arXiv — cs.AI preprintsInternational7 October 2026
OSGuard: A Benchmark for Safety in Computer-Use Agents
This is an official announcement record
Firsthand records what arXiv — cs.AI preprints announced and links to the original. The wording below is theirs, not ours.
arXiv:2606.15034v2 Announce Type: replace Abstract: Computer-use agents can complete benign user instructions while violating important constraints of the user's environment. We introduce OSGuard, a dual-granularity benchmark suite for evaluating safety through local, pre-execution guardrail decisions and end-to-end task execution. Its action-level benchmark contains 324 human-annotated examples in which guardrails classify candidate actions as allowed, unrelated, or unsafe given the original instruction and current interface state. Its risk-augmented execution suite contains 45 tasks derived
Read the official announcement
Opens arxiv.org
More from arXiv — cs.AI preprints
- GAMEGO: Training Game-Dev Agents with Synthetic Trajectories Anchored in Real-World Assets7 October 2026
- Text2Dashboard: A Governed Agent Architecture for Natural-Language Dashboard Generation over Enterprise DataBrain7 October 2026
- FluidPD: In-Place Elasticity for SLO-Aware Prefill-Decode Disaggregated LLM Serving7 October 2026
- Anchor Divergence for Semantic Geometry in Contrastive Learning7 October 2026
- RadOnc-Agent: An LLM-Orchestrated Framework for AI Workflows Across the Radiotherapy Care Pathway7 October 2026
This content is for informational purposes only and is not professional advice. Specifications, prices, plan tiers, and features change frequently and may differ from what is shown here; verify current details on the manufacturer's or company's official page before purchasing. Ratings are based on analysis of published documentation, not independent lab testing.