Why 1 in 5 Vibe-Coded Applications Fail Basic Security Tests

Security risks have increased by a lot as more developers use AI-assisted coding platforms. One-fifth of organizations build on these platforms and expose themselves to security vulnerabilities. Research paints a concerning picture - 45% of AI-generated code samples don't pass security tests and introduce OWASP Top 10 vulnerabilities into production systems.

"Vibe coding" lets developers build applications faster with AI help, but proper security often takes a back seat. NYU and Stanford researchers have validated this concern. Their studies show AI-assisted coding makes exploitable flaws more likely, and 40% of generated programs contain security vulnerabilities. Most developers don't prioritize application security testing in their workflow.

This piece dives into the most common security pitfalls that plague vibe-coded applications. We'll look at client-side authentication problems, exposed API keys, and database access issues. The discussion also covers internal applications that anyone can access and weak coding practices. You'll learn everything in web application security best practices and tools that can protect your AI-assisted projects from these systemic vulnerabilities.

Client-Side Authentication Without Server Validation

Client-side authentication stands out as one of the riskiest patterns in modern web development. Attackers can easily bypass security controls when authentication logic runs in browsers instead of secure servers. Products that run authentication checks in client code but skip server-side verification leave themselves open to attacks through modified clients that skip these checks.

Hardcoded Passwords in JavaScript Files

Source code with embedded credentials creates major security risks. A hardcoded password makes password guessing much easier and lets malicious users access the system.

Default admin accounts exist with basic hardcoded passwords in many systems. These passwords stay similar across installations, and users rarely change them. Attackers find it easy to break in - they just need to look up these public default passwords to gain full admin access.

To cite an instance, see this JavaScript code example:

function verifyAdmin(password) {
 if (password !== "Mew!") {
   return false;
 }
 // Access granted to admin features
 return true;
}

This pattern creates several problems:

• Every program instance uses the same password
• Software patches become necessary to change passwords after distribution
• Anyone can see these credentials by decompiling or viewing source code
• Developers who access the code can see all passwords

LocalStorage Flags Used for Session Control

Browser storage creates serious security holes when used for authentication. LocalStorage wasn't built to be secure - it's just a simple string-based store that helps build complex single-page applications.

Cross-site scripting (XSS) attacks pose the biggest security risk with this approach. Any JavaScript code on the page can access authentication tokens or session data stored in LocalStorage. Your site becomes vulnerable if you use third-party JavaScript like jQuery, React, analytics code, or ad networks. Compromised resources let attackers steal all LocalStorage data.

There's more to worry about with LocalStorage:

• Security levels match cookies at best
• Servers can't control the storage
• Storing sensitive data like JWTs creates huge risks since they work like username/password combinations
• Attackers can make endless requests on behalf of users once they break in

JWTs and session data need the same protection as passwords or credit card numbers - keep them out of LocalStorage.

Bypassing Login via DevTools

Browser developer tools let attackers modify client-side code execution in powerful ways. Many developers build apps that run authentication checks only in JavaScript, making them easy to bypass.

Attackers commonly use these techniques:

1. Network tab interceptors to change response data
2. Breakpoints to disable JavaScript functions
3. Console commands to overwrite global authentication functions
4. DOM element manipulation to show protected content

A developer found they could change the frontend to skip user credential checks when their backend failed, highlighting how easily attackers could do the same. Another developer showed how a simple console command could bypass security: function check(){return true;}.

The rule for client-side authentication remains clear: determined attackers can bypass all client-side authorization and authentication controls. Server-side validation becomes crucial - authentication requests must run on the server whenever possible. Application data should load on mobile or web clients only after successful authentication.

Exposed API Keys and Secrets in Frontend Code

API key exposure in frontend code creates severe security vulnerabilities. Attackers can steal data or rack up unauthorized charges. A detailed study by North Carolina State University showed that more than 100,000 repositories on GitHub faced unauthorized access due to exposed API keys. This security oversight damages both finances and reputation.

Common Patterns of API Key Exposure

Developers make critical security mistakes when handling API keys. To cite an instance, a fintech application hardcoded its Stripe key directly in JavaScript (const stripeKey = "sk_live_5f9...f2"). Attackers exploited this to issue unauthorized refunds by spoofing requests. Similar patterns emerge in different scenarios:

• Hardcoding in source code: JavaScript files with embedded API keys give attackers direct access to your backend
• Environment variables misconception: Developers often think .env files keep keys secure, unaware that bundlers convert these variables to string values during build
• Debug logs and error messages: Troubleshooting logs can permanently expose keys
• Public repositories: Attackers constantly scan GitHub, making even brief credential exposure dangerous

Client-side code runs in the user's browser, which makes it public by nature. OpenAI's security documentation emphasizes: "Never deploy your key in client-side environments like browsers or mobile apps".

