Vibe-Coded Apps: What to Fix Before Going to Production

Fix four things before launch. Authentication that only checks on the frontend. Database permissions left at their default, usually open. Hardcoded API keys sitting in the JavaScript bundle. Unvalidated inputs on any form that touches real data. These four account for most vulnerabilities found across thousands of scanned vibe-coded apps. None of them show up unless someone specifically tests for them.

Maybe your app started as a weekend build in Lovable, Replit, or Bolt. Now it is heading toward real users, a fundraising conversation, or a compliance review. The checklist below tells you what to look at first. It also tells you when to bring in someone who builds software for a living.

This wall looks the same whether you are a funded startup or an enterprise team. A founder raising a seed or Series A round on a vibe-coded MVP is about to face investor technical diligence that asks about AI code provenance before it asks about growth metrics. An enterprise team that inherited a vibe-coded internal tool from another department faces the same question from IT and security review, just with a compliance officer instead of an investor asking it. Either way, “we built it fast” is not an answer anyone accepts anymore.

A vibe coding audit service gives you a real answer: what is actually in the codebase, and who checked it. This picks up where our founder’s guide to vibe coding leaves off, once the prototype is built and the question becomes what to fix before real users touch it. If you are still choosing who builds that first version, our roundup of top vibe coding companies is a useful starting point.

What Actually Breaks When a Vibe-Coded App Goes to Production?

In October 2025, application security firm Escape scanned 5,600 publicly available vibe-coded apps built on platforms like Lovable, Base44, and Create.xyz. The research team found more than 2,000 high-impact vulnerabilities, over 400 exposed secrets such as API keys and access tokens, and 175 cases of exposed personal data, including medical records and financial details. Every finding sat in a live, public system. The scans were run in passive mode, so the actual number of exploitable issues is likely higher.

The pattern behind these numbers repeats for a structural reason. It is not random. An AI coding tool satisfies the request it was given. If a prompt says “let users view their orders,” the model builds exactly that. It has no reason to also add “and block them from viewing anyone else’s orders.” Nobody asked for that part separately. An experienced engineer adds that restriction by reflex. The AI does not. Nothing in the prompt called for it.

That gap shows up in the same few places every time:

• Authorization checked on the frontend only. The interface hides a button or a page. The underlying API route has no server-side check. Anyone who finds the URL can call it directly.
• Database permissions left at their platform default. Tools built on Supabase generate working database access right away. Row-Level Security has to be turned on separately. Leave it off, and any authenticated user, sometimes anyone at all, can read or write every row in the table.
• Secrets pasted into a prompt during setup. Once an API key is in the conversation, it often ends up hardcoded in the generated code. From there it ships straight into the public frontend bundle, where it is easy to find.
• No handling for what happens when something goes wrong. Empty fields, duplicate webhook calls, malformed input. A demo never exercises these cases, because a demo only ever runs the happy path.

None of this means the tools are broken. It means the code they produce still needs the same review any other code gets before it handles real people’s data.

What Should You Check Before Launch?

Think of it as five categories. Each one should get a clear yes or no, not a vague sense of confidence.

• Authentication. Is every protected route checked on the server, not just hidden in the interface? Do sessions expire? Could a password reset flow reveal whether an email address has an account, even without resetting it?
• Secrets and configuration. Search the deployed frontend bundle, not just the source repository, for API keys, database URLs, and tokens. A key that never appears in your code editor can still end up in the public JavaScript. Builder tools sometimes inline it during generation.
• Database access. If the backend uses Supabase, Firebase, or a similar service, confirm Row-Level Security is turned on for every table. Not just the ones that seemed sensitive at build time.
• Input handling. Submit an empty form, an oversized file, and a string with unusual characters to every input the app accepts. Note anything that crashes the server or returns more detail than a user should see.
• Deployment safety. Is there a way to roll back a bad deployment without waiting on a support ticket? Is anyone actually watching error logs? Or does a failure just sit there until a user reports it?

Answer all five with confidence, and you are ahead of most teams shipping AI-generated code. Cannot answer one? That gap is where the next decision starts.

Which Fixes Can You Make Yourself, and Which Need an Engineer?

Not every finding carries the same weight. Treating a leaked test key the same way you’d treat a broken authorization model means fixing the wrong problem first.

Reasonable to fix yourself, with care:

• Rotate any exposed key or token. Move it into environment variables instead of source code.
• Add basic input length limits and format validation on forms.
• Remove dead code, unused routes, and leftover test endpoints the AI generated along the way.
• Turn on Row-Level Security using the platform’s own default policy templates as a starting point.

