How Much Does It Cost to Fix a Vibe-Coded App in 2026?
Fixing a vibe-coded app in 2026 runs about $200–$5,000 for an audit, $7,500–$40,000 to stabilize, and $50,000+ for a full rescue or rebuild. Here's why.
In 2026, fixing a vibe-coded app costs roughly $200–$5,000 for an audit, $7,500–$40,000 to stabilize an app you keep, and $50,000–$150,000 for a full rescue or rebuild, based on prices published by firms that do this work. Where you land depends less on how many lines the AI wrote than on two questions: is your data model sound, and is anyone’s data currently exposed?
Key takeaways
- Access control is the first thing to fail. The best-documented failures in Lovable-style apps are Supabase tables readable with the public key because Row Level Security was off or wrong.
- Audits are cheap; skipping them is not. Published audit prices start at $199 and rarely pass $5,000. IBM puts the global average cost of a data breach at $4.99M.
- Stabilization is the usual answer. Most AI-built apps with real users should be hardened, not rewritten. Vendor quotes cluster around $10,000–$40,000 and 2–4 weeks.
- Rebuild when the data model is wrong, not when the code is ugly.
- Prepare before you hire. Repo access, a list of what’s broken, and names (not values) of every secret will cut the cost of the first week.
What actually breaks in vibe-coded apps
Lovable, Bolt, Replit, Cursor and v0 are very good at producing a UI that works when you click through it as the owner. They’re much worse at the parts you can’t see from the browser: who can read which rows, where secrets live, and what happens when a webhook fires twice. The incidents below are all public and documented. None of them needed a sophisticated attacker.
Row Level Security that’s missing or wrong
Most Lovable and Bolt apps talk to Supabase straight from the browser using the project URL and the public “anon” (publishable) key. That’s fine by design. Supabase’s own docs say the publishable key is safe to expose because “it only reaches what Row Level Security allows”. The catch is in that last clause. If RLS is off, the public key reaches everything.
That’s exactly what happened in CVE-2025-48757. The researcher scanned 1,645 apps from Lovable’s public showcase and found 170 of them, about 10.3%, with 303 endpoints where tables could be read or written without logging in. The exposed data included emails, phone numbers, home addresses, payment and subscription details, and developers’ own API keys for services like Gemini and Google Maps.
It didn’t stop there. In October 2025 Escape published a scan of 5,600 public vibe-coded apps, mostly Lovable plus Base44, Create.xyz and Bolt. It found more than 2,000 vulnerabilities, 400+ exposed secrets and 175 instances of exposed personal data, including medical records and IBANs. Its main pattern was the same: anon keys in the JavaScript bundle pointing at Supabase tables with missing or permissive RLS.
“RLS enabled” isn’t the same as “RLS correct,” either. In February 2026 The Register reported on a Lovable-built exam platform with 16 vulnerabilities, 6 of them critical, that exposed 18,697 user records. The core bug was an inverted auth check: the code blocked the users it should have allowed and allowed the ones it should have blocked. That kind of mistake looks fine in a demo, because the person running the demo is always the owner.
Secrets in the bundle and in the wrong env vars
The second most common failure is secrets that end up somewhere public. Sometimes it’s an OpenAI or Stripe secret key pasted into a client component because the AI was asked to “make the API call work.” Sometimes it’s the Supabase service_role key, which Supabase warns bypasses every Row Level Security policy and must never ship to a browser.
Even correctly placed secrets need care. In April 2026 Vercel disclosed that an attacker who got in through a compromised third-party AI tool could read customer environment variables that weren’t marked “sensitive”. Vercel’s advice was to rotate them all. Few vibe-coded apps have a list of their secrets, let alone a rotation plan.
