LiveSecBench: A Dynamic and Culturally-Relevant AI Safety Benchmark for
  LLMs in Chinese Context
Authors: name: Yudong Li; name: Zhongliang Yang; name: Kejiang Chen; name: Wenxuan Wang; name: Tianxin Zhang; name: Sifang Wan; name: Kecheng Wang; name: Haitian Li; name: Xu Wang; name: Lefan Cheng; name: Youdan Yang; name: Baocheng Chen; name: Ziyu Liu; name: Yufei Sun; name: Liyan Wu; name: Wenya Wen; name: Xingchi Gu; name: Peiru Yang
Published: 2025-11-04 08:44:09

Abstract: In this work, we propose LiveSecBench, a dynamic and continuously updated
safety benchmark specifically for Chinese-language LLM application scenarios.
LiveSecBench evaluates models across six critical dimensions (Legality, Ethics,
Factuality, Privacy, Adversarial Robustness, and Reasoning Safety) rooted in
the Chinese legal and social frameworks. This benchmark maintains relevance
through a dynamic update schedule that incorporates new threat vectors, such as
the planned inclusion of Text-to-Image Generation Safety and Agentic Safety in
the next update. For now, LiveSecBench (v251030) has evaluated 18 LLMs,
providing a landscape of AI safety in the context of Chinese language. The
leaderboard is publicly accessible at https://livesecbench.intokentech.cn/.