# Internal Apps Sweep by VANDAM: Find, test and fix the apps your staff built with AI

> A register of every internal app and agent your staff built with AI, each tested for the leaks these tools are known for, fixed or switched off, and a one-page rule so people can keep building without exposing the company.

URL: https://vandam.ai/internal-apps-sweep  
Contact: hendrik@vibelab.be

# The apps your staff built probably include one that leaks.

A register of every internal app and agent your staff built with AI, each tested for the leaks these tools are known for, fixed or switched off, and a one-page rule so people can keep building without exposing the company.

[Discuss the project](https://vandam.ai/contact?topic=Internal%20Apps%20Sweep)

**$8,000** two weeks, up to 25 apps

## AI app builders ship fast. Many of their apps ship open.

- **170**
  of 1,645 Lovable apps scanned had databases readable by anyone, exposing names, payment details and API keys. [Matt Palmer](https://mattpalmer.io/posts/statement-on-CVE-2025-48757/), CVE-2025-48757, May 2025.
- **400+**
  exposed secrets and 175 cases of exposed personal data in more than 5,600 public apps built with AI app builders. [Escape](https://escape.tech/blog/methodology-how-we-discovered-vulnerabilities-apps-built-with-vibe-coding/), October 2025.
- **45%**
  of AI-generated code samples failed security tests across more than 100 models. [Veracode](https://www.veracode.com/blog/genai-code-security-report/) GenAI Code Security Report, July 2025.

## Building an app now takes an afternoon. Securing it still takes knowledge.

A sales manager builds a quote calculator in Lovable. An HR assistant asks Claude for an onboarding tracker and puts it online. Someone in finance connects a spreadsheet to an agent. Each of these is useful, and none went past IT. The tools write working code fast, and they leave the security settings to whoever is typing.

The same holes come back again and again. In March 2025 the developer [Matt Palmer](https://mattpalmer.io/posts/statement-on-CVE-2025-48757/) scanned 1,645 apps built with Lovable and found **170** whose databases let anyone read data they should not see, including names, phone numbers, payment details and API keys. In October 2025 [Escape](https://escape.tech/blog/methodology-how-we-discovered-vulnerabilities-apps-built-with-vibe-coding/) scanned more than 5,600 public apps built with AI app builders and found over 2,000 vulnerabilities, more than 400 exposed secrets and 175 cases of exposed personal data, from medical records to bank account numbers.

The cause is usually one setting. Many of these apps sit on Supabase, whose [own documentation](https://supabase.com/docs/guides/database/postgres/row-level-security) warns that “a table in an exposed schema without RLS is readable and writable by any role with a grant on it.” [Firebase](https://firebase.google.com/docs/rules/insecure-rules) warns that with open rules “anyone who guesses your project ID can steal, modify, or delete the data.” The key that unlocks the database often ships in the page itself, readable by anyone who opens the browser’s developer tools.

In February 2026, [Wiz](https://www.wiz.io/blog/exposed-moltbook-database-reveals-millions-of-api-keys) found that Moltbook, a social network for AI agents built largely with AI, had exactly this setup: a key in the page’s JavaScript gave anyone read and write access to the whole database, including 1.5 million API tokens and 35,000 email addresses. Your internal tools are smaller, and they hold your customers, your staff files and your prices.

We find these apps first, because nobody has a list. Then we test each one the way an outsider would, fix what we can in the same two weeks, move the useful ones into company accounts and switch off the ones nobody needs. The sweep ends with a rule people can follow, so building stays allowed.

