Your App Works. But Is It Ready for Real Users?
AI coding tools can take you from idea to working app in days. They don't tell you what they got wrong. AI-generated code often looks correct and runs in demos, then fails under real users, real data, and real attackers.
Common signs your app needs an audit:
You're about to launch, raise funding, or onboard paying customers
You can't fully explain how your authentication or database rules work
The app slows down or breaks as users grow
Fixing one bug creates two new ones
A developer is taking over code nobody reviewed
Your API keys or database are connected directly from the frontend
A code audit tells you exactly what's risky, what's fine, and what to fix first.
Common Problems We Find in AI-Generated Code
Problem | Why It Happens | Business Risk |
Exposed API keys and secrets | AI places keys in frontend code or public repos | Stolen keys, unexpected bills, data breach |
Missing database access rules | Supabase RLS or Firebase rules left open or misconfigured | Any user can read or change other users' data |
Broken authentication | Auth logic checked only in the UI, not on the server | Unauthorized access to paid features and admin areas |
No input validation | AI assumes users send valid data | Injection attacks, crashes, corrupted data |
Duplicated and tangled code | Each prompt adds new code instead of reusing existing code | Slow development, bugs that keep coming back |
Unhandled errors | Happy-path code with no failure handling | Silent failures, lost payments, poor user experience |
Inefficient database queries | Queries that work for 10 users, not 10,000 | Slow app, rising hosting costs |
Outdated or risky dependencies | AI suggests old packages with known vulnerabilities | Security exposure, broken builds |
No tests | Tests are rarely generated unless requested | Every change risks breaking production |
What Our Code Audit Covers
Area | What We Check |
Security | Secrets, authentication, authorization, database rules, input validation, dependency vulnerabilities |
Code Quality | Structure, duplication, complexity, readability, dead code, maintainability |
Architecture | Frontend/backend separation, data flow, service boundaries, scalability limits |
Database | Schema design, access rules, indexes, query efficiency, data integrity |
Performance | Slow pages, heavy API calls, unnecessary re-renders, bundle size |
Error Handling | Failure paths, logging, user-facing errors, payment and webhook reliability |
Deployment | Environment variables, build setup, hosting configuration, production readiness |
Testing | Existing coverage and the critical flows that need tests first |
Apps Built With Any AI Coding Tool
We audit code generated or assisted by:
Claude Code · Lovable · Bolt.new · Replit · Cursor · Windsurf · v0 · Google AI Studio · GitHub Copilot · ChatGPT · Codex
Common stacks we review: React, Next.js, Vue, Node.js, Python, Supabase, Firebase, PostgreSQL, MongoDB, Stripe, Vercel, Netlify, AWS.
How the Audit Works
1. Free Scoping Call
Tell us what the app does, how it was built, and what worries you. We confirm the scope and give you a fixed price.
2. NDA and Secure Access
We sign an NDA and get read-only access to your repository. We never change your code during the audit.
3. Review and Testing
Our engineers combine automated scanning with manual review of your security, business logic, database, and architecture.
4. Findings Report
You receive a clear report with every issue rated by severity, explained in plain language, and paired with a recommended fix.
5. Walkthrough Call
We walk you through the findings, answer your questions, and help you decide what to fix first.
What You Receive
Executive summary: the overall health of your app on one page, readable by non-technical founders
Health scorecard: a rating for security, code quality, architecture, database, performance, and testing
Findings report: every issue with its location, severity (Critical / High / Medium / Low), and business impact
Code-level fixes: the problem code and the recommended corrected version
Prioritized roadmap: what to fix this week, this month, and later
Effort estimates: a rough time to fix each issue, so you can plan and budget
Walkthrough call: a live explanation of the findings with Q&A
See What You'll Receive
Every audit ends with a clear, prioritized report. Here's a preview from a sample audit of a demo SaaS app built with an AI coding tool.
Sample Audit: TaskFlow (Demo Task-Management SaaS)
Stack: React · Supabase · Stripe · Vercel
Overall Risk Rating: 🔴 High
# | Finding | Severity | Business Impact | Fix Effort |
F-01 | Supabase RLS disabled on projects table | 🔴 Critical | Any logged-in user can read all customers' projects | 1–2 hrs |
F-02 | Stripe secret key exposed in frontend bundle | 🔴 Critical | Attackers can create refunds or read payment data | 1 hr |
F-03 | Admin API protected only in the UI | 🟠 High | Non-admin users can access admin endpoints | 2–4 hrs |
F-04 | Stripe webhook signature not verified | 🟠 High | Fake payment events can unlock paid plans | 2 hrs |
F-05 | No input validation on task creation API | 🟡 Medium | Malformed data can crash pages or corrupt records | 3–5 hrs |
F-06 | Same fetch logic duplicated across 14 components | 🟡 Medium | Slower development and recurring bugs | 1 day |
F-07 | Missing index on tasks.user_id | 🟡 Medium | Dashboard slows significantly as data grows | 1 hr |
F-08 | No automated tests on signup or checkout | 🔵 Low | Future changes can silently break revenue flows | 2–3 days |
Recommended priority:
This week: F-01 to F-04 (security and payment risks)
This month: F-05 to F-07 (stability and performance)
Next quarter: F-08 (long-term reliability)
Download Full Sample Report → (link to the PDF)
Sample audit of an internal demo application, shown for illustration. Client reports are confidential.
