Raydian Security Guide: AI-Generated App Risks and Best Practices
Raydian uses AI to generate full applications, but AI-generated code carries inherent security risks. Learn how to identify and fix vulnerabilities in your Raydian app.
By Paula C · Kraftwire Software
· 8 min readRaydian is an AI-powered platform for generating complete applications from natural language descriptions. Like other vibe coding platforms, it trades development speed for potential security risks that every builder should understand.
If you have used Raydian to build a web app, there is a good chance your code contains vulnerabilities that need attention. This guide walks through the most common risks, explains why they happen, and shows you how to fix each one.
The AI-Generated Code Problem
Research consistently shows that AI-generated code carries more vulnerabilities than human-written code:
**Veracode**: 45% of AI-assisted development introduces critical security vulnerabilities
**Snyk**: AI-generated code is 30-40% more vulnerable than human-written code
**Stanford**: Developers using AI assistants write significantly less secure code
**Cloud Security Alliance**: 62% of AI-generated code contains security flaws
These statistics apply to all AI code generators, and Raydian is no exception. The AI models that power these tools were trained on public code repositories, Stack Overflow answers, and tutorial code. A lot of that source material contains insecure patterns, outdated libraries, and shortcuts that made sense in a tutorial but have no place in production.
Top Raydian Security Risks
1. Inherited Anti-Patterns from Training Data
AI models learn from publicly available code, and not all of that code is good. The training data includes:
Outdated authentication patterns that were acceptable five years ago but are now considered insecure
Insecure default configurations copied from quick-start guides
Hard-coded credentials from example code and tutorials that were never meant for production use
References to deprecated libraries with known vulnerabilities that have already been patched
When Raydian generates code, it pulls from these patterns without understanding the security implications. The resulting code works, but it may rely on approaches that security researchers have already flagged as dangerous.
**What this looks like in practice:** Your generated app might use MD5 for password hashing instead of bcrypt or argon2. It might store session data in a way that is vulnerable to session fixation attacks. It might use an older version of a library that has a known remote code execution vulnerability.
2. Missing Server-Side Validation
AI-generated apps almost always implement validation on the client side. They add nice form validation with error messages, character limits, and format checks. But they frequently skip the same validation on the server side.
This is a critical gap. Client-side validation is a user experience feature, not a security feature. Any user with basic technical knowledge can bypass client-side validation by sending requests directly to your API.
**What attackers can do without server-side validation:**
Submit forms with malicious content that bypasses your frontend checks
Send oversized payloads that crash your server or consume excessive resources
Inject SQL commands through fields that your frontend properly validates but your backend accepts without question
Upload file types that your UI restricts but your server happily processes
**How to fix it:** Mirror every client-side validation rule on the server. Use a validation library like Zod or Joi on your API endpoints. Never trust data that comes from the browser, even if your frontend code appears to validate it properly.
3. Insecure Default Configurations
Generated apps often ship with configurations that prioritize developer convenience over security:
**Debug mode enabled**: Error messages include full stack traces, database query details, and file paths that tell attackers exactly how your app is structured
**Verbose error messages**: Instead of generic "Something went wrong" responses, your API returns implementation details like table names, column names, and query structures
**Wide-open CORS settings**: Allowing all origins means any website can make authenticated requests to your API on behalf of your users
**No rate limiting**: Without rate limiting, attackers can brute-force login pages, scrape your data, or overwhelm your server with requests
**How to fix it:** Before deploying, go through every configuration file in your project. Switch debug mode off. Replace detailed error messages with generic ones and log the details server-side only. Restrict CORS to your specific frontend domain. Add rate limiting on login endpoints, API routes, and any resource-intensive operations.
4. Exposed Secrets and API Keys
AI code generators frequently embed API keys directly in source code rather than using environment variables. When the app gets deployed, these keys become publicly accessible through the browser or the code repository.
This happens because the AI generates the simplest working solution. When you ask it to connect to a third-party service, it puts the key right where it needs to be used. The code works immediately, and most developers move on to the next feature without realizing the key is now visible.
