AI & ML
Ring-0 by Default: Agents as Operating Systems (AaOS)
arXiv cs.CR0 views
arXiv:2610.33753v1 Announce Type: new Abstract: LLM agents now read and write files, start processes and subagents, fetch network content, load third-party extensions, and save and resume state, which are the responsibilities of an operating system. They gained these functions within about three years, but not the protections that operating systems built over five decades: whatever the model outputs, whether it follows the user, a tool result, or a downloaded skill, runs with the full authority of the host user, in effect at ring 0. Prior work builds an operating system for agents (OS4A); we argue that a deployed agent already is like an operating system (AaOS) and analyze it as one. Taking the mechanisms of standard OS textbooks as a checklist, we map 116 mechanisms in 19 subsystems to their agent counterparts, from product documentation, source code, and the literature, and label each as isomorphic, degraded (function present, protection dependent on the model), missing, mutated, or novel. Only 11 are isomorphic and 65 are missing, most of them protections: privilege separation, resource quotas, transactions, and tamper-proof audit. Existing defenses confine the whole agent or review its extensions and leave this interior unprotected, and by Anderson's reference-monitor criteria (non-bypassable, tamper-proof, verifiable), rules written in the prompt satisfy none. We test the map with thirteen experiments on Claude Code, Codex CLI, and Gemini CLI, covering 25 mechanisms whose enforcement documentation cannot settle: 16 match the analysis, 7 gain a more precise description, and 2 change verdict. Checks sit in single tools, so the shell bypasses them; all three CLIs load forged transcript records on resume; and task control, sub-agent permissions, and model-based monitors are weak. We identify five problems for which no OS defense transfers and derive a prioritized list of open problems from the gaps of the map.
Source:https://arxiv.org/abs/2610.33753PreviousTrust Mechanisms for Offline Generative AI at the Edge: A Connectivity-Regime Framework and an Empirical Study on a Raspberry Pi 5NextEnhancing LLM-Based Vulnerability Detection via Representation-Aware Logical Ensemble
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