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Oct 13 · Tuesday

All papers

Found 3 papers
Filter4

Attack type

Extraction and theft3

Impact

Data and privacy leaks3Output manipulation5

System type

LLM applications3

Layer

Application layer3Infrastructure layer0

System component

MCP and skills16Memory13RAG10Guardrails and judges4Monitors7Permissions and sandboxing11Vision4Embeddings3Multimodal4
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Impact：Data and privacy leaksLayer：Application layerLayer：Infrastructure layerSystem component：EmbeddingsClear all

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  2. DefensesarXiv 2609.04767

    SHAQ: Privacy-preserving retrieval in vector databases using shadow queries

    Proposes SHAQ, which replaces document embeddings with shadow query embeddings to defend against embedding inversion.

    arXiv
    2609.04767
    Published
    Layer
    Application layer
    Setting
    LLM applications
    Attacker
    Black-box
    Evaluated models
    GTR-T5 encoder, DPR
    AbstractSHAQ replaces document embeddings with shadow query embeddings.

    SHAQ is a defense against EIA for cloud vector databases: instead of directly modifying document embeddings, it replaces them with shadow query embeddings.

    Paper analysisRead analysis
  3. AttacksarXiv 2607.01276

    研究者提出嵌入推断攻击 EIA，可在黑盒 IR 系统中识别所用嵌入模型

    提出嵌入推断攻击 EIA，在黑盒 IR 中识别所用嵌入模型

    arXiv
    2607.01276
    Published
    Layer
    Application layer
    Setting
    LLM applications
    Attacker
    Black-box
    Evaluated models
    e5-small, e5-small-v2, e5-base and others19
    AbstractEIA 用无序文档集的差异从候选中识别嵌入模型，并给出 reranker 与阈值下的计数。

    EIA 是在黑盒 IR 上识别所用嵌入模型的攻击。。

    Paper analysisRead analysis
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