**Keys we commonly find exposed in Raydian apps:**
Payment processor keys (Stripe, PayPal) that allow attackers to issue refunds or view customer data
AI service keys (OpenAI, Anthropic) that can generate hundreds of dollars in charges per hour
Email service keys (SendGrid, Mailgun) that enable phishing attacks from your domain
Database connection strings that give direct access to your entire data store
**How to fix it:**
Search your entire codebase for strings that look like API keys, passwords, or tokens
Move every secret to environment variables
Make sure .env files are listed in your .gitignore
Rotate any keys that were previously committed to version control or deployed in client-side code
5. No Access Control Beyond Authentication
Generated CRUD applications often implement authentication (login/signup) but stop there. They skip authorization, which means an authenticated user can access or modify any record in the system, not just their own.
**The difference between authentication and authorization:**
Authentication verifies who you are (login)
Authorization verifies what you are allowed to do (access control)
A common pattern in Raydian apps: the app checks that a user is logged in before showing the dashboard, but the API endpoints that power the dashboard return data for all users, not just the currently authenticated one.
**How to fix it:** For every API endpoint, verify that the authenticated user has permission to access the requested resource. Check that data queries are scoped to the current user. Add role-based access control for admin functionality. Never rely on hiding UI elements as a form of security.
How to Secure Your Raydian App
Step 1: Review Authentication
Check that your app implements:
Secure password hashing (bcrypt or argon2, never MD5 or plain SHA-256)
Session token expiry and refresh logic
CSRF protection on state-changing endpoints
Rate limiting on login, registration, and password reset flows
Email verification before granting account access
Test your auth flow by trying common bypass techniques: submitting the login form with SQL injection payloads, trying to reuse expired tokens, and checking whether password reset links expire after use.
Step 2: Add Server-Side Authorization
For every API endpoint in your application, verify:
Users can only access their own data
Admin endpoints require admin role verification through a secure, server-side check
Resource ownership is validated on every request, not just the initial page load
ID parameters cannot be manipulated to access other users records
Bulk operations (list, export) are scoped to the current user or role
Step 3: Move Secrets to Environment Variables
Search your entire codebase for API keys, tokens, passwords, and connection strings
Move every secret to environment variables
Never commit .env files to version control
Rotate any keys that were previously exposed in code or repositories
Set up billing alerts on all third-party services so you are notified if a key is being abused
Step 4: Enable Security Headers
Ensure your deployed app sends these headers on every response:
`Content-Security-Policy` to prevent XSS attacks
`X-Frame-Options: DENY` to prevent clickjacking
`X-Content-Type-Options: nosniff` to prevent MIME sniffing
`Strict-Transport-Security` to enforce HTTPS connections
`Referrer-Policy` to control information leakage through referrer headers
Step 5: Add Input Validation Everywhere
Define validation schemas for every form and API endpoint
Validate data types, lengths, formats, and allowed values
Sanitize HTML content before storing or rendering it
Restrict file uploads by type, size, and content
Use parameterized queries for all database operations
Step 6: Scan with SimplyScan
Use [SimplyScan](https://simplyscan.io) to automatically check your deployed application for:
Exposed API keys and secrets in your client-side code
Missing security headers
Unprotected API endpoints
Known vulnerability patterns common in AI-generated code
Performance issues that can create security risks
The Vibe Coding Security Checklist
Before launching any Raydian app, verify every item on this list:
Authentication is implemented with secure password hashing
Authorization checks exist on every endpoint, scoped to the current user
No secrets are hard-coded in source code
Server-side validation matches or exceeds client-side validation
Security headers are configured on all responses
CORS is restricted to your specific frontend domain
Rate limiting is enabled on login, registration, and sensitive endpoints
Error messages in production do not leak implementation details
All dependencies are up to date with zero high or critical vulnerabilities
SimplyScan shows no critical findings on your deployed application
Key Takeaways
AI-generated code is statistically more vulnerable than human-written code, and Raydian apps are no exception. The good news is that most of these vulnerabilities follow predictable patterns and have straightforward fixes.
Focus on three areas first: authentication and authorization, secret management, and input validation. These cover the majority of critical vulnerabilities we find in vibe-coded applications.
Then scan every deployment with [SimplyScan](https://simplyscan.io). It was built specifically for AI-generated and vibe-coded apps, and it checks for the vulnerabilities that matter most.
Related Guides
[Base44 Security Guide](/blog/base44-security-guide)
[v0 Security Guide](/blog/v0-security-guide)
[Is Vibe Coding Safe?](/blog/is-vibe-coding-safe)
[Is Lovable Safe?](/blog/is-lovable-safe)
[Is Cursor Safe?](/blog/is-cursor-safe)