Exploring the Secondary Risks of Large Language Models

Understand

Ensuring the safety and alignment of Large Language Models is a significant challenge with their growing integration into critical applications and societal functions.

• While prior research has primarily focused on jailbreak attacks, less attention has been given to non-adversarial failures that subtly emerge during benign interactions.
• We introduce secondary risks a novel class of failure modes marked by harmful or misleading behaviors during benign prompts.
• Unlike adversarial attacks, these risks stem from imperfect generalization and often evade standard safety mechanisms.