How We Know Pre-Action Gates Work

Authors: Igor Ganapolsky
Status: Preprint PDF + LaTeX sources (arXiv submission package prepared; arXiv ID pending announcement)

Abstract

AI coding agents repeatedly commit the same high-cost failures. Pre-action enforcement intercepts tool calls before execution and decides allow, warn, or deny. This paper presents a practical evaluation framework for infrastructure firewalls on coding agents, instantiated by ThumbGate, with seven proof dimensions and re-runnable evidence paths.

Files

  • main.pdf β€” compiled preprint
  • main.tex β€” LaTeX source (arXiv-ready)
  • arxiv-src.tar.gz β€” source bundle for arXiv upload

Linked artifacts

arXiv

Primary category intended: cs.SE (cross-list cs.AI).
After arXiv assigns an ID, this card will be updated and the paper will be indexed at https://huggingface.co/papers/<arxiv-id> and claimed on the author profile.

Citation

@misc{ganapolsky2026preaction,
  title={How We Know Pre-Action Gates Work: An Evaluation Framework for Infrastructure Firewalls on AI Coding Agents},
  author={Ganapolsky, Igor},
  year={2026},
  howpublished={Hugging Face Hub preprint},
  url={https://huggingface.co/IgorGanapolsky/thumbgate-pre-action-gates-paper}
}
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