Vibe Coding Risks: Security and Production Concerns
I tested this.
What are the biggest risks?
Biggest risk: hardcoded secrets. Found in 53% of AI-generated projects. Second: SQL injection through raw query interpolation. Third: insecure session management (tokens in localStorage). Fourth: missing input validation on all endpoints. These are not edge cases. They are the default.
How do you mitigate them?
Mitigate with: .cursorrules with security constraints, ESLint security plugin on every PR, mandatory manual review of auth/payments/data code, and automated security scanning before production deploy. This multi-layer approach catches about 95% of issues.
What should you never use AI for?
Never use AI for: auth middleware, payment processing, encryption logic, database migration files, or deployment configuration. Hand-write these. The security and correctness requirements are too high for AI-generated code. I learned this after a Stripe webhook incident.
Risks: hardcoded secrets (53%), SQL injection, insecure sessions, missing validation. Mitigate: .cursorrules, ESLint, manual review, automated scanning. Never AI: auth, payments, encryption, migrations, deploy config.
The biggest risk is not the AI-generated vulnerabilities. It is the false sense of security. AI code compiles and runs, so developers assume it is safe. It is not. Every AI-generated feature needs security review. Treat AI code like code from an unknown contributor.
Steps.
AI tools are powerful but require human judgment and careful oversight at every step of the development process. I learned this lesson the hard way after several production incidents caused by trusting AI output without verification. Review every change before merging to main. Test every feature with real edge cases, not just the happy path that the AI assumes. Never trust AI-generated code in production without thorough verification. These habits will prevent the production incidents that I experienced in my early days of vibe coding. The extra few minutes spent on review and testing pay for themselves many times over in prevented issues and cleaner codebases that are easier to maintain and debug over the long term.
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