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Oct 12 · Monday

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  1. 研究者提出技能级联攻击

    提出技能级联攻击,把有害目标拆散到多个技能里绕过单技能扫描

    Published
    Setting
    AI Agent
    Evaluated models
    GPT-5.4, GPT-5.4 Mini, Claude Opus 4.6 and others11

    Abstract论文探讨了多技能智能体系统面临的技能级联攻击风险,提出自动化红队框架与基准集,指出跨技能交互存在安全防护盲区。

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  2. CompoSkill 框架利用逐个通过扫描的 Agent 技能组合发起攻击

    提出 CompoSkill,将逐个通过扫描的技能编排为攻击链

    Published
    Setting
    AI Agent
    Evaluated models
    GPT-5.4, Gemini-3.1-flash, DeepSeek-V4 and others4

    Abstract论文分析了智能体技能组合风险,指出单包安全认证状态不具备可组合性,需转向路径级防护。

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  3. LogInject 框架披露 LLM 日志分析中的被动提示注入

    提出 LogInject 框架,评测日志分析中的被动提示注入及缓解

    Published
    Evaluated models
    GPT-4o, Claude 3.5 Sonnet, Llama-3-70B-Instruct

    Abstract论文评估了 LLM 日志分析中的上下文污染风险,提出分片拼接等攻击与三层防御,指出必须结合架构隔离与人工介入。

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