How to secure apps in ai & ml apps
Indie hackers build AI wrappers, GPT-powered tools, and ML dashboards faster than ever using Cursor and Bolt. These apps often pass user input directly to LLM APIs, store API keys insecurely, and lack proper rate limiting on expensive AI inference endpoints. A single SSRF or prompt injection can drain your OpenAI credits overnight.
Scan your ai & ml apps application
Relevant regulatory frameworks
AI & ML Apps applications operate under these regulatory frameworks. VibeEval tests for vulnerabilities that could be relevant to these standards.
Common app types in ai & ml apps
Industry-specific vulnerabilities
API Key Exposure
OpenAI, Anthropic, or other LLM API keys hardcoded in frontend code or committed to public repos, letting anyone drain your credits.
SSRF via Model Endpoints
User-supplied URLs passed to model inference endpoints without validation, allowing attackers to access internal services or cloud metadata.
Prompt Injection
User input concatenated directly into system prompts without sanitization, allowing attackers to override instructions and extract sensitive data.
Missing Rate Limiting on Inference
AI inference endpoints without usage limits that let a single user rack up thousands in API costs through automated requests.
User Data in AI Logs
Sensitive user inputs logged in plain text through LLM API request logging, creating a searchable database of private conversations.
Insecure Output Rendering
AI model outputs rendered as HTML without sanitization, allowing indirect prompt injection to produce XSS payloads.
How VibeEval helps ai & ml apps teams
Automated security testing designed for ai & ml apps applications.
Never expose LLM API keys in client-side code. Use a server-side proxy with per-user rate limiting and usage caps.
Validate and sanitize all user inputs before including them in prompts. Never concatenate raw user input into system prompts.
Implement per-user spending limits and rate limiting on inference endpoints to prevent credit drain attacks.
Frequently asked questions
How does VibeEval test AI wrapper apps?
VibeEval checks for exposed API keys, SSRF in model endpoints, missing rate limiting on inference, prompt injection vectors, and insecure output rendering.
Can VibeEval detect exposed OpenAI keys?
Yes. VibeEval scans for API keys from OpenAI, Anthropic, and other AI providers in frontend code, API responses, and exposed configuration files.
Does VibeEval test for prompt injection?
VibeEval tests input handling patterns that are vulnerable to prompt injection, including direct concatenation and missing input sanitization.
What are the biggest risks for AI wrapper apps?
Exposed API keys that drain your credits, SSRF that accesses internal infrastructure, and missing rate limits that let users abuse expensive inference endpoints.
Should I scan my AI app before launch?
Yes. AI apps are high-value targets because exposed API keys provide direct financial value to attackers. Scan before your first user signs up.
Related resources
Test your ai & ml apps application today
Test your ai & ml apps application for security vulnerabilities with VibeEval.