Worth a second set of engineering eyes:

• Authorization logic that spans multiple user roles or tenants. A fix in one place can quietly break access somewhere else.
• Payment or webhook integrations. A duplicate event or a missed edge case has a direct financial consequence.
• Anything a compliance review, an investor’s technical diligence, or an enterprise customer’s security questionnaire will ask about directly.
• A codebase where the fixes themselves feel uncertain. That uncertainty is usually a sign the architecture needs a second opinion, not just a patch. Some founders solve this on an ongoing basis with a fractional CTO rather than a one-time audit.

The line is not about how much code is involved. It is about how confident you are that fixing one thing will not quietly break another.

What Does a Professional Vibe Coding Audit Actually Involve?

A checklist tells you what to look for. An audit is the process of actually looking. It goes further than a scanner or a quick manual pass through the code.

This looks more like a senior engineer reviewing a contractor’s pull request than running a scanner and reading the output. The scanner catches known patterns. The manual read catches the business-logic gap that only shows up when someone tries something the app’s builder never anticipated.

What Should Be in the Audit Deliverable?

The output that actually helps you decide what to do next is not a spreadsheet of every flagged line. It is a short, prioritized document built around three things:

• A plain-English summary. Two paragraphs on what the actual risk is and what the recommendation is, written for whoever is making the go or no-go call, not just for the engineering team.
• Critical findings, ranked. The three to five issues that genuinely block launch, distinguished clearly from the lower-priority items that can be scheduled for after go-live.
• A fixed path, not just a problem list. Each critical finding paired with what it would take to resolve it, so the decision in front of you is concrete: fix this before Friday, or accept the risk with eyes open.

An audit that hands back forty flagged items with no ranking is not more thorough. It is just harder to act on.

Why Choose iTechnolabs

iTechnolabs holds ISO 27001:2013 and ISO 9001:2015 certification and has delivered 500+ apps across 50,000+ end users. Our engineering teams in Markham, Calgary, and Ottawa treat every AI-assisted codebase the same way they treat any code they did not write line by line: reviewed against the same functional, security, and architecture standards used on every custom software project we deliver, before it ships to real users.

Conclusion

Vibe coding got your product from an idea to something people can click through. That speed is real. What it did not do is add the layer of protection an experienced engineer applies by habit. Checking permissions on the server, not just the interface. Assuming every input is hostile until proven otherwise. Building for the version of your app with a thousand users, not one.

None of that means starting over. Most vibe-coded apps do not need a rebuild. They need a focused review, one that separates what can be patched this afternoon from what needs an engineer to look at the architecture first. The Escape research makes the scale of the gap concrete. Thousands of live apps, most built by people who had no reason to know Row-Level Security was even a setting to check.

It is recommended to know what is actually in your codebase before someone else finds out for you. That someone could be an investor’s diligence team, an enterprise customer’s security questionnaire, or a researcher scanning the public web the way Escape did. A vibe coding audit service run before launch or before a funding conversation costs a fraction of finding out the hard way.

Frequently Asked Questions

1. How much does a vibe coding audit cost?

A focused security and architecture audit typically runs $2,000 to $8,000, depending on app size and how many integrations and user roles it handles, per iTechnolabs’ published MVP cost breakdown. That is a fraction of the $25,000 to $150,000 a full production rebuild costs, which is exactly why the audit happens first.

2. How long does a professional vibe coding audit take?

A focused audit of a small to mid-sized app typically takes one to five days for a senior engineer, depending on how many user roles, integrations, and data types the app handles. Larger or multi-tenant applications with payment or healthcare data usually take longer to review thoroughly.

3. Can I fix vibe coding security issues myself without hiring anyone?

Some issues are safe to fix yourself, including rotating leaked API keys, adding input validation, and turning on default Row-Level Security policies. Issues involving multi-role authorization, payment logic, or compliance-sensitive data are worth a second engineering opinion before you ship the fix.

4. Do I need an audit if my vibe-coded app is still just a prototype?

Not necessarily. A personal tool, an internal demo, or a prototype that has not touched real user data yet can usually stay in exploratory mode. An audit becomes worthwhile once the app is about to handle real users, real payments, or any data you would not want exposed publicly.

5. What is Row-Level Security, and why does it matter for vibe-coded apps?

Row-Level Security is a database feature that restricts which rows a given user can read or write, rather than granting access to an entire table. Platforms like Supabase, commonly used by AI app builders, generate working database access quickly but do not always enable these restrictions by default, which can leave every user’s data visible to every other user.

6. Does using a well-known AI coding tool mean the output is already secure?

No. The Escape research scanned apps built on some of the most widely used platforms, including Lovable and Base44, and found the same categories of gaps across all of them. Tool popularity does not correlate with the presence or absence of a server-side authorization check.

7. What happens after the audit if issues are found?

You receive a prioritized list separating what blocks launch now from what can be scheduled later, along with a recommended fix path for each critical item. From there, you can choose to have your own team implement the fixes or have the auditing engineers handle the remediation directly.