This research introduces SeqAR, a novel framework for automatically generating jailbreak prompts that bypass LLM safety mechanisms by employing multiple malicious characters in sequence.

Key Findings:

• SeqAR successfully evades safety guardrails in state-of-the-art LLMs through sequential character deployment
• The approach reveals critical vulnerabilities in current safety alignment techniques
• Researchers adopt a red-teaming strategy to identify and help address these security weaknesses
• Findings demonstrate the need for more robust safety measures in LLM development

Security Implications: This work provides valuable insights for security teams to strengthen LLM defenses against sophisticated attacks, highlighting how sequential prompts can circumvent existing protections and where additional safeguards are needed.

SeqAR: Jailbreak LLMs with Sequential Auto-Generated Characters