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Oct 13 · Tuesday

All papers

Found 6 papers
Filter5

Attack type

Jailbreaks3Prompt injection4

Attack technique

Gradient and representation optimization3Automated search20Multi-turn escalation7Encoding and obfuscation7Role-play and persuasion3Conversation structure manipulation2Reasoning-chain manipulation1Defense-targeted11Dormant triggers12Selection manipulation3

Impact

Output manipulation3

System type

AI Agent4

Attacker access

Black-box3

Attack surface / entry point

User input6Web pages and interfaces6Documents and messages5Tool responses4Retrieval corpus6Images, audio and video6

Layer

Prompt layer31Model layer4Application layer6
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Attack technique：Gradient and representation optimizationAttack technique：Conversation structure manipulationAttack technique：Reasoning-chain manipulationAttack surface / entry point：User inputLayer：Application layerClear all

Another 215papers do not have category tags yet and are not included in filtered results.

  2. AttacksarXiv 2610.04985

    研究揭示 Jev 作为应用决策层的安全与隐私风险

    评估应用决策层的输入注入与隐私推断风险

    arXiv
    2610.04985
    Published
    Layer
    Application layer
    Setting
    LLM applications
    Attacker
    Black-box, Gray-box
    Evaluated models
    Jev, NanoJev
    AbstractJev 的类型化决策可被输入与训练操纵，也会泄露信息，并同时支持检测与滥用。

    Jev 是 TypeSafe 的 System One 模型，把应用 state 和固定问题变成 Choice、Noul 或 Score 的类型化决策与概率。作者用官方 API 和可改训练的 NanoJev，考察它作为决策层时的操纵、泄露与双重用途。

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  4. AttacksarXiv 2603.12277

    Prompt injection is role confusion

    提出 CoT Forgery，经用户消息或工具输出注入伪造推理

    arXiv
    2603.12277
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Attacker
    Black-box
    Evaluated models
    gpt-oss-20b, gpt-oss-120b, o4-mini and others11
    Abstract提示注入被作者解释为角色感知失败：听起来像某角色，就在表示里成为该角色。

    作者把提示注入解释成角色感知失败：标签划出的权限没有进入模型的内部几何。

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  6. AttacksarXiv 2509.25624

    STAC：看似无害的工具调用链如何攻破 LLM Agent

    提出 STAC 框架，把恶意目标拆成多轮看似无害的工具调用链

    arXiv
    2509.25624
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Attacker
    Black-box
    Evaluated models
    GPT-4.1-2025-04-14, GPT-4.1-mini-2025-04-14, Qwen3-32B and others8

    Abstract作者提出并验证了智能体在序列化工具攻击下的普遍脆弱性，指出针对累积动作序列防御的必要性。

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