创建

登录 ReadmeX

或

了解我们如何处理你的信息: 隐私政策

ReadmeX

陪你读懂 AI 动态

今天,想先了解什么?

选一份动态总结,或直接聊聊你的问题。

社区和关注动态总结只属于你自己。

资讯

Google 报告攻击者利用被盗凭证实施 LLMjacking

AI 总结

TechRadar 援引 Google Threat Intelligence Group 的报告称,攻击者正窃取 AI API 密钥和云凭证,用于运行未经授权的 AI 工作负载、搭建代理服务并给受害者造成高额云账单。报告指出,“LLMjacking”正形成包含“LLM Mixers”等凭据汇聚网关的犯罪生态;其中 UNC6993 相关活动据报产生了超过 10 万美元的费用。

深度见解

这些发现凸显了 AI 基础设施凭证和预算面临的直接风险,也表明非法模型访问正在发展为专业化的网络犯罪市场。

  • Cybercriminals are stealing AI API keys and cloud credentials to hijack expensive LLM services and infrastructure
  • Stolen access is used to run AI workloads, create proxy services, and rack up massive bills for victims
  • Google warns “LLMjacking” is evolving into a specialized cybercrime ecosystem with dedicated monetization operators

Threat actors are using large language models (LLM) to support almost every stage of a cyberattack, from researching potential victims to developing malware and automating various attacks. However, using AI is not cheap, and for those eager to use frontier models, costs can stack up relatively quickly.

But cybercriminals are used to stealing things, so why not steal someone else’s tokens, too?

A new report from Google’s Threat Intelligence Group (GTIG) says that different hacking groups are doing exactly that and that the practice - known as LLMjacking - has been steadily growing more popular over the last couple of years.

Most groups start by focusing either on publicly exposed LLM endpoints, or on obtaining valid LLM application programming interface (API) keys. In many cases, the crooks would use exposed or stolen cloud identity tokens (IAM credentials, Service Account keys, GitHub Personal Access Tokens, and active session tokens) to establish an initial foothold into the target organizations’ infrastructure.

#Google Threat Intelligence Group#Google#LLMjacking#LLM Mixers#UNC6993#D1337-KAIROS#Node.js

原文约 3 分钟读完阅读原文
群聊

还没有评论,来说说你的看法。