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AI agent security dataset reveals scanner disagreement

By PulseAugur Editorial · [1 sources] ·

A new dataset called ClawHub Security Signals has been released, containing 67,453 OpenClaw skill versions to analyze the security of AI agents. The dataset reveals significant disagreement among three security scanners: VirusTotal, static analysis, and NVIDIA SkillSpector. Each scanner flags different types of risks, with SkillSpector focusing on agentic risks and VirusTotal on traditional malware, highlighting the need for layered security approaches for AI agent skills. AI

IMPACT Highlights the need for multi-layered security approaches for AI agents, moving beyond single-scanner solutions.

RANK_REASON The cluster contains an academic paper detailing a new dataset and research findings on AI agent security. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Vincent Koc, Patrick Erichsen, Jacob Tomlinson, Agustin Rivera, Michael Appel, Nir Paz ·

    ClawHub Security Signals: When VirusTotal, Static Analysis, and SkillSpector Disagree

    arXiv:2606.01494v1 Announce Type: cross Abstract: Agent skills extend AI agents with reusable instructions, tools, scripts, references, and workflows, establishing a security boundary distinct from both model safety and traditional package-malware detection. ClawHub Security Sign…

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