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Oct 12 · Monday

All papers

Found 6 papers
Filter4

Attack type

Prompt injection6Poisoning and backdoors3

Attack technique

Dormant triggers3

Impact

Unauthorized actions4

System type

Models and APIs3AI Agent46coding agent3Multi-agent systems3

Attack surface / entry point

User input14Tool responses3Tool and skill descriptions14Code repositories and dependencies10Memory writes3Inter-agent messages8Training data3Weights and gradients4Distribution channels16

Layer

Application layer6

System component

Memory3
Select any value within a category; different categories must all match. Counts include the other filters you have selected.Another 247papers have no tags yet and are not included in filtered results.
System type：coding agentSystem type：Multi-agent systemsAttack surface / entry point：Tool responsesAttack surface / entry point：Memory writesClear all

Another 247papers do not have category tags yet and are not included in filtered results.

  1. AttacksarXiv 2609.18217

    研究：跨通道碎片化攻击可绕过 MCP 单通道防御

    提出跨通道分段攻击，利用 MCP 隐式信任外发敏感文件

    arXiv
    2609.18217
    Published
    Layer
    Application layer
    Setting
    coding agent
    Evaluated models
    GPT-4o, GPT-4o-mini, GPT-5.4 and others15

    Abstract论文揭示了 MCP 多通道隐式信任层级，通过跨通道分段与协议级利用突破现有防御，展示了严重的凭证外发风险。

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  3. AttacksarXiv 2607.11698

    AHA 用自动研究循环发现生产 Agent 漏洞概念

    提出 AHA 自动科研循环，发现生产 Agent 的可复用漏洞概念

    arXiv
    2607.11698
    Published
    Layer
    Application layer
    Setting
    coding agent
    Attacker
    Black-box
    Evaluated models
    Minimax-M2.7, Kimi-K2.6, Deepseek-V4-Pro and others5
    Abstract论文提出基于可证伪科研循环的 AHA 框架，从生产级智能体中挖掘并沉淀漏洞概念图，提升攻击复用率并指导防御加固。

    AHA 是一项针对生产级 LLM 智能体自动化红队测试的研究，旨在解决传统方法仅保留具体攻击载荷而缺乏成因解释、导致跨版本复用困难且无法指导修复的问题。

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  5. AttacksarXiv 2605.08460

    论文建模多智能体网络中的子智能体继承攻击面

    建模并利用多智能体网络中子智能体生成时的记忆继承漏洞

    arXiv
    2605.08460
    Published
    Layer
    Application layer
    Setting
    Multi-agent systems
    Evaluated models
    MiniMax M2.5, Llama-4-Maverick-17B-128E-Instruct-FP8, Qwen3.5-Plus and others5
    Abstract形式化子智能体继承，在 OpenClaw 上演示四类编排层漏洞并提出防御。

    作者对多智能体网络里的子智能体继承做形式化分析，并用开源框架上的 PoC 演示编排层如何让单点妥协继续扩散。

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  6. AttacksarXiv 2601.00240

    When agents view humans as out-group: belief-dependent bias in LLM-driven agents

    提出 BPA 改写 profile 与记忆，重新诱发智能体对人类的外群体偏向

    arXiv
    2601.00240
    Published
    Layer
    Application layer
    Setting
    Multi-agent systems
    Evaluated models
    gpt-4o-mini
    Abstract最小群体线索下出现内群体偏向。

    作者考察 LLM 智能体在任意群体边界下会不会把人类当外群体，并用信念投毒检验面向人类的抑制是否依赖身份信念。

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