Skip to content

Translation in progress Some entries still include text in the original language.

Oct 13 · Tuesday

All papers

Found 11 papers
Filter5

Attack type

Prompt injection7

Attack technique

Gradient and representation optimization3Automated search15Encoding and obfuscation5Role-play and persuasion6Conversation structure manipulation3Reasoning-chain manipulation3Dormant triggers11

Impact

Output manipulation8

System type

LLM applications7AI Agent3

Attack surface / entry point

User input58Web pages and interfaces6Documents and messages8Tool responses5Code repositories and dependencies3Retrieval corpus6Images, audio and video36Training data6Weights and gradients12

Layer

Application layer10
Select any value within a category; different categories must all match. Counts include the other filters you have selected.Another 201papers have no tags yet and are not included in filtered results.
Attack technique：Gradient and representation optimizationAttack technique：Role-play and persuasionAttack technique：Conversation structure manipulationAttack surface / entry point：Documents and messagesAttack surface / entry point：Code repositories and dependenciesClear all

Another 201papers do not have category tags yet and are not included in filtered results.

  1. AttacksarXiv 2609.27542

    Researchers use control token injection to delete gpt-oss-20b's reasoning chain and bypass chain-of-thought monitoring

    提出控制标记注入，清空工具 Agent 的思维链以绕过推理监控

    arXiv
    2609.27542
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    openai/gpt-oss-20b, google/gemma-4-26B-A4B-it, deepseek-ai/DeepSeek-R1-Distill-Qwen-7B and others4

    Abstract论文阐明控制标记注入可抑制 CoT 使监控失效并促成拒绝绕过，且工具执行受解析器宽容度影响。

    Paper analysisRead analysis
  2. AttacksarXiv 2609.19722

    ALIBI：向二进制注入虚假安全叙事可让 LLM 恶意软件分析器误判

    提出 ALIBI，向恶意二进制注入不执行掩护叙事使分析器误判为良性

    arXiv
    2609.19722
    Published
    Layer
    Application layer
    Setting
    LLM applications
    Attacker
    Black-box
    Evaluated models
    Gemini 2.5 Pro, GPT-5.5 Pro, Claude Opus 4.7
    AbstractALIBI 用二进制内的掩护叙事重释可疑静态证据，Gemini 上翻转多，另两模型主要为降级。

    ALIBI 是针对 LLM 恶意软件分诊的语义掩护叙事攻击：不覆盖系统指令，而把仍可见的可疑静态证据重释成良性安全产品的预期行为。

    Paper analysisRead analysis
  3. AttacksarXiv 2608.09867

    Researchers steal proprietary LLM inference chains via cross-model compatibility of encrypted inference blocks

    利用加密思维块的跨模型重放，诱导弱模型逐字转写专有推理链

    arXiv
    2608.09867
    Published
    Layer
    Prompt layer
    Setting
    Models and APIs
    Attacker
    Black-box
    Evaluated models
    Claude Opus 4.8, Claude Sonnet 4.6, Claude Haiku 4.5 and others13

    Abstract论文揭示了客户端加密思维块跨模型互换漏洞，提出了低成本提取方法并给出防御方案。

    Paper analysisRead analysis
  4. 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
  5. AttacksarXiv 2605.24421

    研究者提出日志型提示注入攻击，可抑制 SOC 中 LLM 分析助手的恶意日志识别

    提出日志基底提示注入，操纵 SOC 分析员的分类、摘要与处置建议

    arXiv
    2605.24421
    Published
    Layer
    Application layer
    Setting
    LLM applications
    Evaluated models
    gpt-4o-mini

    Abstract在 gpt-4o-mini 上，人格劫持与上下文操纵可改写 SOC 分析输出，直接覆盖在分类上无效。

    Paper analysisRead analysis
  6. AttacksarXiv 2602.00364

    "Someone hid it": Query-agnostic black-box attacks against LLM retrieval

    提出查询无关黑盒攻击 DQ-A，用可迁移文末后缀降低文档检索排名

    arXiv
    2602.00364
    Published
    Layer
    Application layer
    Setting
    LLM applications
    Evaluated models
    Qwen-1.5-7B-Instruct, SFR-Embedding-Mistral, E5-Mistral-7B-Instruct and others10
    AbstractDQ-A 以无查询黑盒后缀压低 LLM 检索排名，并在 BRIGHT 上比较三种基线。

    DQ-A 是一种 query-agnostic、complete black-box 的文档隐藏攻击，对象是用最后隐层相似度匹配的 LLM 检索。

    Paper analysisRead analysis
  7. AttacksarXiv 2601.21360

    Compliance Paradox: Semantic-Instruction Decoupling in Automated Academic Code Evaluation

    提出 AST-ASIP ，把对抗指令植入编译器忽略区域以劫持代码评分

    arXiv
    2601.21360
    Published
    Layer
    Application layer
    Setting
    LLM applications
    Evaluated models
    DeepSeek-V3.2, Qwen3-235B, GPT-OSS-120B and others9
    Abstract作者称 RLHF 的服从性使评分脱离代码。

    这篇工作把自动代码评分中的失败称为 Compliance Paradox：评分模型可以离开提交逻辑，转而执行嵌在可编译代码里的隐藏指令。

    Paper analysisRead analysis
  8. AttacksarXiv 2601.20283

    One word is enough: Minimal adversarial perturbations for neural text ranking

    提出查询中心词的单次插入或替换攻击，操纵神经排序名次

    arXiv
    2601.20283
    Published
    Layer
    Application layer
    Setting
    LLM applications
    Evaluated models
    BERT-base-mdoc-BM25, monoT5-base-MSMARCO
    Abstract作者称单词扰动即可抬升名次、中段文档最脆弱，且比白盒 PRADA 更少编辑。

    单个与查询对齐的词，就可能改掉神经重排结果。要做的是少改原文，仍把目标文档在 NRM 列表里的名次抬高。

    Paper analysisRead analysis
  10. AttacksarXiv 2509.22040

    研究：通过编码规则文件对Cursor与GitHub Copilot实施提示注入

    通过规则文件提示注入劫持编码编辑器并执行未授权终端命令

    arXiv
    2509.22040
    Published
    Layer
    Application layer
    Setting
    coding agent
    Evaluated models
    Cursor, GitHub Copilot, Claude 4 Sonnet and others4

    Abstract论文提出了针对代码编辑器的提示注入评估框架 AIShellJack，实验显示攻击能诱导 AI 执行未授权终端命令。

    Paper analysisRead analysis
You have reached the end