TL;DR
Lovable (formerly GPT Engineer) creates impressive apps quickly, but ships them without essential security measures. The biggest risks are missing Supabase Row Level Security, exposed environment variables, and incomplete authentication flows. The platform itself is secure, but you need to add security before deploying to production. Great for prototypes, needs work for real user data.
What is Lovable?
Lovable (formerly known as GPT Engineer) is an AI-powered app builder that creates full-stack web applications from natural language descriptions. It generates React frontends with Supabase backends and can deploy directly to their hosting or be exported for self-hosting.
Like other AI app builders, Lovable prioritizes speed and functionality over security, which means generated apps need security hardening before production use.
Our Verdict
What's Good
- Clean, modern React code
- Supabase integration built-in
- GitHub sync available
- One-click deployment
- Good for complex UIs
What to Watch
- RLS not configured by default
- Auth flows often incomplete
- API keys may be exposed
- No server-side validation
- Missing rate limiting
The Supabase Security Problem
Lovable heavily integrates with Supabase for backend functionality. While this is powerful, it creates a significant security concern: Lovable often doesn't configure Row Level Security (RLS) properly.
Why This Matters
Without RLS, anyone who knows your Supabase URL and anon key (which are public in your frontend code) can:
- Read all data from your tables
- Modify any user's data
- Delete records from your database
- Access sensitive information
Critical: We've seen Lovable apps where user emails, passwords (hashed), and private data were accessible to anyone who inspected the network requests. Always verify RLS is enabled and configured.
How to Check
After generating an app, check your Supabase dashboard:
- Go to Table Editor and select each table
- Click the shield icon to view RLS status
- If RLS is disabled, your data is exposed
- Enable RLS and create appropriate policies
Common Security Issues
| Issue | Risk Level | How to Fix |
|---|---|---|
| Missing RLS policies | Critical | Enable RLS, write policies |
| Auth bypass possible | High | Add server-side auth checks |
| Exposed API keys | High | Move to environment variables |
| No input validation | Medium | Add Zod schemas |
| CORS too permissive | Medium | Restrict to your domains |
Lovable vs Other AI Builders
| Feature | Lovable | Bolt.new | v0 |
|---|---|---|---|
| Backend included | Yes (Supabase) | Yes | No |
| Database security | RLS often missing | RLS often missing | N/A |
| Auth quality | Partial | Partial | None |
| Code export | Yes | Yes | Yes |
| GitHub sync | Yes | Limited | No |
Security Checklist for Lovable Apps
Before Going Live
- Enable RLS: Every table with user data needs Row Level Security
- Write RLS policies: Users should only access their own data
- Check auth flows: Verify protected pages require login
- Review API calls: Ensure sensitive operations check authentication
- Move secrets: API keys should be in environment variables
- Add validation: Implement server-side input validation
- Test as attacker: Try accessing other users' data
When to Use Lovable
Good for: Prototypes, internal tools, landing pages, MVPs with non-sensitive data, and projects where you'll add security before handling real users.
Be careful with: Apps handling payment data, health information, or any sensitive user data. These need thorough security review and hardening before launch.
Is Lovable safe for production?
Not out of the box. Lovable-generated apps need security hardening before production use. The platform itself is secure, but the generated code lacks essential security measures like proper RLS configuration and complete authentication flows. Export the code, fix security issues, then deploy.
How does Lovable compare to coding it myself?
Lovable generates functional code much faster than writing from scratch, but you still need to understand security to deploy safely. Think of it as getting 80% of the way there quickly, then spending time on the critical 20% (security, edge cases, error handling).
What happened to GPT Engineer?
GPT Engineer rebranded to Lovable in 2024. The product is essentially the same, with ongoing improvements. Any security considerations that applied to GPT Engineer apply to Lovable as well.
Can I fix security issues without coding knowledge?
Basic Supabase RLS can be configured through the dashboard UI, but understanding what policies to create requires some knowledge. For anything beyond simple user-owns-data patterns, you'll likely need developer help or to learn the basics of database security.
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