agent/papers/items/2026-2604-13536-don-t-let-ai-agents-yolo-your-files-shifting-information-and-control-to-filesyst.md

Paper: Don't Let AI Agents YOLO Your Files: Shifting Information and Control to Filesystems for Agent Safety and Autonomy

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type: paper title: "Don't Let AI Agents YOLO Your Files: Shifting Information and Control to Filesystems for Agent Safety and Autonomy" authors: Shawn Wanxiang Zhong, Junxuan Liao, Jing Liu, Mai Zheng, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau year: 2026 venue: arXiv url: https://arxiv.org/abs/2604.13536 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-04-15 updated_at: 2026-04-16 status: queued relevance: high topics:

• agent-evaluation
• agent-safety
• coding-agent
• tool-use methods:

benchmarks:

models:

datasets:

• cs.OS related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 16 collection_queries: agent-safety

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: agent-safety
• inferred topics: agent-evaluation, agent-safety, coding-agent, tool-use
• arXiv categories: cs.OS
• collection score: 16

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2604.13536