Steven Gonsalvez

Software Engineer

LLMs could control their host machines by exploiting inference engines

Why CEREBRO kept it

LLM safety/inference engine mechanics, agentic threat

The text below is an automated extraction of the article at https://boydkane.com/essays/llms-could-control-their-host-machines-by-exploiting-inference-engines, stored verbatim in the public cerebro-vault repository. Copyright remains with the original publisher (boydkane.com).

| Read on LessWrong | Large language models often take actions running on one computer (via an agentic harness such as Claude Code or Codex), however the LLMsâ responses to prompts are computed on a different computer with GPU access. Could a malicious LLM gain control of the host machine where its weights are loaded? Such a machine is a high-value target: it has sufficient compute to run a frontier LLM, offers easy access to the LLMâs weights, and has privileged access to other computers in the datacentre compared with a generic computer on the internet. This essay explores how easily a malic

Community take

The article misunderstands LLM architecture and misplaces the security responsibility—sandboxing belongs in infrastructure (VMs/containers), not the harness.

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Shares tags: ai/agents · ai/llm-mechanics · cerebro/signal

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