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Loading.It's a real risk, and no prompt fixes it. Once an agent can run tools, prompt injection becomes code execution: a poisoned file's hidden instruction runs with the agent's permissions. OWASP ranks it the top LLM risk, and in 2026 it turned into real code execution in shipping tools. Make agents safe by treating them as an untrusted client: least-privilege credentials, sandboxed execution, a human gate on the irreversible, and audited tool calls.
A chatbot that gets injected says something wrong; a coding agent that gets injected can do something wrong, because it's wired to a shell, a package manager, and your credentials. The injected instruction arrives in the same context as yours and the model can't reliably tell them apart.
Telling the model to ignore injected commands is like telling a SQL query not to be injected. Adaptive attacks bypass prompt-level defenses well over 80% of the time. The boundary has to live in the system around the model, where it's enforced, not requested.
We scope the agent's own credentials (never a dev's god-key), sandbox its execution away from prod and secrets, gate the irreversible to a human, and audit every tool call — so when an injection lands, the blast radius is small and visible.
or have us build it — same capability, the other door