SideKernel: A Usable microVM Sandbox for AI Coding Agents on macOS

arXiv:2610.02456 · cs.CR, cs.AI · Submitted 2026-10-01 · Read on arXiv

cs.CR, cs.AI

Submitted: 2026-10-01

Updated: 2026-10-01

Comments: 17 pages, 5 figures, 9 tables. Georgia Tech M.S. Cybersecurity practicum project

Code: https://github.com/Zouuup/landrun

License: http://creativecommons.org/licenses/by/4.0/

The gist: AI coding agents are untrusted system components, yet they require autonomy on the developer machines they run on.

Abstract

AI coding agents are untrusted system components, yet they require autonomy on the developer machines they run on. This contradiction is a security problem. Sandboxes provide an isolated environment, but for local macOS development, the existing local, open-source options for AI coding agents are few in number and cumbersome to use. I conducted a formative online user survey which indicates that fewer than 40% of AI coding agent users run their agents in a sandbox and identifies the top usability barriers hindering AI coding agent sandbox adoption. These findings are used to develop SideKernel: an open-source, local, microVM-based macOS sandbox for AI coding agents designed for usability. To evaluate SideKernel, I compiled a list of sandboxes available on the market and filtered it against five inclusion criteria. Then I performed a comparative analysis between SideKernel and the sandboxes that satisfy these criteria, across 23 capability tests derived from the usability barriers revealed by the user survey. I discovered that only a few sandboxes are similar to SideKernel, and that among those, Docker Sandboxes and SideKernel score highest on capability features related to usability. A secondary contribution of this paper is a survey of the existing solution space for local, open-source, microVM-based macOS sandboxes for AI coding agents.

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