English(EN) System Prompt Confidentiality Is Security by Obscurity

研究人员演示大型语言模型中的系统提示不安全

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-06 04:59

根据一篇dev.to文章，大型语言模型中的系统提示并非安全边界，不应依赖其进行安全防护。研究人员已经展示了多种方法，包括直接提问以及更复杂的策略，如Policy Puppetry和PLeak，来从众多模型中提取这些提示。文章强调了现实世界中提取提示导致敏感信息泄露的事件，例如代号、业务逻辑甚至凭证，从而导致后续的精确越狱和凭证滥用等攻击。 AI

影响强调了大型语言模型系统提示中存在的关键安全漏洞，敦促开发人员重新考虑将其用作安全控制措施。

排序理由文章详细介绍了提示提取技术及其影响的研究。[lever_c_demoted from research: ic=1 ai=1.0]

在 dev.to — LLM tag 阅读 →

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

本文如何被排名

Signal score: 30 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 文章详细介绍了提示提取技术及其影响的研究。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: safety, product; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Breaking (< 6h); Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

报道来源 [1]

dev.to — LLM tag TIER_1 English(EN) · Davi · 2026-09-06 04:59

系统提示词保密是隐晦安全

<h1> System Prompt Confidentiality Is Security by Obscurity </h1> <p>In February 2023, one researcher needed a single chat session to extract Bing Chat's entire system prompt. The extracted content included the instruction never to reveal it. Microsoft confirmed the extracted pro…

本文如何被排名

报道来源 [1]

系统提示词保密是隐晦安全

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