SECURITY TESTING FOR AI WRAPPER APPS

AI wrapper apps are the hottest category for indie hackers – ChatGPT clones, AI writing tools, image generators, and LLM-powered utilities. Built fast with Cursor and Bolt, these apps often ship with exposed API keys, no rate limiting on expensive inference endpoints, and user inputs passed directly to LLM APIs without sanitization.

Why Security Matters for AI Wrapper Apps

AI wrapper apps handle sensitive data and business-critical operations. A single vulnerability can lead to data breaches, financial loss, and damaged reputation. Unlike most credential leaks, an exposed LLM key converts directly into money: whoever finds it runs inference on your account until the key is rotated or the card declines.

Top Vulnerabilities in AI Wrapper Apps

LLM API Key Exposure

OpenAI, Anthropic, or Replicate API keys hardcoded in frontend JavaScript or committed to public repos, letting anyone drain your credits. The Token Leak Checker finds keys that already shipped in your bundle.

SSRF via Model Endpoints

User-supplied URLs passed to AI model endpoints without validation, allowing attackers to access internal services or cloud metadata endpoints.

Prompt Injection

User input concatenated directly into system prompts, allowing attackers to override instructions, extract system prompts, or access sensitive data. See indirect prompt injection for the variant that arrives through retrieved content instead of the input box.

Missing Usage Limits

AI inference endpoints without per-user rate limiting or spending caps, letting a single user rack up thousands in API costs. The fix patterns – token budgets, sliding-window limits, hard provider caps – are covered in API abuse and bot protection.

Insecure Output Rendering

AI model outputs rendered as HTML without sanitization, allowing indirect prompt injection to produce XSS payloads that execute in the browser. See LLM-rendered HTML/Markdown for the recurring shapes.

User Data in Request Logs

Sensitive user inputs logged in plain text through LLM API request logging, creating a searchable database of private conversations.

How VibeEval Secures AI Wrapper Apps

Three steps to find and fix security issues in your AI wrapper app:

1. VibeEval scans for exposed LLM API keys in frontend code, API responses, and configuration files that could drain your credits.
2. The scanner tests AI inference endpoints for missing rate limiting and usage caps that let users abuse expensive API calls.
3. You get AI-specific findings covering prompt injection, SSRF, output sanitization, and API key management.

Related Resources

API Abuse & Bot Protection

Rate limiting, token budgets, and bot detection for the endpoints that cost you money

Token Leak Checker

Free check for LLM API keys exposed in your frontend bundle

Indirect Prompt Injection

How injection arrives through retrieved content, and what actually mitigates it

Vibe Code Scanner

Multi-platform scanner for AI-generated apps – whatever tool you built with

Test Your AI Wrapper App Before Launch

Exposed keys and open inference endpoints get found fast – scan with the vibe code scanner before your first user signs up.