arXiv — cs.AI preprintsInternational5 October 2026
LPS-Bench: Benchmarking Safety Awareness of Computer-Use Agents in Long-Horizon Planning under Benign and Adversarial Scenarios
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arXiv:2602.03255v2 Announce Type: replace Abstract: Computer-use agents (CUAs) execute multi-stage tasks through tools, where an early unsafe decision can propagate to consequential actions. Evaluating only final outcomes can miss such decisions, while constructing executable environments for new tasks can make benchmark expansion costly. We present LPS-Bench, a benchmark of long-horizon planning safety in MCP-style tool workflows under benign requests and adversarial steering. A template-guided multi-agent pipeline generates user instructions, simulated toolkits, and case-specific safety crit
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