This research introduces a novel approach to LLM safety by adding special red flag tokens to detect harmful content without degrading performance.

• Creates a vocabulary extension with tokens that identify harmful requests
• Prevents vulnerability to jailbreaking attacks that exploit initial affirmative responses
• Maintains model capabilities while improving safety mechanisms
• Offers a more robust alternative to traditional refusal-based safety training

This approach matters for security teams because it addresses fundamental vulnerabilities in current LLM safety mechanisms while preserving the functionality that users expect.

A generative approach to LLM harmfulness detection with special red flag tokens