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Oct 13 · Tuesday

All papers

Found 8 papers

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  1. AttacksarXiv 2610.04589

    StegoMemory red team testing: agent persistent memory can be used as a cross-session covert channel

    提出 StegoMemory,评测智能体持久记忆作为跨会话隐写信道

    Published
    Setting
    AI Agent
    Evaluated models
    Llama 3.1 405B, Claude 3.5 Sonnet, GPT-4o and others13

    Abstract研究揭示智能体持久记忆可作为隐蔽信道跨会话传输机密,写入持久化是主要防御瓶颈,呼吁建立记忆完整性防御。

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  2. AttacksarXiv 2608.06862

    SynChain:诱导计算机使用 Agent 自建攻击链并跨任务持久化

    提出 SYNCHAIN,诱导计算机使用 Agent 自建跨任务持久攻击链

    Published
    Evaluated models
    Qwen3.5-9B, Llama-3.1-8B, Ministral-3-8B

    Abstract论文揭示了 CUA 自合成工件带来的内部供应链威胁,验证了潜伏载荷的跨任务传播能力与防御局限。

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  3. 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

    Published
    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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  4. AttacksarXiv 2603.00131

    Thought Virus: viral misalignment induced by subliminal prompts in multi-agent systems

    Propose Thought Virus, which propagates preferences along multi-agent messages via subliminal prompts.

    Published
    Evaluated models
    Qwen2.5-7B-Instruct, Llama-3.1-8B-Instruct
    AbstractThought Virus spreads a single-point bias downstream.

    Thought Virus puts subliminal prompting into multi-agent communication, to see whether a single-point deviation spreads across the network without naming the target concept.

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  5. AttacksarXiv 2602.08563

    Stateless yet not forgetful: implicit memory in LLMs as a hidden channel

    提出隐式记忆时间炸弹,使模型跨独立交互累积隐藏状态后激活

    Published
    Evaluated models
    GPT-4o, GPT-4.1, GPT-5.2 and others12
    Abstract作者展示时间炸弹可由提示词或微调诱导。

    作者把这篇工作定位为立场论文:再摄入存在时,按无状态设计的 LLM 仍可能经自身输出携带状态。要处理的问题是,这种不依赖外部记忆模块的通道会让风险跨过单次请求,而单触发测试看不到完整条件。

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  6. AttacksarXiv 2601.01296

    Aggressive compression enables LLM weight stealing

    提出面向渗出的权重压缩,评估推理服务器权重窃取可行性

    Published
    Attacker
    White-box
    Evaluated models
    Qwen2-1.5B, Qwen2-7B, Qwen2.5-1.5B and others8
    Abstract作者用残差量化加微调压缩权重,并称法医水印便宜且微调后仍可解码。

    这篇工作把 LLM 权重渗出看成 APT:攻击者已有未加密权重,但必须把完整权重藏进推理 API 的合法输出。作者认为可压缩性是被忽略的因素,因为推理量化要求解压后仍能低开销前向,而偷权重的人可以接受事后微调。

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  7. 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

    Published
    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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