JailbreakEval introduces a comprehensive toolkit for researchers to systematically evaluate jailbreak attempts against Large Language Models, addressing inconsistencies in current assessment approaches.

• Standardizes evaluation methods for harmful LLM responses
• Balances assessment trade-offs between human values alignment, time efficiency, and cost
• Provides security researchers with reliable tools to benchmark jailbreak defenses
• Contributes to safer AI development by enabling consistent security evaluations

This research is crucial for the security community as it establishes a unified framework to assess LLM vulnerabilities, helping organizations better protect against manipulative prompts that could bypass safety guardrails.

JailbreakEval: An Integrated Toolkit for Evaluating Jailbreak Attempts Against Large Language Models