Vibe coding is safe with guardrails, not automatically. Vibe coding means describing what you want in plain language and letting an AI model write the code for you.
In fact, a 2026 Carnegie Mellon benchmark called SusVibes found that only about 10.5% of AI-generated solutions were actually secure, even when they worked exactly as intended. That gap between “it works” and “it’s safe” is what this article walks you through, five concrete checks before you trust what the AI built.
Key takeaways:
- Vibe coding is safe when the five checks get run before launch: project scope, prompt history, high-risk features, exposed secrets, and developer escalation; not by default.
- The two failure points research keeps finding: prompt leakage and missing access controls
- Static sites carry little risk; logins, payments, and shared customer data carry a lot
- Coderick AI handles authentication, hosting security, and version control by default, but a human still needs to check the rest
What “safe” actually means for vibe coding
Whether vibe coding is safe depends on one thing: whether the output gets reviewed before it goes live.
Research from Invicti, which generated and analyzed more than 20,000 vibe-coded web applications, found that AI models have gotten noticeably better at avoiding classic vulnerabilities like SQL injection and cross-site scripting. That’s genuinely good news. But other flaws remain stubbornly common: hardcoded secrets, reused credentials, and predictable endpoints, the kind of issues that don’t require a sophisticated attack, just someone who knows where to look.
That’s the plain-English version of what the CMU study found too. Two well-designed studies, testing different things, landing on the same point: this is why the rest of this article is a review process, not a verdict on the technology.
Why “it works” isn’t the same as “it’s secure”
Here’s the reason this gap exists: coding agents are optimized to eliminate errors, not to understand what caused them. The model is graded on “does this run without crashing,” not “does this correctly decide who’s allowed to see what.”
Here’s what that looks like in practice. In May 2025, a security researcher found that more than 170 apps built on a popular vibe coding platform had a shared flaw: their databases were wide open. Anyone, with no login required, could read, edit, or delete any customer’s data in any of those apps. Each one had already been tested and shipped by its builder, because on the surface, everything looked fine.
That’s the gap between two kinds of testing:
- Happy path: using the app the normal, intended way. Logging in as yourself, checking out with a real card, uploading a real file.
- Unhappy path: someone deliberately trying to do something they shouldn’t. Logging in as one person, then pulling up someone else’s data.
Passing your own testing only proves the happy path works. It says nothing about the unhappy path, and that’s exactly what a review step catches and a demo doesn’t. The admin panels and customer data check later in this article walks through a simple way to test for this yourself.
See our vibe coding glossary for any other unfamiliar terms.
The 5 vibe coding security checks before you launch
The 5 checks below turn that review process into something concrete you can actually run yourself, or know when to hand off.
1. Size up your project’s security needs before you build
Not every build carries the same risk. First, figure out what you’re actually working with.
Ask yourself three questions:
- Does it touch payments, personal data, or logins?
- Is it public-facing, or just for your own internal use?
- Will more than one customer or organization use it, each expecting their own data kept separate?
A quick example: say you’re building a booking system for a small physio clinic. Clients log in, pick a time slot, and pay a deposit online.
Run it through the three questions: it touches payments (yes), it’s public-facing (yes), and there’s no need for row-level isolation since only one clinic uses it (no). Two out of three high-risk answers puts this build solidly in the high-risk category below. Compare that to a simple portfolio site with a contact form: none of the three questions apply, so it sits at the low-risk end.
Low-risk builds
These sit at the low end of the risk scale:
- Static or brochure sites: worst case is defacement or a spammy contact form. There’s nothing sensitive stored to begin with.
- Internal tools used only by your own team: often treated as safe by default because they’re not public. But they still touch business data, client names, numbers, internal documents, worth protecting even behind closed doors.
What to do: run through all 5 checks below once before launch. Most will take a minute or two to confirm, since there’s little exposure to begin with.
High-risk builds
- Customer-facing apps with accounts and logins
- Anything handling payments or checkout
- Multi-tenant apps, where several customers share one system but should only see their own data
Logins and payments introduce authentication, sessions, and financial data, exactly where research shows AI-generated code concentrates its access-control failures. Multi-tenant apps are the easiest to underestimate: they look like a normal single-user app in testing, then silently expose one customer’s data to another if row-level isolation isn’t enforced.
What to do: run every check below, no skipping. Treat Check 3 (feature review) and Check 5 (developer escalation) as non-negotiable. If payments or shared customer data are involved, get a developer to confirm Check 3’s access-control questions instead of answering them yourself.
If this sounds like your project, read what vibe coding actually is before going further. The model’s limits matter more as the stakes go up.
2. Review your prompt history for leaked credentials
This check is about what you typed to build your app, and what happened to it afterward.
What you’re sending the AI (and who can see it)
A prompt isn’t just text. It can include uploaded files and connected accounts too, and each one is a different way real data ends up in scope.
Prompt leakage is the common failure here: credentials or real customer data end up sitting in chat history simply because they were typed in while describing what to build.
Where your prompt history actually lives
What happens after you hit send matters just as much as what you sent. Does the tool log conversations? For how long? Is that history used for anything beyond your own session, debugging, support access, model training?
Check the retention practice of whatever tool you’re using before you paste anything sensitive into it. Look for three things specifically: how long conversations are stored, whether that data is used to train models, and whether anyone besides you (support staff, other systems) can access it.
