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

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.

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

Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI)

arXiv:2610.02456 [cs.CR]

(or arXiv:2610.02456v1 [cs.CR] for this version)

https://doi.org/10.48550/arXiv.2610.02456 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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