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HYV-2026-014·Production-readiness audit·7 findings

Critical2High2Medium2Low1
#FindingSeverity
01Any signed-in user can read every other user's recordsCritical
02Database service key is shipped in the client bundleCritical
03Uploaded files are readable by anyone with the URLHigh
04No rate limiting on login or password resetHigh
05Dashboard issues 60+ queries per page loadMedium
06No error tracking or alerting configuredMedium
07Security headers are not setLow

Sample report — see all seven findings ↓

  • No call required
  • Read access only
  • NDA on request
  • Report is yours to keep
  • No upsell attached

01/The honest answer

Can you ship a vibe-coded app?

Yes. Plenty of good businesses do.

The problem is narrower than the internet suggests. AI finishes the feature and skips everything around it — and none of what's missing makes your app look broken. That's the whole trap.

what-you-actually-shipped.diff+5 −5
+Working screens and flows
+A database and the queries against it
+Login and signup that function
+File upload that works first time
+A deploy that goes live
−Rules on who may read which row
−Keys kept out of the browser bundle
−Storage locked to the right people
−Limits on login attempts
−Any alert when it breaks at 3am

Everything below the gap is findable by reading the code.

02/What it has cost

These aren't hypotheticals.

Two independent sources each, with the publication's own headline, so you can check every one.

4,000

fake users invented to hide it

July 2025· AI-built

An AI agent deleted a live production database, then invented 4,000 users to cover it

Replit's AI agent wiped a live database holding roughly 1,200 executive and 1,196 company records — then generated thousands of fake profiles and reported success, so nobody noticed straight away.

Root cause

The agent could write directly to production while building. No separation between the sandbox and the real data, so one wrong command reached live records.

Cybernewscybernews.com

AI coding tool wipes production database, fabricates 4,000 users, and lies to cover its tracks

The Registertheregister.com

Vibe coding service Replit deleted user's production database, faked data, told fibs galore

1 in 10

apps on Lovable's own showcase leaked data

2025–2026· AI-built

One in ten apps on Lovable's own showcase was leaking user data

Researchers tested 1,645 apps featured on Lovable's marketplace. About 170 exposed other users' data through the same flaw. Tracked as CVE-2025-48757.

Root cause

The AI wrote the database and the queries but not the policies deciding who may read which rows. Invisible in testing — one user reading their own data looks identical to one reading everyone's.

The Next Webthenextweb.com

Lovable left thousands of projects exposed for 48 days, and the vibe coding security crisis is only getting worse

The Registertheregister.com

Lovable-hosted app littered with basic flaws exposed 18K users, researcher claims

72,000

images exposed, incl. 13,000 photo IDs

July 2025

A misconfigured storage bucket exposed 72,000 images — including 13,000 selfies and photo IDs

Tea, a dating-safety app, left a storage bucket publicly readable. A second exposure days later covered roughly 1.1 million private messages.

Root cause

The bucket was reachable without authentication. Nothing was hacked — the files were served to anyone who asked, because no access rule had been written.

What it cost

Ten class actions, at least four seeking $5m+. Apple pulled the app from the App Store in October 2025.

NBC Newsnbcnews.com

10 women have sued the Tea app after user photos were hacked and leaked online

American Bar Associationamericanbar.org

Cloud Misconfiguration and the Private Right of Action: A Technical and Legal Analysis of the Tea App Data Breach

The third was a misconfigured storage bucket, not a confirmed AI-built app. It's here because it's the same class of failure — a data store shipped without access rules — and it's the one with reported cost.

03/What you get

Four things, against every finding.

Not a list of scary words. Each item is written so you can act on it without calling us back.

Every finding ranked twice

Severity and difficulty, not severity alone. A critical issue a bored teenager can hit is a different problem from one needing real resources, and only the pair tells you which is which.

A written exploit scenario

Exactly how someone reaches your data, in plain sentences. You can judge the risk yourself instead of taking a severity label on trust.

Two fixes for each one

What to do this week to close it, and the durable change that stops it coming back — usually a test or a default, so it cannot recur silently.

An effort estimate

Hours or days against each fix, so you can plan the work, price it out, or hand the list to whoever built it.

04/The deliverable

What you actually receive.

The format security firms use — scope, a summary you can take in at a glance, then every finding with its exploit scenario and the fix. This is the first page of a real one.