To make this a bit easier for you: most privacy policies cover this in a section titled something like “data retention” or “how we use your information.”
3. Code-review your high-risk features, one by one
Remember the low-risk and high-risk categories from check 1? This is where that distinction gets applied at the feature level. Even inside a single build, some individual features need a closer look than others.
The actual definition of “high-risk” here: anything that authenticates a user, gates access to something, or handles money.
In plain terms on payments specifically: the payment usually works fine. The problem is who’s allowed to trigger it isn’t properly checked.
| Feature | Risk level | What to check |
| Contact form | Low-stakes | Submit the form 5–10 times in a row quickly. If it lets every submission through with no delay or block, ask for a limit to be added |
| Login system | High-stakes | Log out, then hit the back button. If you’re still logged in and can see account data, the session isn’t ending properly |
| Payments and checkout flows | High-stakes | Start a checkout and confirm who’s allowed to trigger it. If you’re using Coderick AI’s built-in Stripe integration, card details are handled by Stripe’s own checkout page and never touch your code, so this risk is mostly about anything you built around the payment, like a custom pricing page, not the payment itself. |
| Admin panels, user accounts, customer data | High-stakes | Log in as yourself, open any page showing your own data (like an account or order page), and note the number in the address bar. Change that number by one and reload. If someone else’s data loads, that’s a real problem |
4. Check for exposed secrets and public-by-default settings
Some red flags don’t need code-reading skills to spot:
- A setting shipped public instead of private
- A secret sitting in plain view in a file that shouldn’t have it
- A permission check that’s simply missing
How common is this, really? A scan of 5,600 publicly available vibe-coded apps found:
- More than 2,000 vulnerabilities
- 400 exposed secrets
- 175 instances of leaked personal data, including medical records and bank account numbers
That’s not a fringe case. It’s the typical outcome across thousands of real, live apps.
What this looks like in the wild: researchers hacked an AI-agent social network’s database in under three minutes, exposing 35,000 email addresses, thousands of private messages, and 1.5 million API tokens. The cause wasn’t a sophisticated attack. It was a red flag like the ones above, left unchecked.
5. Check whether payments or customer data mean you need a developer
Some situations call for a developer, not a checklist:
- Handles payments with custom logic beyond a standard checkout (splitting funds between multiple parties, a custom pricing engine, anything that isn’t just “charge a fixed amount”)
- Stores personal data
- Serves multiple customers who shouldn’t see each other’s records
đź’ˇIf you’re building with Coderick AI specifically, a standard Stripe checkout, subscription, or one-time payment doesn’t need this level of developer review, that part’s already handled. Custom payment logic beyond that still does.
If your app has multiple users who shouldn’t see each other’s data, or it touches a database directly, that’s a developer-level check, not something to verify yourself. Row-level data isolation and access-control logic are the kind of thing that looks fine in a demo and fails the moment two customers use it at once. Our guide on getting started with vibe coding covers where to draw this line before you’re deep into a build.
So, is vibe coding safe? For a landing page, almost certainly. For a login system handling customer payments, only once someone’s actually checked it.
How Coderick AI reduces these vibe coding vulnerabilities
A few of the checks above are already handled by default, no need to ask for them:
- User authentication built in from the start. No need to specify it or catch it missing, removing one of the checklist’s highest-risk gaps as a manual to-do.
- SiteGround’s hosting and security stack, inherited automatically. No unconfigured server to start from, which handles the server-level security (firewalls, malware scanning, DDoS protection) that a standalone AI code generator would otherwise leave entirely up to you.
- Version control included by default. Every generated change is tracked, giving you a history to check instead of a live app with no paper trail.
- Stripe checkout built in for payments. Card details go straight to Stripe’s secure page and never touch your project’s code, closing the exact “who’s allowed to trigger this payment” gap Check 3 describes, for anything using this integration specifically.
What it doesn’t do: catch business-logic or access-control bugs elsewhere in the generated code automatically. Even with Stripe connected, it’s worth a quick confirmation on two things: that subscription cancellation is built into your customer’s experience (just ask Coderick to add it), and that your refund permissions are set the way you want them, which is usually the default.
Your Digital Alchemist, for instance, is a solo web design agency that built 15 client websites in five months with Coderick AI and won a regional design award doing it.
That’s exactly why the checks in this article matter: the tool is production-ready enough that people are already putting client work on it, which makes review habits a live concern, not a someday one.
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Frequently asked questions about vibe coding security
Whether vibe coding is riskier than hiring a freelance developer depends entirely on whether either one gets reviewed. An unreviewed AI build and an unreviewed freelance build carry similar risk; the difference is that a freelancer typically brings security judgment baked into the process, while an AI tool needs you to supply that judgment yourself.
Sometimes, if you point it at the specific issue. AI models are better at fixing a named vulnerability than at spotting one on their own, so a manual review step to find the problem first is still necessary.
Generally, yes, for the infrastructure layer. A purpose-built platform bundles hosting security and authentication by default, where a general chatbot leaves you to configure, or forget to configure, all of that yourself.
It’s almost always more expensive than catching it before launch, both in developer time and in the damage a breach can do to customer trust. Fixing an issue in a live app also means auditing what data may already have been exposed, which a pre-launch check avoids entirely.
Yes. A static site with no logins, payments, or stored customer data carries very little of the risk this article covers. The checklist above still applies, but the stakes, and the effort needed, scale down a lot.