Is Vibe Coding Safe? Security Risks of AI-Generated Code

Quick answer: Vibe coding is safe only with a security layer the AI doesn't provide. SimplyScan's scans of 177 AI-built apps show 33% carry a high or critical issue. AI often prioritizes functionality over safety, leading to exposed secrets and broken auth. Prompt for security explicitly and scan every app before launch.

By Paula C · Kraftwire Software

Vibe coding is safe only if you treat AI as a junior developer who ignores security unless forced to prioritize it. To make vibe coding safe, you must explicitly prompt for security, manually review generated logic, and use automated scanners to catch exposed secrets or broken access controls before shipping. In SimplyScan's scans of 177 AI-built apps, 33% (58 apps) carried at least one high or critical severity issue, proving that the "vibe" alone is not a security strategy.

What Is Vibe Coding and Why Does It Matter for Security?

Vibe coding is a development paradigm where natural language prompts replace manual syntax. Instead of writing useEffect hooks or SQL queries, you "vibe" with an AI agent · using tools like Lovable, Bolt.new, Cursor, or Windsurf · to iterate on a vision until the app works.

While this speed is revolutionary for founders, it creates a "security-by-accident" culture. Vibe coding security is the practice of testing and hardening applications produced by AI coding tools like v0 and Replit. Without this hardening, you are essentially shipping code that has never been peer-reviewed by a human who understands adversarial risk.

The danger isn't the AI itself, but the lack of friction. When it takes 30 seconds to deploy a feature, security reviews are often the first thing skipped. According to SimplyScan's proprietary data, while the average security score for these apps is 86 out of 100, the presence of critical flaws in one-third of the sample suggests that a high "average" score can mask catastrophic single points of failure.

Why Does AI-Generated Code Have Security Gaps?

1. Optimization for "The Happy Path"

AI models are trained to satisfy the user's prompt. If you ask for a "working login," the AI provides the shortest path to a successful login. It rarely considers the "unhappy path" · what happens when an attacker injects a malicious payload or attempts to bypass a client-side check. This leads to code injection risks that are often invisible to the person prompting the code.

2. Training on Legacy and Insecure Code

Large Language Models (LLMs) are trained on vast repositories of public code, much of which is outdated or written by developers who didn't prioritize security. If an AI sees thousands of examples of hardcoded API keys in GitHub tutorials, it learns that hardcoding keys is a "standard" way to make things work. This is why finding exposed secrets is a top priority for any AI-built project.

3. The "Prompt Gap"

Most vibe coders describe features, not constraints. A prompt like "build a user profile page" results in a page that displays user data. It does not inherently include Row Level Security (RLS) or server-side authorization unless those requirements are part of the "vibe." SimplyScan found that architecture issues (medium severity) appeared in 81 out of 177 apps (46%), often stemming from these missing constraints.

4. Lack of Contextual Awareness

While tools like Windsurf and Cursor have better project awareness than basic chat interfaces, they still struggle to understand the full security perimeter of your infrastructure, such as how your Supabase instance interacts with your Vercel deployment. They may suggest a configuration that works in isolation but creates a CORS vulnerability or an open redirect in production.

The 6 Most Common Vibe Coding Vulnerabilities

1. Exposed API Keys and Secrets

This is the most frequent critical finding. AI often places secrets in .env files that get committed to Git, or worse, directly in frontend components. In SimplyScan's corpus, we frequently find OpenAI, Stripe, and Supabase service-role keys exposed in client-side bundles.

• The Risk: Attackers can drain your API credits or access your database.
• The Fix: Use environment variables and ensure secrets are only accessed in server-side routes or Edge Functions. Use a secret scanner to verify your build.

2. Broken Access Control (Bypassing RLS)

AI-built apps often rely on the frontend to "hide" data. However, if the backend or database doesn't enforce permissions, anyone with a tool like Postman can access your data.

• The Risk: Unauthorized data access or deletion.
• The Fix: Implement Supabase RLS or equivalent database-level security. Never trust the client to tell you who the user is. Check our broken access control checklist for common bypasses.

3. Code Injection and XSS

AI sometimes generates code that uses dangerouslySetInnerHTML or concatenates strings into SQL queries to "make things work" quickly.

• The Risk: Attackers can execute malicious scripts in your users' browsers or run unauthorized database commands.
• The Fix: Follow an XSS prevention guide and use parameterized queries for all database interactions.

4. Insecure Session Management

Vibe-coded apps often store JWTs in localStorage, which is vulnerable to XSS. They may also lack proper logout logic that invalidates the session on the server.

• The Risk: Session hijacking.
• The Fix: Use httpOnly cookies and follow a JWT security guide to handle tokens safely. You can test your tokens with our JWT debugger.

5. Missing Security Headers

Most AI tools don't automatically configure your next.config.js or vercel.json with security headers like CSP, HSTS, or X-Frame-Options.

• The Risk: Increased vulnerability to clickjacking and protocol downgrades.
• The Fix: Use our security headers tool to check your site and apply a CSP guide.

