Quoting Matthew Green
[...] 将这些部分组合在一起，你就得到了一个蠕虫的两个部分：一个劫持代理程序的负载，以及一个能够将负载传递给下一个代理程序的代理程序。在各自隔离沙盒中的代理程序发现，它们可以在一个共享的包缓存中互相留下指令，而这些指令改变了接收者的行为。将包缓存替换为电子邮件、Slack、共享文档或WhatsApp，并将独立的沙盒训练运行替换为独立部署的个人代理程序，如Muse，那么你就正好具备了蠕虫所需的所有要素。—— Matthew Green，《沙盒是否足以遏制恶意代理？》 标签：意外网络攻击、人工智能滥用、生成式人工智能、人工智能安全研究、沙盒、人工智能、大型语言模型
[...] Put these pieces together and you have the two halves of a worm: a payload that hijacks the agent, and an agent that will carry the payload to the next agent. Agents in separately-isolated sandboxes discovered that they could leave instructions for each other in a shared package cache, and those instructions changed what the recipients did. Replace the package cache with email, Slack and shared documents or WhatsApp, and replace independently-sandboxed training runs with independently-deployed personal agents like Muse, and you have exactly the ingredients that a worm needs. — Matthew Green , Is sandboxing sufficient to contain rogue agents? Tags: accidental-cyberattacks , ai-misuse , generative-ai , ai-security-research , sandboxing , ai , llms