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New SEEK agent extracts protected skills from science AI agents

By PulseAugur Editorial · [1 sources] ·

A new research paper introduces SEEK, a self-evolving red-teaming agent designed to extract protected skills from science agents. The study found that all eight tested science agent platforms leaked at least one protected skill, with some achieving 100% attack success on the first direct request. SEEK demonstrated effectiveness by achieving 100% attack success on specific skills from SpatialAgent and Biomni, reducing the rounds needed for successful attacks compared to other probing methods. AI

IMPACT Highlights a critical security vulnerability in current science agents, necessitating more robust defenses against adaptive attackers.

RANK_REASON Research paper detailing a new method for evaluating 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 →

New SEEK agent extracts protected skills from science AI agents

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14 / 100
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Research paper detailing a new method for evaluating AI agent security. [lever_c_demoted from research: ic=1 ai=1.0]
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High
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Cheng Gui, Xiang Zheng, Xingjun Ma, Kaidi Xu, Cong Wang, Weiying Ma ·

    SEEK: Skill Extraction with Evolving Knowledge against Frontier Science Agents

    arXiv:2610.34365v1 Announce Type: cross Abstract: Science agents increasingly package domain expertise as reusable skills that plan analyses, select tools, and execute workflows. This modularity creates a confidentiality risk: the interactions that deliver a skill's capability ca…

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