Frontier AI Risk Management Framework in Practice: A Risk Analysis
  Technical Report
Authors: name: Shanghai AI Lab; name: Xiaoyang Chen; name: Yunhao Chen; name: Zeren Chen; name: Zhiyun Chen; name: Hanyun Cui; name: Yawen Duan; name: Jiaxuan Guo; name: Qi Guo; name: Xuhao Hu; name: Hong Huang; name: Lige Huang; name: Chunxiao Li; name: Juncheng Li; name: Qihao Lin; name: Dongrui Liu; name: Xinmin Liu; name: Zicheng Liu; name: Chaochao Lu; name: Xiaoya Lu; name: Jingjing Qu; name: Qibing Ren; name: Jing Shao; name: Jingwei Shi; name: Jingwei Sun; name: Peng Wang; name: Weibing Wang; name: Jia Xu; name: Lewen Yan; name: Xiao Yu; name: Yi Yu; name: Boxuan Zhang; name: Jie Zhang; name: Weichen Zhang; name: Zhijie Zheng; name: Tianyi Zhou; name: Bowen Zhou
Published: 2025-07-22 12:44:38

Abstract: To understand and identify the unprecedented risks posed by rapidly advancing
artificial intelligence (AI) models, this report presents a comprehensive
assessment of their frontier risks. Drawing on the E-T-C analysis (deployment
environment, threat source, enabling capability) from the Frontier AI Risk
Management Framework (v1.0) (SafeWork-F1-Framework), we identify critical risks
in seven areas: cyber offense, biological and chemical risks, persuasion and
manipulation, uncontrolled autonomous AI R\&D, strategic deception and
scheming, self-replication, and collusion. Guided by the "AI-45^circ Law,"
we evaluate these risks using "red lines" (intolerable thresholds) and "yellow
lines" (early warning indicators) to define risk zones: green (manageable risk
for routine deployment and continuous monitoring), yellow (requiring
strengthened mitigations and controlled deployment), and red (necessitating
suspension of development and/or deployment). Experimental results show that
all recent frontier AI models reside in green and yellow zones, without
crossing red lines. Specifically, no evaluated models cross the yellow line for
cyber offense or uncontrolled AI R\&D risks. For self-replication, and
strategic deception and scheming, most models remain in the green zone, except
for certain reasoning models in the yellow zone. In persuasion and
manipulation, most models are in the yellow zone due to their effective
influence on humans. For biological and chemical risks, we are unable to rule
out the possibility of most models residing in the yellow zone, although
detailed threat modeling and in-depth assessment are required to make further
claims. This work reflects our current understanding of AI frontier risks and
urges collective action to mitigate these challenges.