arXiv AI

How Agents Ask for Permission: User Permissions for AI Agents, from Interfaces to Enforcement

arXiv:2607. 13718v1 Announce Type: cross Abstract: As AI agents gain prevalance, users are increasingly exposed to the risks such systems entail.

arXiv AI
Sep 15

Empirical Evaluation of Task-Based Permission Scoping Architecture for AI Agents

The paper evaluates a task-based permission scoping architecture for AI agents, comparing a fine‑tuned RoBERTa‑large encoder to few‑shot Claude Haiku 4.5 on a 600‑prompt dataset. It shows the new system achieves comparable macro‑F1 (0.881 vs. 0.886) and higher precision (0.897 vs. 0.842), while reducing severity‑weighted residual risk from 1.12 to 0.63. The study also introduces an attack‑surface elimination metric, demonstrating that task‑granular control can close 84.4% of the severity‑weighted surface, far surpassing role‑based ceilings alone.

By Halil Burak Noyan
Hugging Face Trending Papers
Jun 22

Intent-Governed Tool Authorization for AI Agents

AI agents increasingly act through external tools: they read private data, construct structured payloads, submit write requests, export records, and coordinate workflows across application boundaries. Existing authorization mechanisms usually ask whether an integration credential, app, or token can call a tool.

arXiv AI
4d ago

CoSec: Benchmarking Agent Security in Communities

arXiv:2609.34790v2 Announce Type: replace-cross Abstract: LLM agents operate in persistent collaborative environments involving multiple users, communities, memories, files, and tools. Community boun...

By Hao Chen, Wenhui Dong, Ye Chen, Jiezhi Yao, Chenbo Xia, Yuwen Qu, Renxiang Wang, Fudong Yuan, Camil Hamami, Chenglong Pan, Xinquan Yue, Ziyu Wang, Fengyu Ye, Chenyang Si, Caifeng Shan