SafeDialBench introduces a comprehensive framework for evaluating LLM safety during complex multi-turn dialogues with various jailbreak attacks.

• Addresses limitations in current safety benchmarks that focus only on single-turn interactions
• Implements diverse jailbreak attack methods to thoroughly test LLM defenses
• Provides detailed assessment of how LLMs identify and handle unsafe information
• Enables fine-grained safety evaluation beyond simple pass/fail metrics

This research is critical for security professionals as it offers a more realistic evaluation of LLM vulnerabilities in conversational contexts, where safety risks are often highest. The benchmark helps identify specific weaknesses in safety mechanisms that could be exploited in real-world applications.

SafeDialBench: A Fine-Grained Safety Benchmark for Large Language Models in Multi-Turn Dialogues with Diverse Jailbreak Attacks