A Practical Vibe Coding Security Checklist: What Passive Scanners Can and Cannot Prove

Check My Vibe — Mon, 13 Jul 2026 02:24:00 +0000

Vibe coding makes it possible to ship a useful web app in a weekend. It does not make the security model disappear.

A generated app can compile, deploy, and look polished while still exposing a source map, shipping a credential-shaped string in a JavaScript bundle, missing basic browser security headers, or relying on authorization rules nobody has tested.

The practical response is not to trust one score. It is to use the right scanner for each layer.

Disclosure: I am building Check My Vibe. I include it below alongside competing tools because the useful question is not which product has the loudest claim; it is which part of the system each one can actually inspect.

What a passive URL scan can actually prove

A passive scanner starts with the same public surface a normal visitor can reach. Without credentials or exploit attempts, it can provide useful evidence about:

HTTPS behavior, redirects, and certificate delivery
response headers such as Content-Security-Policy, HSTS, X-Content-Type-Options, and framing controls
cookies visible in public responses
public HTML and selected same-origin JavaScript assets
publicly reachable source maps or sensitive-looking files
credential-shaped strings that were shipped to the browser
CORS behavior that can be observed safely
technology and deployment clues exposed in responses

That evidence is valuable because these are real deployment mistakes. If a production bundle contains a private key, or a source map is publicly available, the problem is already observable from outside.

But wording matters. A passive scan reports what it observed at a particular URL and time. It does not prove the entire application is secure.

What it cannot prove

A public, unauthenticated scan normally cannot verify:

tenant isolation after login
whether user A can read or modify user B's records
the correctness of Supabase RLS policies that are not exposed through public behavior
server-side authorization on every API route
secret handling inside a private repository or CI system
vulnerable dependencies that never reveal their versions publicly
payment, webhook, password-reset, and invitation business logic
administrative paths that require legitimate test accounts
the absence of every vulnerability

A green public-surface result should therefore mean no issue was observed in the tested surface, not the app is safe in every respect.

Four tools, four different scopes

The feature descriptions below reflect the products' public sites in July 2026. They are not a benchmark result, and the tools can change.

Tool	Primary surface	Useful when	Important boundary
ScanVibe	Public URL	You want a fast outside-in scan, a grade, and fix prompts. Its site lists 18 analyzers covering SSL, headers, exposed secrets, libraries, files, cookies, and CORS.	Outside-in evidence cannot by itself prove private authorization, database isolation, or every server-side condition.
ShipSafe	GitHub repository and live URL	You want source-aware checks plus plain-English findings. Its site currently advertises 60+ checks and says uploaded code is deleted after scanning.	Repository access gives deeper visibility, but the result still depends on rule coverage, repository completeness, and runtime configuration.
SecureVibe	Cursor and VS Code	You want file-level feedback inside the IDE before deployment, with reports and remediation prompts. Its site says it does not collect or store code.	IDE analysis is strongest on code it can see; it may not observe the final CDN, proxy, DNS, header, or production configuration.
Check My Vibe	Passive public web surface plus a manual checklist	You want a free, no-account first pass over public deployment mistakes, followed by a separate 36-point review checklist.	It does not log in, exploit the target, recursively crawl the whole site, inspect a private repo, or certify backend policy correctness.

This is not a winner-takes-all category. The products above overlap, but they sit at different points in the delivery loop: editor, repository, deployed application, and manual review.

A practical layered workflow

For an AI-built app, I would use the following order.

1. Run a passive scan on the deployed URL

Do this before sharing the launch publicly. Fix obvious header gaps, exposed source maps, accidentally public files, browser-shipped secrets, and unsafe redirects. Re-run after the fix.

Only scan sites you own or are authorized to assess. Passive does not mean permissionless.

2. Scan the repository and dependency graph

A URL scanner cannot see most server code. Use repository-aware secret scanning, dependency analysis, and static analysis. Review findings rather than pasting every generated fix blindly; automated remediation can change behavior or introduce new bugs.

3. Add feedback inside the editor or CI pipeline

The cheapest issue is the one that never reaches production. IDE and CI checks can flag new secrets, unsafe patterns, and dependency changes close to the commit that introduced them.

4. Test authorization with real roles

Create a small role matrix: anonymous user, normal user, second tenant, support user, and administrator. For every sensitive action, record who should be able to read, create, update, and delete.

Then test the negative cases. Can user A request user B's object ID? Can a normal user call an admin API directly? Does hiding a button merely hide the action, or does the server enforce the rule?

5. Review the data layer separately

For Supabase, Firebase, or another backend-as-a-service, inspect policies in the provider console. Verify row-level rules, storage permissions, service-role key handling, backups, and logs. A public scanner should not claim to have proven private policy state it cannot access.

6. Exercise business logic

Password resets, email changes, invitations, checkout sessions, refunds, webhooks, and file uploads deserve explicit abuse cases. These failures are often specific to the product and are difficult for a generic scanner to infer.

7. Escalate when the risk justifies it

If the app handles money, health data, identity documents, regulated information, or meaningful volumes of personal data, automated checks are only preparation. A scoped professional review or penetration test is the appropriate deeper layer.

A compact pre-launch checklist

Before launch, I want clear answers to these questions:

Did any secret reach client-side code or version history?
Are production source maps intentionally public?
Are security headers configured at the final edge, not only in local code?
Does the server enforce authorization for every sensitive operation?
Have cross-tenant negative tests been run?
Are database and storage policies reviewed in the provider console?
Are dependencies and lockfiles scanned?
Are admin functions protected server-side?
Are rate limits and abuse controls present on expensive or sensitive endpoints?
Are logs, backups, incident contacts, and key-rotation steps documented?

You can use the free Check My Vibe passive scanner and 36-point checklist as the first step. Treat the automated score and the manual checklist as separate evidence, then add repository, IDE, authorization, and business-logic testing according to the risk of the application.

The responsible promise is not that a two-minute scan makes an app secure. It is that a well-scoped scan can reveal specific, fixable evidence — and tell you honestly what still has not been tested.

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