## How the two weeks run.

1. Find every app and agent: We ask, and we look. A short form to every team, then the places these apps leave traces: Lovable, Bolt, Replit and Vercel workspaces, Supabase and Firebase projects, Google and Microsoft OAuth grants, browser extensions, Zapier and Make accounts and expense lines. Each app gets an owner, a purpose and a list of the data it touches. Found in week one - Quote calculator · LovableSales · customer prices
- Onboarding tracker · ReplitHR · staff files
- Expense agent · Zapier and ChatGPTFinance · card data
- Stock dashboard · CursorOperations · no personal data
- Event sign-up · BoltMarketing · unused since May
2. Test each one for the common leaks: For every app in scope we check whether its database can be read without signing in, whether keys sit in the browser, whether every page and API route checks who is asking, whether one user can see another’s records, and where its data is sent. Each finding is proven with a request anyone on your team can repeat. Onboarding tracker, page source - const supabase = createClient(url,
- 'eyJhbGciOi…service_role…')
- 'eyJhbGciOi…anon…')
- // table staff_files
- alter table staff_files enable row level security; Example. The service key in the page could read every staff file.
3. Fix, move or retire: Row-level security switched on, keys moved to the server and rotated, sign-in added through your company accounts. Apps worth keeping move into company-owned accounts with a named owner. Apps nobody uses are switched off after a warning to their maker. Every fix is tested again. Verdicts - Quote calculatorfixed, moved to company account
- Onboarding trackerfixed, keys rotated
- Expense agentdrafts only, owner named
- Event sign-upretired after notice
4. Leave a rule people can follow: One page: which tools staff may build with, which data needs IT first, how to sign in, where keys go and who to ask. With a starter project that has sign-in and security settings already in place, so the safe way is also the quick way. Builder’s rule, page one - **Build with**
  Lovable, Cursor or Claude, in the company workspace
- **Sign in**
  Company Google or Microsoft account only
- **Keys**
  In the server settings, never in the page
- **Ask IT first**
  Customer, staff or payment data

## Swept once. Swept again every month.

People keep building, and that is the point. After the sweep we can come back every month: find what is new, test it, and keep the register current, so a new app never sits open for long.

- New apps found: Workspaces, databases and OAuth grants checked again for anything built since last month.
- New apps tested: The same leak checks on every new app, with fixes applied.
- Register kept current: Owners, data and verdicts updated, retired apps confirmed off.
- Builders’ hour: A monthly session where staff bring what they are building and leave with it set up safely.

[Ask about the monthly re-sweep](https://vandam.ai/contact?topic=Internal%20Apps%20Sweep%20care)

## What you receive.

- App register: Every AI-built tool in the company, with an owner, its data and a verdict.
- Findings, fixed: Each leak with the proof, the fix applied and a re-test.
- Builder’s rule: One page and a starter setup so the next app is built safely from day one.

$8,000

two weeks, up to 25 apps

An indication from past projects. The final price can move a little with the size and complexity of your company, and we agree it in writing before we start.

For COOs, IT leads and security leads at 20–500 person companies where staff build their own tools. Useful once people outside IT ship apps that touch customer, staff or finance data.

[hendrik@vibelab.be](https://vandam.ai/contact?topic=Internal%20Apps%20Sweep)

## Where the sweep leads. Each next step has its own service.

### [Adversarial App Audit](https://vandam.ai/adversarial-app-audit)

For the one app that matters most: a deep review of its code, with the fixes attached.

**$9,600**

### [Agent Attack Audit](https://vandam.ai/agent-attack-audit)

For the agents the sweep found: planted instructions, wide scopes and exposed keys, tested and fixed.

**$8,000**

### [Team Harness](https://vandam.ai/team-harness)

Gives staff a safe, supported place to build, with the rule from the sweep built in.

**$12,800**

### [AI Act Deployer File](https://vandam.ai/ai-act-deployer-file)

Turns the app register into the AI Act file: a risk class and the duties for every system.

**$8,000**

## Before you ask.

### Will you shut down tools people depend on?

Not without warning. Each app’s maker and its users hear our verdict first. An app that leaks but is useful gets fixed or moved, not switched off. We only retire apps nobody uses or that cannot be made safe, and your IT lead decides.

### How do you find apps nobody told IT about?

We combine a short form to every team with what the systems already record: OAuth grants in Google or Microsoft, projects in the AI builders’ workspaces, Supabase and Firebase accounts paid with company cards, and automation accounts. Most apps leave several of these traces.

### Is this a ban on building with AI?

No. The sweep ends with a rule and a starter project that make building safely the easy way. Companies that ban it tend to push it into personal accounts, where nobody can see or fix it.

### What if we have more than 25 apps?

We price larger estates on the count after the first discovery day, and agree it in writing before testing starts.

### How is this different from the Adversarial App Audit?

The Adversarial App Audit goes deep on one important application. The sweep goes wide: every small tool in the company, tested for the leaks AI-built apps are known for.