Working with AI agents and Large Language Models introduces new security dimensions where text becomes vulnerable and can have executable intent. The three critical pillars that make agents vulnerable are: (1) access to privileged information or private data, (2) exposure to untrusted content from the outside world, and (3) the ability to communicate externally. Most agents by default possess all three of these capabilities simultaneously, creating a significant security risk.
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The New Security Rules for Agentic Coding本站收录:
Your AI coding agent has access to your secrets, pulls in content from the outside world, and can run shell commands. According to Joe Holdcroft, that combination makes you one prompt injection away from a very bad time. The tools haven't changed the fundamentals of security — they've just made every existing risk move faster, and introduced a few genuinely new ones. **In this episode** - Why the "lethal trifecta" of agent capabilities creates a novel threat surface - How text and markdown files have become a new class of vulnerability - Slop squatting: the attack vector created by agents hallucinating package names - The context supply chain — and why it mirrors the early days of npm security - What a "CBOM" (context bill of materials) might look like and why we may need one - How to think about agent trust using the contractor mental model
Working with agents and LMS introduces some new dimensions on security that we wouldn't normally think about. Text becomes something that can be vulnerable, can have some executable intent. A couple years ago, you would never worry about the security of a markdown document, a combination of some access to privileged information or some private data, some exposure to some untrusted content maybe from the outside world, and the ability to communicate externally. Most agents by default are going to have all of these three things and that is where you're one prompt injection away from uh let's say bad time.
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