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OpenRouter实测Armor防御提示注入

AI 总结

OpenRouter用文档摘要助手对四个模型进行了25项提示注入攻击测试,对比不同防护配置。报告称,Armor可拦截工具调用,使攻击邮件从1,440次尝试中的73次成功降至零;仅把文档标记为数据时,720次尝试中仍有13次成功。Armor几乎放行用户明确要求的邮件,但因用户未指明收件地址而误拦截了一次合法请求。

深度见解

OpenRouter的测试显示,应用层工具调用规则可能阻止间接提示注入驱动智能体执行不当操作,但这项由单一厂商发布的评估仍存在误拦截。

How to Prevent Prompt Injection: 13 Attacks, Tested

OpenRouter ·10/29/2026

How to Prevent Prompt Injection: 13 Attacks, Tested
How to Prevent Prompt Injection: 13 Attacks, Tested

If your app has a model read documents, emails or web pages, anyone who can write in those can try to give the model instructions. That is prompt injection. The worst case is an agent that uses its tools because a document told it to, for example by sending your data to an outside address.

To prevent prompt injection, mark untrusted content as data, limit which models and how much spend a key can reach, and check every tool call against rules the model can’t change. We ran 13 attacks from our own set plus 12 written by other models against four current models, with each defense on and off. With Armor checking tool calls, attack emails went from 73 of 1,440 attempts to 0. Armor let through almost every email a user asked for. The exception was a user approving a request in the document without naming the address.

#OpenRouter#OpenRouter Armor#Claude Haiku 5.5#GPT-6 Luna#DeepSeek V4.1 Flash#GLM 5.3 Flash#DocBot

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