Supabase Edge Functions as a Secure Proxy

Creating a secure proxy between frontend and third-party APIs stands as the industry standard solution. Supabase Edge Functions excel as a secure middleman that protects your credentials.

Edge Functions come with built-in access to environment variables like SUPABASE_URL, SUPABASE_ANON_KEY, and SUPABASE_SERVICE_ROLE_KEY. The proper configuration lets you:

// Access secure keys safely in Edge Functions
const secretKey = Deno.env.get('STRIPE_SECRET_KEY')

This solution addresses a crucial ground problem: secure integration of third-party APIs like Google Maps or OpenAI without credential exposure in client-side code. Edge Functions also let you implement strong security measures. These include CORS policies and request validation while caching responses improves performance.

Storing Secrets in Supabase Secrets

Supabase provides dedicated features to manage sensitive information through its Secrets system. Development environments can load environment variables through:

1. An .env file placed at supabase/functions/.env
2. The --env-file option for supabase functions serve

Production deployment allows secret setting through the Supabase Dashboard or CLI:

# .env
STRIPE_SECRET_KEY=sk_live_...

You can push all secrets from the .env file to your remote project using supabase secrets set.

Supabase Vault offers an encrypted database storage solution for API keys and sensitive data. The vault uses Transparent Column Encryption to store secrets in authenticated encrypted form. This ensures they stay tamper-proof. Attackers who capture the entire database only see encrypted data without the encryption key. Supabase manages these keys in secured backend systems.

One security principle remains unchanged: "Secret API keys belong on the server, never in the client".

Misconfigured Database Access and RLS Policies

Database security forms the foundations of application protection. Many vibe-coded applications fail at this basic level. RLS policies in database systems like Supabase add vital protection layers, but developers often misconfigure them in fast-paced development projects.

Anon Key Exposure in Supabase

Supabase's "anon" key (also called the publishable key) lets frontend applications access the database. Developers think this key is secure on its own, but it only works safely with proper RLS policies. This misunderstanding creates dangerous gaps in security. Marketing claims about security sound reassuring, but I've seen many projects where developers didn't grasp what exposing this key means.

The anon key can't tell users apart - it only identifies different applications. Without proper RLS setup, anyone who gets this key can access your database's data. The key shows up easily in browser DevTools. A developer proved this by retrieving 831 user profile records using just the exposed anon key from a live application.

Missing or Overly Permissive RLS Rules

RLS-enabled tables block all data access until you create specific policies. Developers often write overly permissive policies that make security protections useless. These critical mistakes happen often:

• Using USING (true) conditions without extra restrictions
• Forgetting policies for specific operations (UPDATE needs a matching SELECT policy)
• Wrong authenticated user checks in policy conditions
• No separate USING and WITH CHECK expressions for detailed control

A vulnerability in generated projects surfaced recently. It showed how weak RLS policies could expose sensitive data including personal information and API credentials to attackers without authentication, even with the supposedly limited anon key.

Deny-by-Default Policy for Data Access

Strong database security needs a "deny-by-default" approach. Postgres blocks all row visibility and modifications automatically when RLS is on but has no policies. This creates a secure starting point where you must grant access explicitly.

Public data needs policies that allow read access to safe columns only. Authenticated access requires policies that use auth.uid() or similar session variables to limit data to the logged-in user's view. Complex applications make RLS configuration tricky, sometimes needing subqueries or functions with SELECTs to make policy decisions.

Superusers and roles with BYPASSRLS can skip all RLS restrictions. Supabase's service_role key has this power, so it should stay private and never run in browsers.

Publicly Accessible Internal Applications

Vibe-coded applications built for internal use often end up on the public internet and create major security risks. Security researchers report that developers build internal tools, admin dashboards, and staging environments with vibe-coding platforms. These developers fail to add proper authentication before deployment. This oversight makes these applications easy targets for attackers who scan the web looking for vulnerable systems.

Fingerprinting Vibe-Coded Apps via Domain Patterns

Attackers use specialized fingerprinting techniques to find vulnerable vibe-coded applications. Security researchers found that many internal applications were exposed to the public internet by using simple search patterns that match strings like "lovable.app" along with other identifying markers. These fingerprinting methods help attackers locate applications built with specific vibe-coding platforms systematically, whatever their developers' original intentions.