Typical Audit Scenarios
These examples show the kinds of apps we audit, the issues that commonly surface, and what founders do with the findings.
Scenario 1: B2B SaaS Before Its First Paying Customers
Built with: Lovable + Supabase
Audit: Focused Code Audit
Situation: A solo non-technical founder built a client-reporting SaaS with Lovable in six weeks. Ten beta users loved it, and paid plans were launching in two weeks. Nobody had checked the code.
Common findings:
Row Level Security disabled on tables that store client data, so any user could read other companies' reports
Supabase service role key used inside a frontend function
Password reset flow that didn't expire old reset links
What happens next:
The critical issues are fixed in 2–3 days before launch. The founder starts charging customers knowing that their data is isolated and protected.
Scenario 2: Marketplace App Handed Over to a New Developer
Built with: Bolt.new + Next.js + Firebase
Audit: Full Code Audit
Situation: A two-sided marketplace built with AI tools had around 2,000 users. The founder hired a freelance developer to add features, but every change broke something else, and the developer quoted a full rebuild.
Common findings:
Firebase security rules allowing any authenticated user to write to any listing
The same booking logic copied across 9 files with small differences, which caused recurring bugs
Listing search loading the entire database on every page view, which drove up hosting costs
No error handling on payment confirmation, so some bookings never recorded payment
What happens next: The report shows that the app doesn't need a rebuild. Security rules and the payment flow are fixed first, and the duplicated logic is consolidated into shared modules. The developer ships features without new regressions, and the founder avoids the rebuild cost.
Scenario 3: AI SaaS Preparing for Investor Technical Due Diligence
Built with: Claude Code + Python (FastAPI) + PostgreSQL + OpenAI API ·
Audit: Full Code Audit
Situation: A two-founder startup built an AI document-analysis product largely with Claude Code. A seed investor requested a technical review before closing the round.
Common findings:
OpenAI API key committed to the Git history, still valid after being "removed"
No per-user rate limiting on AI endpoints, leaving the product open to runaway API bills
Uploaded documents stored in a publicly readable storage bucket
No logging or monitoring, so production errors went unnoticed
What happens next: The founders rotate the exposed key, lock down storage, and add rate limits and monitoring before the investor review. They present the audit report and fix log as evidence of engineering discipline instead of an unknown risk.
Code Audit Pricing
Focused Code Audit
Starting at $499 · 5–7 business days
For MVPs and early-stage apps that need a fast safety check before launch.
Security review (secrets, auth, database rules)
Top 10 prioritized findings
Findings report with severity ratings
30-minute walkthrough call
Full Code Audit
Starting at $1,499 · 2 weeks
For apps with paying users, or before funding, scaling, or a developer handover.
Complete security, code quality, architecture, database, and performance review
Full findings report with code-level fixes
Prioritized roadmap with effort estimates
60-minute walkthrough call
14 days of follow-up Q&A
Get a Full Code Audit → (Most Popular)
Final price depends on codebase size and number of integrations, and is confirmed after a free scoping call.
After the Audit: We Can Fix It Too
An audit shows you the problems. If you don't have a developer to fix them, our engineers can.
VibeRescue is our fix-and-harden service for AI-built apps. We take your audit findings, resolve the critical security issues, clean up the codebase, and make your app production-ready.
The cost of your audit is credited toward a VibeRescue project started within 30 days.
Fix My App With VibeRescue →
Frequently Asked Questions
What is an AI-generated code audit?
It's an independent review of code written with AI coding tools such as Claude Code, Lovable, Bolt, or Cursor. It identifies security vulnerabilities, bugs, poor code structure, and scaling risks, and recommends what to fix first.
How much does a code audit cost?
A Focused Code Audit starts at $499 and a Full Code Audit starts at $1,499. The final price depends on codebase size and complexity, and is fixed before work begins.
How long does a code audit take?
A Focused Code Audit takes 5–7 business days. A Full Code Audit takes about 2 weeks.
I'm not technical. Will I understand the report?
Yes. Every report includes a plain-language executive summary, and every finding explains the business impact, not only the technical detail.
What access do you need?
Read-only access to your code repository, such as GitHub or GitLab. For database and deployment checks, we may request read-only access to services like Supabase, Firebase, or Vercel.
Will you sign an NDA?
Yes. We sign an NDA before receiving any access to your code or systems.
Is a code audit the same as a penetration test?
No. A code audit reviews your source code from the inside to find root causes. A penetration test attacks the running app from the outside. For most AI-built apps, a code audit is the better first step because it both finds problems and shows exactly where to fix them.
Should I rebuild my app instead of auditing it?
Not before an audit. Most AI-built apps need targeted fixes, not a rebuild. The audit shows whether the foundation is sound, so you don't pay for a rebuild you don't need.
Can you fix the issues you find?
Yes. Through VibeRescue, our engineers can fix the issues from your audit, and your audit cost is credited toward the project.
Launch With Confidence, Not Guesswork
Find the security holes, bugs, and scaling risks in your AI-built app before your users do.