPR and the DPDP Act may require notification.

• Lost deals: enterprise buyers walk away from products that leak data.

• Churn: customers leave when they learn their data was visible to others.

Root causes: why apps leak data

Missing ownership checks

The API checks that a user is logged in but not that the record belongs to them.

Database rules too broad

Supabase RLS disabled or set to allow everyone; Firebase rules left in test mode.

Over-exposed API responses

Endpoints return whole database rows instead of only the fields the app needs.

Public storage

Buckets or file links that anyone with the URL can open.

Multi-tenancy added later

Team or organization boundaries were never built into queries.

Common data leak scenarios

Data exposure checklist

Every “no” is a likely gap.

API

• Does every endpoint check that the user may access that specific record?

• Do responses contain only the fields the app needs?

Database

• Is row-level security or equivalent enabled on every table?

• Are service or admin keys kept on the server only?

Storage

• Are buckets private with signed or expiring links?

• Are user uploads separated by user or tenant?

Testing

• Do you test access as two different users and two tenants?

• Do tests run before every release?

Potential solution family

Solution type: Fix. We close every leak and prove it with tests.

Solution family: Access control and data security engineering: API authorization, database row-level rules, storage policies and automated access tests.

How we fix it: closing data leaks

1. Map the data

List every table, endpoint and bucket that holds private data and who should see it.

2. Test like an attacker

Query everything as anonymous users, normal users and other tenants.

3. Fix access control

Add ownership and tenant checks in the API and database rules.

4. Trim responses

Return only the fields each screen needs.

5. Lock down storage

Make buckets private and switch to signed URLs.

6. Add tests

Automated access tests that run before every release.

Typical timeline

Most leaks can be closed within days once found. Redesign is only needed when tenancy was never modeled.

Mistakes to avoid

• Hiding data in the interface instead of blocking it in the API

• Testing only as an admin user

• Enabling RLS without policies, which breaks the app and leads teams to disable it again

• Using a service-role key in the frontend to make errors go away

• Fixing one endpoint and assuming the rest are fine

Required skills

• Database security: row-level security, roles and encryption.

• API security: ownership checks and response filtering.

• Access control: roles, permissions and tenant isolation.

• Multi-tenant systems: separating customer data by design.

Relevant technologies

• Backends-as-a-service: Supabase and Firebase

• Databases: PostgreSQL, MySQL and MongoDB

• Cloud storage on AWS, Azure and Google Cloud

• REST and GraphQL APIs

Diagnosis offer: start with a fixed-price access audit

If you use Supabase, start with a fixed-price RLS audit. For Firebase, use the security rules audit. For custom APIs, start with an API security review.

What you get:

• A table-by-table or endpoint-by-endpoint exposure report

• Tests run as each role and tenant

• Fixed rules or code changes

• Confirmation that the leak is closed

Proof

Example engagement: marketplace leaking order data

An illustrative example based on the pattern we see most often. Client details are kept confidential.

The situation: A marketplace built with an AI app builder received a report that one seller could see another seller's orders.

What we found:

• RLS was enabled on 9 of 14 Supabase tables

• The orders and messages tables had no policies

• A storage bucket of invoices was public

What we changed:

• Added owner and tenant RLS policies on every table

• Made the bucket private with signed URLs

• Added access tests for two sellers and two buyers

The result: Each user now sees only their own data, and the tests catch regressions before release.

Why buyers trust Codersarts

• Delivering software, cloud and security engineering for clients worldwide since 2018

• A managed in-house engineering team, not a freelancer marketplace

• Security engineers who are also developers, so we fix what we find

• Testing only with written authorization and agreed scope

• Confidential by default: we sign NDAs before accessing your code or accounts

Frequently asked questions

Related problems

• App got hacked: when an attacker has broken in.

• MVP not production ready: apps launched before security was reviewed.

• Product not enterprise ready: when buyers ask how data is protected.

• Codersarts cybersecurity services: every security service in one place.