Platform bugs you can’t fix in your own code
Some failures aren’t in your app at all. In July 2025 Wiz found that Base44 let anyone register on a private app using only its public app_id, which bypassed SSO entirely. Wix fixed it within 24 hours. In April 2026 a researcher showed that a Lovable API regression let any free account read other users’ source code, chat histories and hardcoded database credentials on projects created before November 2025. The Next Web reported that the report had sat for 48 days.
You can’t patch your vendor, but you can limit the blast radius. Keep real secrets out of source code and chat prompts, and rotate anything that was ever pasted into the builder.
AI agents with production access
In July 2025 a Replit agent deleted a production database during an explicit code freeze, wiping records for more than 1,200 executives and about 1,190 companies, then told the user a rollback wouldn’t work. It would have. Replit has since separated development and production databases. The lesson for your own setup still applies: if an agent can reach prod, so can its mistakes. And if you’re on Supabase’s free plan, there are no automatic daily backups to restore from.
Code that works but can’t be changed
The least dramatic failure is the most expensive one. Veracode tested more than 100 LLMs on 80 coding tasks and found that 45% of the generated code introduced a security flaw, a rate that hadn’t improved as models got better at writing code that compiles. GitClear’s analysis of 211 million changed lines found that copy-pasted code rose from 8.3% to 12.3% of changes between 2021 and 2024, while refactoring fell from 25% to under 10%.
In an AI-built app this shows up as the same Supabase query written six slightly different ways, auth checks in some components but not others, and no tests. Every new prompt fixes one thing and breaks two others. That’s the point where founders start looking for help.
What it costs: audit vs. stabilization vs. rebuild
There’s no industry survey of “vibe-code rescue” prices yet, so the ranges below come from what firms publish on their own pricing pages. All of these are vendor numbers. Treat them as market signals, not benchmarks.
| Path | What you get | Published price range | Typical timeline |
|---|---|---|---|
| Audit | Written findings, ranked risks, a fix plan | $199 for a small MVP (Valletta); from $1,400 (Teyrex) | 2–7 days |
| Targeted fix | One area: RLS policies, Stripe, auth, deploys | $1,500–$3,500 per integration; $2,500–$5,000 for a security audit with patched policies (Afterbuild Labs) | Days to 2 weeks |
| Stabilization | Security fixes, error handling, tests on critical paths, CI/CD, monitoring | $7,500–$15,000 for a “full production pass” (Afterbuild Labs); $10,000–$40,000 for audit plus refactoring and hardening (Teyrex) | 2–4 weeks for apps under 50K lines (Teyrex) |
| Rescue or rebuild | Re-architected or rewritten app, migrated data | $50,000–$150,000 (MetaCTO); $40,000–$120,000 for a new custom MVP (Keyhole Software) | 1–4 months |
Audit: $200–$5,000
An audit is a senior engineer reading your code, your database policies and your deploy setup, then telling you what’s dangerous, in what order. The cheap end covers a single-feature MVP. The upper end covers a multi-tenant SaaS with payments, or pre-fundraise diligence.
A useful audit tells you three things: what’s exposed right now, what will break at 10x users, and whether the app is worth keeping. If a report doesn’t answer the third question, you’ve paid for a lint run.
Stabilization: $7,500–$40,000
This is the most common outcome, and usually the right one. The app’s screens and flows stay as they are. What changes is underneath: RLS policies rewritten and tested, secrets moved server-side and rotated, payment webhooks verified and made idempotent, error tracking and backups switched on, and tests written for the paths that make money.
The spread in price mostly reflects how many distinct systems you have (auth, payments, email, file storage, AI calls) and whether the data model needs migrations. One Supabase project with clean tables is at the low end. Three sources of truth for “who is a paying customer” is at the high end.
Rescue or rebuild: $50,000 and up
A rebuild means keeping the product and the data while replacing most of the code. It costs about as much as building the app properly the first time, because that’s what it is. Done right, it also includes migrating your existing users and their data, which is the part that turns a 6-week estimate into 10.
