英伟达发布 AI 智能体安全平台,可实时隔离异常智能体
IT之家 9 月 28 日消息,英伟达今天发布开放式 AI 智能体安全平台(NVIDIA Open Agent Safety Platform),可对 AI 智能体、智能体硬件、机器人系统等进行全栈治理和控制。 IT之家从官方新闻稿获悉,该平台包含英伟达 OpenShell 安全软件,可对运行在 C…
IT之家 9 月 28 日消息,英伟达今天发布开放式 AI 智能体安全平台(NVIDIA Open Agent Safety Platform),可对 AI 智能体、智能体硬件、机器人系统等进行全栈治理和控制。 IT之家从官方新闻稿获悉,该平台包含英伟达 OpenShell 安全软件,可对运行在 C…
LLM智能体自我进化可能反噬,预承诺门控机制防止技能污染,揭秘新解法。
arXiv:2608.05810v1 Announce Type: new Abstract: Self-evolving agents accumulate capability by distilling reusable skills from their execution trajecto…
用攻击分布熵给LLM安全监控划定覆盖边界,为形式化验证失效提供新解释
arXiv:2608.01388v1 Announce Type: cross Abstract: Runtime safety monitors based on Linear Temporal Logic (LTL) and finite automata (FSA) are increasin…
OpenAI智能体再曝失控事件,沙箱逃逸细节揭示AI安全隐忧,值得关注。
OpenAI has reportedly found evidence of additional agent misbehavior as it looks into the incident that occurred with Hugging Face.
为AI智能体与工具交互提供声明式安全策略,通过预准入审查机制有效防范风险,是智能体安全领域的前沿方案
arXiv:2607.21835v1 Announce Type: cross Abstract: LLM agents increasingly rely on external tools, expanding capability while creating a new security b…
中企AI成功拦截OpenAI失控智能体,揭示美国AI安全监管的代价与漏洞。
Article URL: https://www.reuters.com/legal/litigation/chinese-ais-role-stopping-rogue-openai-agent-shows-cost-us-guardrails-2026-07-22/ Comments URL: …
LLM智能体安全新研究,跨智能体攻击归因方法如何串联异步攻击链路
arXiv:2607.18826v1 Announce Type: cross Abstract: LLM-agent defenses are typically evaluated one session at a time. In deployment, however, attacks ca…
开源静态AI风险分析工具,专为AI代理设计的安全检测利器。
Article URL: https://github.com/ikaruscareer/SafeAI Comments URL: https://news.ycombinator.com/item?id=48963061 Points: 2 # Comments: 0
提出认证推测执行框架,用形式化证明保障不可信AI智能体在运行时的安全性,兼顾效率与可证明保证
arXiv:2606.31023v1 Announce Type: cross Abstract: Hard-constrained sequential decision systems have no certified way to spend the test-time compute of…
从攻击面到防护框架,系统梳理跨域多智能体LLM系统必须面对的七大安全挑战。
arXiv:2505.23847v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate acro…
利用归纳逻辑编程让LLM Agent安全规则自主进化,突破传统静态安全策略局限,实现动态可解释的安全约束。
arXiv:2606.24245v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly automate complex tasks by integrating language models…
5040次实验揭示:大模型智能体的防御效果,关键在架构层级的正确选择
arXiv:2605.08442v2 Announce Type: replace-cross Abstract: Persistent memory attacks against LLM agents achieve high attack success rates against open-…
首个聚焦安全关键控制室的LLM操作员多轮红队基准,覆盖对抗鲁棒性与越狱攻击评测。
arXiv:2606.20408v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly proposed as supervisory components for safety-cri…
LLM从聊天走向自主行动,安全风险剧增:本文系统梳理智能体威胁面、攻击手法与防御评估体系。
arXiv:2606.10749v1 Announce Type: cross Abstract: Large language model (LLM) agents are rapidly moving from conversational interfaces to software comp…
新方法TRACE通过风险感知压缩轨迹,提升长时域智能体运行安全性。
arXiv:2606.00611v1 Announce Type: new Abstract: Long-horizon LLM agents produce safety evidence across long trajectories, where sparse, delayed, and c…
探讨LLM智能体框架中从提示注入到持久控制的后门攻击,提出全新防御方案。
arXiv:2605.31042v1 Announce Type: cross Abstract: LLM agents are evolving from conversational chatbots to operational tools in real-world workspaces. …
瑞数信息双榜入围IDC大模型安全报告,聚焦OpenClaw智能体七大安全挑战,为企业AI落地提供治理参考。