Examples of Exposed Admin Dashboards

Fingerprinting has revealed several applications that pose serious data exposure risks:

• Mock websites with real production data but no authentication controls
• Internal knowledge bases that leak proprietary information
• Company chatbots trained on sensitive corporate data

This problem gets worse because internal applications usually contain much more valuable data than public-facing sites. While developers add security features to customer-facing applications, they often skip these safeguards for internal tools, thinking network security will protect them.

Authentication Enforcement for Internal Tools

Protection against unauthorized access starts by keeping AI-coded applications away from external users. But many vibe-coding tools add authentication directly into AI-generated code, which makes them vulnerable to hallucinations or coding errors. A security expert warns, "If AI hallucinates just one line of code and removes the requireAdmin keyword, you will expose all your customers to any crawler that's scanning the internet".

Security-minded organizations implement authentication at the infrastructure layer through reverse proxies like NGINX. These proxies check user credentials before API requests reach the application. This approach will give a security barrier that works no matter what code the AI creates.

Organizations need to track all their vibe-coded applications during development and must add authentication to any application that handles sensitive data or internal information.

Lack of Secure Coding Practices in AI-Generated Code

Stanford University's recent studies reveal a troubling pattern in AI-generated code: nearly half of all code from large language models contains security vulnerabilities. These numbers emphasize fundamental security gaps in today's AI coding practices.

No Input Validation or Sanitization

Security experts notice AI-generated code lacks proper input validation mechanisms. User inputs remain unchecked before processing, which creates serious security gaps and leads to injection attacks. The biggest problem comes from AI's limited grasp of security practices' contextual factors. A human developer knows which data types an application should accept based on business needs, but AI tools can't understand these contextual boundaries.

AI models can't determine which variables need sanitization without broader application context. AI-generated components pass static analysis but fail under ground conditions. Security gaps like SQL injection, cross-site scripting (XSS), and insecure deserialization slip through easily without full validation.

Missing Authentication Layers

AI tools create vulnerabilities through poorly implemented authentication. These weaknesses show up when AI applications skip authentication verification for critical functions. Unauthorized users could access sensitive data, system controls, or critical infrastructure components.

Stanford researchers discovered security issues in both newer and larger models. AI generates insecure code 86% of the time for certain authentication implementations. Improper error handling and insecure API key management surface as common authentication vulnerabilities in AI-generated code. These systemic problems led to security breaches in multiple industries. Healthcare facilities saw patient data become available due to weak authentication mechanisms.

No Use of Application Security Testing Tools

Developers spend more time fixing security vulnerabilities after adopting AI-generated code - 68% report this issue. Many developers integrate this code without proper testing, which creates a dangerous "comprehension gap".

A newer study shows developers using AI assistants wrote less secure code but believed their code was more secure than manual alternatives. Traditional security processes weren't built to handle AI-generated code's volume and speed. This creates friction between development speed and security oversight.

Experts suggest using detailed application security testing to reduce these risks, including SAST, SCA, and dynamic application security testing (DAST). Training developers to spot common AI-generated vulnerabilities creates another critical defense layer.

Conclusion

Security vulnerabilities haunt vibe-coded applications at an alarming rate. These issues create major risks for organizations that embrace AI-assisted development. This piece dives into several dangerous security pitfalls that undermine modern applications. The biggest problem lies in client-side authentication without server validation. This flaw lets attackers bypass security controls easily. API keys sitting exposed in frontend code also create immediate risks of unauthorized access and financial damage.

Database security takes a hit under fast development conditions. Many developers don't fully grasp how Row Level Security works with public keys. This gap leads them to expose sensitive data to anyone who finds these credentials. Internal applications often become available to the public without proper security barriers. Attackers who scan systematically for these exposed resources can easily find their targets.

The most worrying aspect shows how AI-generated code lacks secure coding practices. Statistics reveal that all but one of these codes from large language models have security flaws. This fact should make organizations think twice before deploying these solutions without proper testing.

Security needs to be at the forefront rather than an afterthought with AI-assisted development tools. Organizations need server-side authentication, secure API key handling, and proper database access controls. A full security testing program protects against these systemic problems.

AI tools offer undeniable speed benefits. Yet organizations must balance this speed with the right security measures. Without proper safeguards, they might join the unfortunate 20% whose vibe-coded applications fail simple security checks. Such failures can expose sensitive data, allow unauthorized access, or create compliance problems that dwarf any time saved in development.