For most of the short history of LLM applications, model risk was text risk. A model could output bad advice, leak something from its prompt, or produce a convincing phishing draft — but it couldn't touch your machine. The worst case ended at the screen.
Wire a few tools into that model — a shell, an HTTP fetcher, a filesystem client, a cloud SDK — and the equation changes. With the Model Context Protocol, agents don't just suggest operations anymore; they perform them, with your credentials, on your infrastructure. The attack surface moves from "text the model wrote" to "actions the model took." A prompt that used to produce a paragraph can now produce a process.
If you're shipping agents with tool access, configuration hygiene is necessary but not sufficient. Here's why, and what runtime verification adds.
Four ways tool calls go wrong
The abuse patterns below are well-known categories — described generically, without reference to any specific project's incident
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