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Oct 12 · Monday

Backdoors and poisoning · Papers

Found 5 papers
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Attack type

Poisoning and backdoors5

Attack technique

Automated search1Defense-targeted4Dormant triggers23

Impact

Output manipulation4

System type

Models and APIs4

Attack surface / entry point

Training data4

Layer

Training and data layer4

System component

Fine-tuning and open weights5
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Attack technique：Automated searchAttack technique：Defense-targetedTopic: Backdoors and poisoningClear all
  1. AttacksarXiv 2610.07723

    Researchers propose answer-side backdoors: letting the model self-generate trigger words to bypass safety refusals.

    提出回答端后门，让模型自生成触发词以在干净有害请求下绕过拒答

    arXiv
    2610.07723
    Published
    Layer
    Training and data layer
    Setting
    Models and APIs
    Evaluated models
    Llama-2-7B-chat-hf, Mistral-7B-Instruct-v0.3, Gemma-7B-it and others4

    Abstract论文提出了多轮对话中回答端自生成触发词绕过安全拒绝的后门攻击，指出输入端防护存在盲区。

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  2. AttacksarXiv 2609.37468

    论文提出针对 Agentic RAG 的检索器后门攻击与 DOU 隐藏方法

    提出检索器后门攻击操纵智能体搜索，并用 DOU 逃避检测

    arXiv
    2609.37468
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    E5, Contriever-MSMARCO

    Abstract论文展示了通过恶意检索器操纵智能体多轮搜索并利用诱饵重塑表征隐蔽后门的可行性与系统风险。

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  3. AttacksarXiv 2609.27422

    RAMP：逆转对抗扰动以增强针对恶意软件检测器的干净标签后门攻击

    提出 RAMP，逆转对抗扰动加强恶意软件检测器的干净标签后门

    arXiv
    2609.27422
    Published
    Layer
    Training and data layer
    Setting
    Models and APIs
    Evaluated models
    MalConv, MalConvGCG
    AbstractRAMP 用反转扰动做 clean-label 投毒。

    RAMP 是 score-based black-box 下的 clean-label 后门增强，对象是会微调的 Windows PE 原始字节恶意软件检测器。

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