LinuxArena: A Control Setting for AI Agents in Live Production Software Environments
Abstract
We introduce LinuxArena, a control setting in which agents operate directly on live, multi-service production environments. LinuxArena contains 20 environments, 1,671 main tasks representing legitimate software engineering work, and 184 side tasks representing safety failures such as data exfiltration and backdooring, making it the largest and most diverse control setting for software engineering to date. We validate LinuxArena is useful for control research by running sabotage evaluations, which measure whether attackers can complete side tasks while working on main tasks, and monitor evaluations, which measure a monitor model's ability to detect sabotage attempts. Against a GPT-5-nano trusted monitor at a 1\% step-wise false positive rate, Claude Opus 4.6 achieves roughly a 23% undetected sabotage success rate. We additionally release LaStraj, a dataset of human-crafted attack trajectories that evade monitors at substantially higher rates than any model-generated attacks we elicited, showing that current attack policies do not saturate LinuxArena. These results suggest that LinuxArena has meaningful headroom for both attackers and defenders, making it a strong testbed for developing and evaluating future control protocols.
Cite
@article{arxiv.2604.15384,
title = {LinuxArena: A Control Setting for AI Agents in Live Production Software Environments},
author = {Tyler Tracy and Ram Potham and Nick Kuhn and Myles Heller and Anshul Khandelwal and Cody Rushing and Henri Lemoine and Miguel Brandao and Tomas Turlik and Adam Hanson and Josh Hills and Amy Ngo and Ram Rachum and Nik Mitchell and Falko Galperin and Oscar Sykes and Pip Arnott and Samuel Prieto Lima and Carlos Giudice and Matt Goldwater and Daniel Popp and Drew de Wet and Ruben Castaing and Qi Guo and Douw Marx and Benjamin Shaffrey and Justin Shenk and Martin Milbradt and Hannah Meagher and Shaheen Ahmed-Chowdhury and Daniel O'Connell and Chris Canal and Buck Shlegeris and Aryan Bhatt},
journal= {arXiv preprint arXiv:2604.15384},
year = {2026}
}