The BEST way to prevent sensitive information disclosure by large language model (LLM) chatbots is...

Large Language Models (LLMs) have the capacity to memorize and unintentionally reveal sensitive information if not properly managed. As per the AAIA™ Study Guide, data masking is a critical technique that prevents the exposure of personally identifiable information (PII) or confidential content by obscuring or replacing sensitive parts of the data during training or interaction.

“Data masking ensures that training data used for LLMs does not contain real sensitive identifiers. Unlike sanitization, masking modifies data to maintain utility while eliminating exposure risk.”

Manual monitoring and access controls are supportive security measures, and data sanitization helps remove content but may not preserve the data’s structure. Data masking offers the most proactive and technically robust solution.