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Oct 13 · Tuesday

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Found 5 papers
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Attack type

Prompt injection4Poisoning and backdoors4

Attack technique

Gradient and representation optimization10Automated search9Encoding and obfuscation5Cross-modal payloads13Dormant triggers7

System type

AI Agent4

Attack surface / entry point

Retrieval corpus3

Layer

Prompt layer12Application layer5Training and data layer0

System component

MCP and skills7Memory3RAG3Guardrails and judges6Vision2
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Attack technique：Encoding and obfuscationLayer：Application layerLayer：Training and data layerSystem component：RAGSystem component：VisionClear all

Another 213papers do not have category tags yet and are not included in filtered results.

  1. Evaluation and benchmarksarXiv 2609.35912

    MMSkillRisk：多模态技能图像中的隐藏指令可诱导 Agent 执行未授权操作

    提出 MMSkillRisk 基准，评测多模态技能图像中的隐藏指令诱导 Agent 越权操作

    arXiv
    2609.35912
    Published
    Layer
    Application layer
    Setting
    coding agent
    Evaluated models
    GPT-5.6-sol, Kimi-K2.6, Kimi-K3 and others6

    Abstract论文提出 MMSkillRisk 基准与 NCVA 攻击，揭示多模态技能中教学图像潜藏指令可引发未授权操作并与良性任务共存。

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  2. AttacksarXiv 2603.17239

    LAAF: A Systematic Red-Teaming Method and Automated Attack Framework for LPCI Vulnerabilities in Agentic LLM Systems

    Proposes LAAF, which automatically attacks LPCI vulnerabilities in agent systems in stages

    arXiv
    2603.17239
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    gemini-2.0-flash-001, claude-3-haiku-20240307, meta-llama/llama-3.1-70b-instruct and others5
    AbstractLAAF does LPCI red teaming with taxonomy plus stage seeding.

    The authors state that LAAF is an automated red-teaming framework built specifically for LPCI in agentic LLMs. The issue to address is that encoded, delayed, and conditionally triggered payloads can persist in memory or RAG and re-enter across sessions, whereas Garak and PyRIT do not use the previous round's breakthrough results to seed the next stage across the six stages.

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  5. AttacksarXiv 2507.10457

    论文提出 LPCI：针对 Agent 逻辑层与持久记忆的提示控制注入攻击

    提出 LPCI，把延迟条件载荷写入记忆与检索库以跨会话触发

    arXiv
    2507.10457
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    ChatGPT, Claude, LLaMA3 and others8
    Abstract作者定义 LPCI。

    作者把LPCI定义为针对智能体逻辑执行、记忆留存和工具集成的跨阶段漏洞类，而不是单次输入上的提示改写。

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