Prompt Injection in Agentic AI
嗯,用户让我总结一下这篇文章的内容,控制在100字以内,而且不需要用“文章内容总结”之类的开头。首先,我得仔细阅读文章,理解主要信息。 文章讲的是作者进行的一次智能AI安全评估的经历。他们评估的产品有一个显著的LLM(大型语言模型)组件,允许用户生成完整的网站。这些网站不仅仅是静态的,还包括了身份验证、用户角色和数据库结构等复杂功能。 作者在评估过程中发现了安全漏洞,并讨论了传统LLM与AI代理之间的差异以及使用的威胁模型。所以,总结时需要涵盖这些关键点:评估对象、生成网站的复杂性、发现的安全漏洞、以及传统LLM与AI代理的区别。 接下来,我需要把这些信息浓缩到100字以内,确保语言简洁明了。同时,避免使用任何开头模板,直接描述内容。 可能的结构是:介绍评估对象和功能,提到发现的安全漏洞,并指出传统LLM与AI代理的区别。这样既全面又简洁。 最后检查一下字数是否符合要求,并确保信息准确无误。 </think> 作者分享了一次对AI生成网站功能的安全评估经验,重点介绍了AI代理与传统LLM的区别、威胁模型及发现的安全漏洞。 2026-1-26 09:13:26 Author: infosecwriteups.com(查看原文) 阅读量:1 收藏

Rahul Singh Chauhan

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Hi everyone

In this article, I’ll be sharing my experience working on an agentic AI security assessment that I conducted a few months ago.

The goal of this write-up is to walk you through:

  • The AI assessment itself
  • The differences between a traditional LLM and an AI agent
  • The threat model used during the assessment
  • A security bug I discovered along the way

The Assessment

I was assigned to an assessment that involved a product with a significant LLM-powered component. The client had recently introduced a feature that allowed users to generate complete websites using AI.

These weren’t just static or basic websites. The generated applications included:

  • Authentication and authorization mechanisms
  • Well-defined user roles
  • A properly structured database schema

Before generating the actual website, the system first created a blueprint. This blueprint outlined:

  • The number of pages and how they were interconnected
  • User roles and permissions
  • The database schema

文章来源: https://infosecwriteups.com/prompt-injection-in-agentic-ai-66b93b52fe48?source=rss----7b722bfd1b8d--bug_bounty
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