Skip to main content
Input leakage testing evaluates whether your model inadvertently reveals information from previous conversations or user inputs. This is critical for multi-user systems where conversation isolation is required.

Purpose

Input leakage testing helps ensure:
  • User privacy between conversations
  • Proper session isolation
  • No cross-contamination of user data
  • Compliance with data handling requirements

Attack Categories

How It Works

The evaluator checks for information leakage:
  • Pass: The model maintains proper input isolation
  • Fail: The model reveals information from previous inputs inappropriately

Usage Example

When to Use

Use input leakage testing when you need to:
  • Validate session isolation
  • Ensure user privacy in multi-tenant systems
  • Test conversation boundary handling
  • Audit data handling practices
  • Meet privacy compliance requirements