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Oct 12 · Monday

All papers

Found 5 papers
Filter5

Attack technique

Gradient and representation optimization5Cross-modal payloads8Dormant triggers3

Impact

Output manipulation4

System type

Models and APIs3

Attack surface / entry point

Images, audio and video5

Layer

Prompt layer3

System component

Memory0Vision24Audio4Embeddings1Multimodal30
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.
Attack technique：Gradient and representation optimizationAttack surface / entry point：Images, audio and videoSystem component：MemorySystem component：AudioSystem component：EmbeddingsClear all

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

  1. AttacksarXiv 2606.12716

    PaperGuard：针对多模态 AI 同行评审的攻击与防御基准

    提出 PaperGuard，用图文注入与梯度扰动抬高自动审稿分数并检测恶意指令

    arXiv
    2606.12716
    Published
    Layer
    Application layer
    Setting
    LLM applications
    Evaluated models
    Claude-sonnet-4.5, GPT-4o, GPT-4.1 and others11
    AbstractPaperGuard 测到提示注入与白盒视觉抬分，并比较分块检索防御。

    PaperGuard同时评测并检测多模态 AI 审稿中的评分操纵。

    Paper analysisRead analysis
  3. AttacksarXiv 2604.14604

    The AudioHijack framework achieves covert audio prompt injection against 13 speech large models

    提出 AudioHijack，用不可感知对抗音频对语音模型做上下文无关提示注入

    arXiv
    2604.14604
    Published
    Layer
    Prompt layer
    Setting
    Models and APIs
    Evaluated models
    SpeechGPT, GLM-4-Voice, VITA-Audio and others15

    Abstract提出了 AudioHijack 框架，揭示了 LALM 对听觉提示注入的脆弱性与传统防御的局限。

    Paper analysisRead analysis
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