// ANSWER

What security checks should I do before launching my SaaS?

Updated 2026-08-07 · 6 min read

The short answer

You do not need a long audit, for an AI-built SaaS, a handful of checks catch almost all of the serious risk. Confirm that no private database table is readable by a logged-out stranger, that no secret keys are visible in the browser, that permission checks run on the server rather than in the interface, that payments are verified server-side, and that user uploads are not sitting on public URLs. Run these before you take a real payment, not after. Each one has a clear yes/no answer and a known fix.

The five checks that actually matter

Security advice for engineers can run to hundreds of items. For a founder launching an AI-built SaaS, the risk is concentrated in a few places. Get these right and you have handled the issues most likely to leak customer data or money:

1. Database access, can a logged-out visitor read any private table? Check Supabase Row Level Security or Firebase security rules on every table that holds user data.
2. Exposed secrets, is any secret key visible in View Source, the network tab, or your JavaScript bundle? Public keys are fine; sk_ and service_role keys are not.
3. Server-side permissions, are "who can do what" checks enforced on the server, not just hidden in the front-end where a user can bypass them?
4. Payment verification, does your server confirm payments with Stripe (verified webhook or a server-side check) instead of trusting the browser?
5. File uploads, are user files private by default and served through signed links, not sitting on guessable public URLs?

Why these five and not fifty

These are the checks where an AI tool's "make it work" shortcut turns directly into exposed data or lost money, and where the problem is invisible until someone finds it. They are also the areas AI tools most reliably get wrong on Next.js, Supabase, Firebase, and Stripe. Longer lists exist and have their place, but if you only have an afternoon before launch, spend it here.

How to actually run each check

None of these require you to be an engineer:

Database: in a private browser window with no login, try to load pages and watch the network tab for /rest/v1/ (Supabase) requests that return real data. In the dashboard, confirm RLS is on with real policies.
Secrets: right-click → View Source and search for sk_, service_role, and secret. Search your loaded scripts too (developer tools → Sources → global search).
Permissions: try to open an admin page or edit another user's data while logged in as a normal user. If the interface merely hides the button, that is not protection.
Payments: check whether access unlocks from browser code and whether your Stripe webhook verifies a signature.
Uploads: copy a file's URL and open it in a logged-out window. If it loads for anyone, the bucket is public.

Do it once, then keep watching

Launch security is not a one-time event, because every new feature your AI tool ships can reopen a gap, a new table without RLS, a new key in the wrong place. Run the checklist before launch, and re-run the relevant checks whenever you ship something that touches data, auth, or payments. A scan can do this automatically on every deploy and email you when a new hole appears, so you are not relying on memory.

Key takeaways

Most serious risk in an AI-built SaaS sits in five areas: database access, exposed secrets, server-side permissions, payment verification, and file uploads.
Run these checks before you take a real payment, not after.
Each check has a clear yes/no answer you can test yourself, mostly using a private browser window and developer tools.
Hiding a button in the interface is not a permission check, enforcement must happen on the server.
Re-check after every feature that touches data, auth, or payments; new code can reopen old gaps.

Frequently asked

How long does a pre-launch security check take?

The manual version of these five checks is an afternoon's work for most small apps. An automated scan returns a graded result in about a minute and points you straight at what needs fixing.

Do I need penetration testing before launch?

A formal pentest is usually overkill for an early-stage AI-built SaaS and is aimed at engineers. Start with the five checks here; consider a pentest later if you handle especially sensitive data or a customer requires one.

What if I only have time for one check?

Check database access. Whether a logged-out stranger can read your private tables is the most common serious flaw in AI-built apps and the one that leaks customer data directly.