6. Vulnerable Dependencies

AI may suggest outdated npm packages that it "remembers" from its training data. These packages often contain known CVEs.

• The Risk: Supply chain attacks.
• The Fix: Regularly run npm audit and use SimplyScan to detect known vulnerabilities in your stack.

The Ultimate Vibe Coding Security Checklist

To ship AI apps safely, you need a repeatable process. Use this vibe coding security checklist before every major deployment:

• Secret Audit: Search your codebase for strings like sk-, key=, or password. Use a secret scanner to ensure no keys are in the frontend.
• Auth Verification: Log in as User A and try to access User B's data via an API URL. If it works, your access control is broken.
• Database Hardening: If using Supabase, ensure every table has RLS enabled. Use our Supabase security checklist for guidance.
• Input Sanitization: Test every form field with special characters like <script> or ' OR 1=1.
• Security Headers: Ensure Content-Security-Policy is active to mitigate the impact of any accidental XSS.
• Automated Scan: Run a SimplyScan report. It takes 30 seconds and checks 8 dimensions, including AI-specific risks and GDPR compliance signals.

How to Prompt for More Secure Code

You can improve the "vibe" by changing how you talk to the AI. Instead of asking for a feature, ask for a secure feature.

• Bad Prompt: "Create a contact form that saves to my database."
• Good Prompt: "Create a contact form with Zod validation, rate limiting on the API route, and ensure the database insert uses a service-role key only on the server side. Do not expose any keys in the client."

By adding constraints to your prompts, you force the AI to select higher-quality patterns from its training data. For more tips, see our guide on AI security prompt injection and how to defend against it. Using prompt engineering for secure web apps is the most effective way to reduce technical debt at the source.

Beyond Security: Speed, SEO, and AI Visibility (AEO)

Security is the foundation, but a "safe" app that no one can find is a failed product. Vibe-coded apps often struggle with Speed and Performance. SimplyScan's data shows that speed issues (medium) appeared in 124 out of 177 apps (70%), while high-severity speed issues affected 9% (16 apps). This often happens because AI adds heavy libraries for simple tasks.

Furthermore, you must optimize for Answer Engine Optimization (AEO). If AI engines like Perplexity or ChatGPT can't "read" your site because of poor semantic HTML or broken metadata, your vibe-coded app won't rank in the new era of AI search. SimplyScan's free scan includes an AI visibility (AEO) check to ensure your site is discoverable.

The Bottom Line: Trust but Verify

Vibe coding is the future of development, but it requires a "Trust but Verify" mindset. The AI is your co-pilot, not your security officer. Security issues (medium) appeared in 20% of scanned apps, and high-severity security issues were found in 11%. These aren't just theoretical risks; they are real vulnerabilities in live applications.

By combining the speed of tools like Bolt and Lovable with the rigorous checking of SimplyScan, you can ship faster than traditional developers without the catastrophic risks of unreviewed code.

Scan your vibe-coded app for free →

FAQ

Is vibe coding safe for founders with no technical background?

Vibe coding is safe only if you use automated guardrails. While you don't need to write code, you must understand the risks of exposed secrets and broken auth. SimplyScan's scans of 177 apps show that 33% have high or critical flaws. Founders should use a security audit checklist and run automated scans before every launch to compensate for a lack of manual code review.

How do I know if my AI-generated app is leaking data?

The most common sign of data leakage is "Broken Access Control." You can test this by trying to access private API endpoints without being logged in. SimplyScan detects missing security headers and exposed API keys in ~30 seconds. If your app uses Supabase, ensure you follow RLS policies to prevent one user from seeing another's data.

Can I rely on Cursor or Windsurf to write secure code?

No. While Cursor and Windsurf are advanced, they optimize for functionality. These tools are excellent for building, but they do not replace a security scanner. Always verify the output, especially for authentication logic and database queries. SimplyScan's data shows 11% of AI-built apps still contain high-severity security issues despite using these tools.

What are the most common security risks in Bolt.new and Lovable apps?

The most frequent risks include exposed Supabase anon/service keys, missing CSRF protection, and lack of input validation. These platforms are powerful, but the "vibe" often skips the boring but essential security configurations required for production-grade software. SimplyScan found that 20% of AI-built apps have medium-severity security issues that could lead to data exposure.

How does SimplyScan help with vibe coding security?

SimplyScan provides a one-click health grade across 8 dimensions, including security, speed, and AI visibility (AEO). It detects exposed API keys, weak RLS, and XSS risks that AI tools often miss. With two free rescans and a verified security badge, it helps vibe coders prove to their users that their AI-generated application is safe and professional.

Is it possible to optimize vibe-coded apps for AI search engines?

Yes, this is called Answer Engine Optimization (AEO). Vibe-coded apps often have "thin" content or poor metadata that makes them invisible to AI crawlers. By using SimplyScan's AEO guide, you can ensure your app's architecture is readable by LLMs, helping you rank in AI-driven search results while maintaining a secure and fast user experience. Our scan includes a dedicated AI visibility check for this purpose.