Vibe Coded App Security

Security testing built for apps made with AI coding tools

Applications built with Lovable, Cursor, Bolt, v0, and similar AI tools ship fast — but common security patterns are frequently missed. NeedSec understands these stacks and tests for the specific vulnerabilities that emerge from AI-generated code: broken access control, exposed APIs, missing RLS policies, and secrets left in frontend bundles.

Book Vibe Coded Security Review View Process

routes.tsschema.tssecurity.ts

TypeScript 5.5

// secure API — NeedSec

import { withAuth } from "@/lib/auth"

import { validate } from "@/lib/schema"

import { rateLimit } from "@/lib/security"

export const POST = withAuth(async (req) => {

await rateLimit(req, { max: 20 })

const body = validate(await req.json())

// parameterised — safe

return Response.json({ ok: true })

}

0 issues — ready✓ Secure

Tech Stack

Next.jsReactTypeScriptTailwindNode.jsPostgreSQL

Built-in Security

Auth & Sessions

Input Validation

Rate Limiting

SQL Injection Guard

CSRF Protection

Security Headers

Manual-led testing

Every assessment is led by a qualified security engineer — human judgment, not just automated scanning.

Evidence-backed findings

Each vulnerability includes proof of concept, reproduction steps, and a business-impact risk rating.

Actionable fix guidance

Reports are structured for developers and decision makers so remediation can start immediately.

What We Test

Focused testing against realistic attack paths

NeedSec combines manual testing, structured methodology, and business-focused reporting to identify issues that matter — not just scanner noise.

AI-generated code pattern analysis — missing auth checks and unsafe defaults

Authentication flow review — Supabase Auth, Clerk, Auth.js, and custom setups

Row-level security (RLS) policy testing — data access across user boundaries

API route authorization — missing guards, role bypass, and IDOR vulnerabilities

Environment variable and API key exposure in frontend bundles and source maps

Database access patterns — direct client queries and SQL injection risk

Prompt injection in AI-integrated features and chatbot components

Serverless and edge function security — Vercel, Netlify, and Cloudflare Workers

Third-party library and dependency security review

Frontend security — exposed secrets, unsafe rendering, and XSS risks

Supabase-specific risks — Storage, Realtime, and Edge Function misconfigurations

Sensitive data in logs, analytics events, and error boundaries

Deliverables

What you receive after every engagement

Every engagement concludes with a professional report package — written to drive action across your technical and business teams.

Vibe coded app security report

A report covering the specific risk patterns common in AI-generated application code.

Authentication and session findings

Findings on authentication and session-handling weaknesses often introduced by AI code generators.

RLS and database access risk report

Findings on row-level security and database access control gaps.

API authorization vulnerability list

Vulnerabilities where API endpoints fail to properly enforce authorisation checks.

Secrets and credential exposure notes

Findings on API keys or credentials left exposed in code or configuration.

Severity-rated issue list

Every issue ranked by severity so fixes can be prioritised correctly.

Remediation guidance for AI-built stacks

Fix guidance written for teams working with AI-assisted or AI-generated codebases.

Retest validation

Confirmation that previously identified vulnerabilities have been fixed and no longer present after remediation.

Need help scoping this assessment?

Share your target systems, business goals, and timeline. NeedSec will help define the correct scope and testing approach.

Get a Quote