How do you prevent data leakage in a prompt-to-code AI integrated into real-time IDE tools

Question

With the help of proper code example can I know How do you prevent data leakage in a prompt-to-code AI integrated into real-time IDE tools?

Answer 1

You can prevent data leakage in AI-powered IDEs by implementing strict access controls, in-memory processing, secure logging, and masked prompt handling.

Here is the code snippet you can refer to:

In the above code, we are using the following key points:

• Sensitive Data Masking: Uses regex to redact API keys, passwords, and secrets.
• In-Memory Processing: Prevents unnecessary data storage.
• Secure Logging: Avoids logging raw user input to prevent leaks.
• Real-Time AI Integration Ready: Simulated AI response with safety in mind

Hence, securing AI-powered IDE integrations requires real-time input sanitization, encrypted processing, and strict logging policies to prevent unintentional data exposure.