arXiv:2607. 13718v1 Announce Type: cross Abstract: As AI agents gain prevalance, users are increasingly exposed to the risks such systems entail.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.
arXiv:2607. 01510v1 Announce Type: new Abstract: AI agents that autonomously execute tool calls on a user's behalf raise pressing questions about permission management: what role could users play, and what role should they play?
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.
arXiv:2604.19657v2 Announce Type: replace-cross Abstract: AI agents promise to serve as general-purpose personal assistants for their users, which requires them to have access to private user data (e...
arXiv:2601.12449v2 Announce Type: replace-cross Abstract: AI agents are autonomous systems that combine LLMs with external tools to solve complex tasks. While such tools extend capability, improper t...
arXiv:2607. 22611v1 Announce Type: new Abstract: The deployment of autonomous AI agents in production infrastructure introduces fundamental security challenges that traditional role-based access control (RBAC) models cannot address.
arXiv:2607. 21325v1 Announce Type: cross Abstract: Autonomous AI agents increasingly execute actions, invoke tools, and operate on protected resources with limited human oversight.