Production-readiness audit

Example SaaS

Next.js 15 · Supabase · Vercel · ~14,000 lines

REF
HYV-2026-014
PREPARED BY
Hyvo
TURNAROUND
5 business days

7 findings

Critical2High2Medium2Low1

1·Scope

Reviewed
Application code, database schema and policies, storage rules, auth flow, deploy configuration
Not reviewed
Third-party SaaS you do not control, native mobile builds, penetration testing
Method
Manual review by a senior engineer, supported by static analysis

2·Findings summary

#FindingCategorySeverityDifficultyEffort
01Any signed-in user can read every other user's recordsAccess ControlsCriticallowHalf a day
02Database service key is shipped in the client bundleData ExposureCriticallowOne day, plus rotation
03Uploaded files are readable by anyone with the URLData ExposureHighlowHalf a day
04No rate limiting on login or password resetAuthenticationHighmediumHalf a day
05Dashboard issues 60+ queries per page loadPerformanceMediumhighHalf a day
06No error tracking or alerting configuredObservabilityMediumhighTwo hours
07Security headers are not setConfigurationLowhighOne hour

3·Findings in detail

3.1HYV-001CriticalLow — trivial to exploit

Any signed-in user can read every other user's records

Target

supabase/orders, profiles, messages

Description

None of the three tables has row-level security enabled. The application filters by user ID in the front-end query, but the API accepts whatever filter it is given — the database itself applies no ownership check.

Exploit scenario

A user opens the network tab, copies their own dashboard request, changes the user ID and replays it. They receive another customer's full order history. No tooling, no credentials, no privilege escalation — the API answers the question it was asked.

Remediation

NowEnable RLS on all three tables and add owner-match policies so the database refuses the request rather than trusting the client.

DurableAdd a CI test asserting user A cannot read user B's rows, and make RLS-enabled the default for every new table.

Effort

Half a day
3.2HYV-002CriticalLow — trivial to exploit

Database service key is shipped in the client bundle

Target

app/lib/db.ts

Description

The service-role key — which bypasses every access rule — is imported into a component that renders client-side. It is present in plain text in the JavaScript any visitor downloads.

Exploit scenario

An automated scanner crawls the site, extracts the key from the bundle, and reads, alters or drops the entire database from the attacker's own machine. Because the requests carry a legitimate key, nothing in the logs looks unusual.

Remediation

NowMove every privileged call behind a server route and rotate the key immediately — assume it is already compromised.

DurableAdd a build step that fails if a service key is reachable from client code, so this cannot recur silently.

Effort

One day, plus rotation

HYV-2026-014 · Confidential

Excerpt — every finding is written out at this depth

Composite example. No client's findings are reproduced, and nothing from a codebase we review appears anywhere on this site.

05/How it works

Four steps, one of them yours.

  1. 01

    You send a link

    A URL, or repo access. No questionnaire, no discovery call.

  2. 02

    A senior engineer reads it

    Not a scanner. Someone who has shipped this stack reads the code, schema, access rules and deploy config.

  3. 03

    You get the report

    Findings ordered by risk against effort. Five business days.

  4. 04

    You decide

    Fix it yourself, hand it to your developer, or ask us. Most people do the first.

SCOPE: Application code, database schema and policies, storage rules, auth flow, deploy configuration. NOT INCLUDED: Third-party SaaS you do not control, native mobile builds, penetration testing.

06/Why not just run a scanner

A scanner reads your dependencies. It can't read your logic.

Most of what actually breaks an AI-built app is a decision, not a known CVE — and decisions are invisible to pattern matching.

 Hyvo auditAutomated scannerLaunch and find out
Reads your actual authorization logicYesNoNo
Explains how each issue gets exploitedYesNoNo
Ranks by risk against effort to fixYesPartlyNo
Catches what no test would fail onYesNoNo
Written by someone who has shipped this stackYesNoNo
CostFree · 5 days$30–200 a monthTea paid ten class actions

07/From clients who took it

What they said afterwards.

“They performed a free technical audit, which identified a number of opportunities for us to improve our platform before we launched, then they took our prototype and made it into a production-ready application, refining our architecture, our deployment processes and getting our platform ready for real-world use, giving us the confidence to proceed with launch with a scalable and reliable product.”
Team Zippy · Zippy
“Hyvo played a key role in taking our product from development to launch. They performed a full technical audit for us for free, advised us on how to improve our cloud setup, and gave us some hands-on tips on scalability and deployment. They also helped us throughout the Play Store publishing process, and our application was published without any hassle. They were very knowledgeable and helpful, and made the whole process a lot easier.”
Prasad Magdum · Founder, Bookr

08/Questions people ask first

Before you send anything.

What does it cost?

Nothing. We're a young studio and we need work we can point at, so the audit is free while we have capacity. No upsell attached to receiving the report.

Do I have to get on a call?

No. The report arrives by email and stands on its own. If you want to talk it through we will, but it isn't a condition.

Will you look at AI-generated code?

That's most of what we see. Code from Lovable, v0, Bolt, Cursor or Claude has a recognisable set of gaps, and knowing where to look makes the review faster.

Is my code safe with you?

Read access only, we ask before touching anything, and we'll sign an NDA if you send one. Nothing from your codebase appears in our examples.

What if you find nothing serious?

Then the report says so and you launch with more confidence than you had. That happens, and we'd rather tell you than manufacture a problem.

How is this different from a scanner?

A scanner finds known patterns in dependencies. It can't tell you your authorization logic trusts the client, or that your dashboard query collapses at fifty times the data.

Send us a link.

That's the whole ask. Five days later you'll know exactly where you stand — and it costs you nothing to find out.

Request the free audit

Want more than a review? Prototype → production