This research reveals how removing superfluous constraints in jailbreaking attacks significantly improves their transferability across different LLMs.

• Key Finding: Excessive restrictions in attack prompts can limit transferability between models
• Novel Approach: The authors develop a framework that identifies and removes unnecessary constraints during attack optimization
• Improved Effectiveness: Their method achieves up to 30% better transferability than existing techniques
• Security Implications: This work highlights critical vulnerabilities in the cross-model security landscape of LLMs

For security professionals, this research underscores the urgent need for robust, cross-model defense mechanisms against increasingly transferable jailbreak attacks.

Guiding not Forcing: Enhancing the Transferability of Jailbreaking Attacks on LLMs via Removing Superfluous Constraints