#computer-using-agents News & Analysis

AIBearisharXiv – CS AI · Jun 57/10

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Domain-Conditioned Safety in Frontier Computer-Using Agents: A 793-Episode Browser Benchmark, a Coding-Domain Cross-Reference, and a Reproducibility Audit of Recent Red-Teaming

Researchers challenge the credibility of recent computer-using agent (CUA) red-teaming studies by reproducing published prompt-injection attacks against frontier models Claude Sonnet 4.6 and GPT-5.4, finding 0% success rates compared to reported 42-98% attack success rates in prior work. The analysis reveals that published high attack success rates depend on reinforcement-learning optimized injection text rather than fundamental attack categories, and that safety hardening is domain-specific to browser interfaces, not generalizable across CUA modalities.

🧠 GPT-5🧠 Claude🧠 Sonnet

AINeutralarXiv – CS AI · Jun 196/10

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Automating SKILL.md Generation for Computer-Using Agents via Interaction Trajectory Mining

Researchers developed a three-stage pipeline to automatically extract skill libraries from computer-using agent interaction data, achieving high readability (95% purity on labeled benchmarks) but failing to improve downstream policy performance across domains. The study reveals that while trajectory mining can expose interpretable skill structure, current technical limitations prevent reliable cross-domain transfer improvements.