国内首个大模型“体检”结果发布，这样问AI很危险

Core Insights - The recent security assessment of AI large models revealed 281 vulnerabilities, with 177 being specific to large models, indicating new threats beyond traditional security concerns [1] - Users often treat AI as an all-knowing advisor, which increases the risk of privacy breaches due to the sensitive nature of inquiries made to AI [1][2] Vulnerability Findings - Five major types of vulnerabilities were identified: improper output vulnerabilities, information leakage, prompt injection vulnerabilities, inadequate defenses against unlimited consumption attacks, and persistent traditional security vulnerabilities [2] - The impact of large model vulnerabilities is less direct than traditional system vulnerabilities, often involving circumvention of prompts to access illegal or unethical information [2][3] Security Levels of Domestic Models - Major domestic models such as Tencent's Hunyuan, Baidu's Wenxin Yiyan, Alibaba's Tongyi App, and Zhiyun Qingyan exhibited fewer vulnerabilities, indicating a higher level of security [2] - Despite the lower number of vulnerabilities, the overall security of domestic foundational models still requires significant improvement, as indicated by a maximum score of only 77 out of 100 in security assessments [8] Emerging Risks with AI Agents - The transition from large models to AI agents introduces more complex risks, as AI agents inherit common security vulnerabilities while also presenting unique systemic risks due to their multi-modal capabilities [9][10] - Specific risks associated with AI agents include perception errors, decision-making mistakes, memory contamination, and potential misuse of tools and interfaces [10][11] Regulatory Developments - The National Market Supervision Administration has released 10 national standards and initiated 48 technical documents in areas such as multi-modal large models and AI agents, highlighting the need for standardized measures to mitigate risks associated with rapid technological advancements [11]