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English(EN) 7 of 10 Prompt-Injection Payloads Broke My Commit-Message Generator's System Prompt

提示注入绕过了Claude模型的提交消息生成

一位开发者测试了其使用Anthropic的Claude模型的提交消息生成工具的提示注入漏洞。在十个自定义载荷中,有七个成功绕过了系统提示的限制,导致了意外的输出,例如添加了联合作者行或AI归属。经典的提示注入技术,如“忽略指令”或“伪造系统标签”,无效,但嵌入在diff文本中的请求微小例外情况的载荷是成功的。 AI

影响 凸显了基于LLM的工具中潜在的漏洞,强调了对健壮的输入验证和安全措施的需求。

排序理由 该条目描述了对特定工具的提示注入漏洞的测试,而不是新的模型发布或重大的行业事件。

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 →

提示注入绕过了Claude模型的提交消息生成

本文如何被排名

Signal score
38 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
该条目描述了对特定工具的提示注入漏洞的测试,而不是新的模型发布或重大的行业事件。
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]

  1. dev.to — LLM tag TIER_1 English(EN) · Enjoy Kumawat ·

    10个提示注入载荷中有7个破坏了我的提交消息生成器的系统提示

    <p>Every few days someone on here posts a number from a prompt-injection test they ran against their agent, and every time I read it I wonder how it would hold up against mine. I have a small, boring, perfect target sitting in my own repo: a tool called <code>generate_commit_mess…