The cost of doing nothing
The comparison founders usually skip is against a breach. IBM’s 2026 report puts the average cost of a data breach at $4.99M. A seed-stage startup won’t lose that much in direct costs, but under GDPR you have 72 hours to notify your regulator once you know personal data leaked. “We didn’t know RLS was off” isn’t a defense. Against those numbers, a $1,500 audit is cheap.
Refactor or rebuild: how to decide
The instinct after seeing a messy AI-generated codebase is to start over. Usually that’s wrong. Joel Spolsky’s argument from 2000 still holds: the ugly code contains every bug fix and edge case you’ve already paid for. That applies even when the “you” who paid was a prompt.
Here’s the rule we use: rebuild when the data model is wrong. Refactor when the code is wrong. Code can be fixed one file at a time while the app keeps running. A broken data model can’t, because every feature sits on top of it.
| Signal | Points to refactor | Points to rebuild |
|---|---|---|
| Data model | Tables map to real things; ownership is clear (user_id or org_id on every row) |
No tenant column; the same entity stored in several places; JSON blobs holding relational data |
| Access control | RLS is missing but could be added table by table | Authorization only exists in the UI, and the schema can’t express “who owns this” |
| Paying users | You have them, and their data must survive | None yet, or a handful you can migrate by hand |
| Core flows | Mostly work; bugs are at the edges | The main flow fails in normal use |
| Platform | The stack can handle your next year (Supabase, Postgres, Next.js) | You need something the platform can’t do, like long-running jobs, complex permissions or on-prem deployment |
| Team plan | You’ll keep shipping with AI tools plus a reviewer | You’re hiring engineers who need a codebase they can own |
Two practical notes. First, a hybrid is common: keep the database and auth, and rewrite the frontend or the server functions around them. Second, don’t decide before the audit. The first hour of reading the schema answers this question better than any amount of clicking through the app.
What to prepare before hiring someone
You can cut a day or more off any engagement, and avoid paying senior rates for detective work, by having these ready:
- Code access. Connect Lovable or Bolt to GitHub and share the repo, or export it. If you use Cursor, make sure the latest code is actually pushed.
- Backend access. Invite the engineer to your Supabase or Firebase project with the lowest role that lets them read schema and policies. Don’t email keys.
- A secrets inventory. List the names of every API key and env var, and where each one is set: Vercel, Netlify, Supabase, the builder’s own secrets panel. Plan to rotate them all after the work is done.
- A broken-things list. Five to ten items, each with steps to reproduce and how much it matters to revenue. “Login sometimes fails” is a start. “Google login fails for users who signed up with email first” saves hours.
- Your real numbers. Active users, paying users, the kinds of data you store (emails, payments, health, kids), and the countries your users are in. These decide how much of the compliance work actually applies to you.
- Accounts and owners. Who owns the domain, DNS, Stripe account, app store accounts and email sender? Engagements stall for days on “my co-founder has the Stripe login.”
- Constraints. A launch date, a fundraise, an enterprise customer’s security questionnaire. Say so up front, because it changes what gets fixed first.
- The prompts, if you have them. Lovable and Bolt chat histories are messy, but they explain why things are the way they are. That context is worth having.
Then ask anyone you’re considering three questions. Will you tell me if this should be rebuilt rather than fixed? What exactly do I get at the end of the audit? Is the audit fee credited if I hire you for the fix? A good firm will answer all three in writing.
If you want us to look at it
If your app has real users and you’re not sure what’s exposed, start with an audit. Ours is the AI-App Rescue Audit: $1,490 fixed, delivered in 72 hours. It covers RLS and access control, secrets, payments, infrastructure, and a straight refactor-or-rebuild recommendation. If you go ahead with a Stabilization Sprint (from $7,500 for two weeks), the audit fee is credited toward it.
If you’d rather check things yourself first, work through our production-readiness checklist for AI-built apps. It’s the same list we start from. And if you just want to talk it through, book a call.