Priya spent four months building her B2B HR compliance tool on Lovable. It connects to Supabase, handles employee PII, and processes uploaded payroll documents. She has seven paying customers. Then CloudGiant Corp's procurement team sends the questionnaire.
Twenty-three pages. SOC 2 Type II. Data residency requirements. Encryption at rest and in transit. Token storage policies. A $18,000 ARR deal — her largest ever — sitting on the other side of questions she cannot answer. Two weeks later, CloudGiant goes with a competitor. Priya never hears back.
This is not a rare story. It is the default outcome for non-technical founders who built real B2B SaaS apps with AI tools and then hit the enterprise wall. The apps work. The customers love them. The security posture, invisible to everyone until it isn't, quietly kills the deals that would change everything.
Three Ways Vibe-Coded Apps Fail Security
The deal killer. Enterprise procurement exists to protect large organizations from vendor risk. When your app touches employee data, financial records, or uploaded documents, procurement requires answers about your security posture. "We built it with Lovable and it works great" is not an answer. Without a documented security audit, an OWASP compliance summary, or even a basic vendor security questionnaire response, the deal dies before legal ever sees the contract. Not because your app is insecure — it might be fine — but because you cannot prove it.
The breach you didn't know was coming. AI code generation tools are extraordinarily good at making things work and quietly terrible at security defaults. The most common pattern: authentication tokens stored in localStorage instead of httpOnly cookies. API keys hardcoded in frontend files that end up in your public GitHub repository. User-uploaded files stored with public read access in your Supabase bucket. These are not theoretical risks. They are the specific patterns that AI assistants reach for because they are easy to implement and produce working demos immediately. Until a user's session token gets scraped, their employer's payroll data walks out the door, and you are explaining GDPR violation exposure to a lawyer you just hired.
The platform rejection.** Stripe's risk team flags incorrect card data handling. Apple rejects your app for data policy violations in your privacy manifest. Firebase's terms of service prohibit storing certain categories of health data in the default configuration your AI assistant chose. These rejections arrive without warning, freeze your revenue, and require fixes that expose how much security debt accumulated silently while you were shipping features.
The 3-Hour Audit That Changes the Conversation
The good news is that a meaningful security audit for a vibe-coded app is not a six-month SOC 2 engagement. It is a structured workflow using tools that already exist, producing output that enterprise procurement teams actually recognize.
The workflow runs in four stages. First, static analysis with Semgrep scans your codebase for hardcoded secrets, insecure patterns, and known vulnerability signatures. It produces findings mapped to severity levels in under ten minutes. Second, Snyk audits your dependency tree — every npm package, every Python library — against a continuously updated vulnerability database. Third, Gitleaks and TruffleHog scan your git history for secrets that were committed and then deleted; deleted secrets in git history are still exposed to anyone who clones the repository. Fourth, a narrative analysis pass using Claude Code or GPT-4 reads the actual logic of your authentication, data handling, and API integration flows and maps findings against the OWASP Top 10 — the industry standard taxonomy that procurement teams use to evaluate vendor risk.
The output is a shareable PDF report and an embeddable security badge. Not proof that you are perfect. Proof that you looked, you found issues, you fixed the critical ones, and you can articulate your security posture in terms the questionnaire was designed to receive. That is often enough to move past procurement into a real conversation.
Why Generic Security Advice Doesn't Work for Your Stack
Here is the part that most security guides miss entirely: the specific vulnerabilities in a Lovable + Supabase + Stripe app are different from the vulnerabilities in a Bolt.new + Firebase + Plaid app. The token storage patterns are different. The data residency defaults are different. The payment data flow is different. Generic "secure your app" advice produces generic findings that do not map to the actual risk surface of what you built.
This is the gap that stack-specific security guidance fills. Knowing that you are using Lovable with Supabase Row Level Security and Stripe Connect means the audit can prioritize the exact patterns those tools produce — the specific RLS misconfiguration footguns in Supabase, the webhook signature verification patterns Stripe requires, the session handling defaults Lovable generates. The same three hours produces dramatically more actionable output when it starts from your actual stack rather than abstract best practices.
DuckDive finds the specific AI setup gaps for your stack — Lovable, Bolt, Cursor, and the 40+ niches we've mapped including exactly the B2B SaaS security compliance gap Priya hit. Get your tailored security roadmap at https://duckdive-aiciv.netlify.app.