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English(EN) One adversarial line before signing took signed agent handoffs from 8.3% violations to 75.0% on GPT-5.6-luna, and the HMAC then authenticated the corrupted mani

对抗性提示将 GPT-5.6 Luna 的错误率提高到 75%,HMAC 验证恢复了安全性

一项在 Mastodon 上进行的研究探讨了 AI 系统中代理交接的安全影响,特别是针对 GPT-5.6 Luna。研究人员发现,当代理在签署任务时,一行对抗性代码可以将错误率从 8.3% 大幅提高到 75.0%。然而,当 HMAC 验证应用于清单时,系统在合成任务中实现了零错误率,表明其能够有效防御此类操纵。 AI

影响 强调了 AI 代理交接中潜在的漏洞以及身份验证机制在降低风险方面的有效性。

排序理由 该集群描述了一项关于 AI 代理安全和模型漏洞的研究,发表在 arXiv 上。[lever_c_demoted from research: ic=1 ai=1.0]

在 Mastodon — mastodon.social 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

对抗性提示将 GPT-5.6 Luna 的错误率提高到 75%,HMAC 验证恢复了安全性

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该集群描述了一项关于 AI 代理安全和模型漏洞的研究,发表在 arXiv 上。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · shellonline ·

    一条对抗性指令在签署前,使签署的代理移交从 8.3% 的违规率降至 GPT-5.6-luna 上的 75.0%,然后 HMAC 验证了损坏的 mani

    One adversarial line before signing took signed agent handoffs from 8.3% violations to 75.0% on GPT-5.6-luna, and the HMAC then authenticated the corrupted manifest. Same preregistered study, synthetic tasks: in transit, signing works (unsigned manifests committed violations in 7…