AI & LLM Security

User input is concatenated directly into an LLM prompt, letting attackers override your instructions and make the AI do things you never intended.

Your app sends personally identifiable information — emails, names, passwords, phone numbers — to external AI APIs, exposing user data to third-party model providers.

LLM output is rendered or executed directly without checking whether it matches the expected format or contains harmful content.

Your OpenAI, Anthropic, or other AI API key is exposed in client-side code, where anyone can steal it and rack up charges on your account.

LLM-generated HTML or code is rendered directly in the UI without sanitization, opening the door to stored XSS attacks.

Your app sends entire database records, config files, or secrets as context to an AI model, exposing far more data than the task requires.

When the primary AI model fails, your app silently falls back to a weaker or unvalidated model that bypasses your safety configurations.

Your app makes AI API calls with no per-user limits, letting a single user (or bot) trigger thousands of requests and drain your API budget in minutes.

Your app uses eval() or Function() to execute code that was generated by an LLM, giving attackers a path to arbitrary code execution via prompt injection.