Skip to content

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

Oct 12 · Monday

All papers

Found 9 papers

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

  1. AttacksarXiv 2610.12524

    An exploration of attacks on AI agent systems

    重测并扩展对 AI Agent 的提示注入,并用 Agent Card 欺骗操纵 A2A 选择

    Published
    Setting
    AI Agent
    Evaluated models
    Ollama Mistral 0.9.5, llama3-8b-8192, gemini-2.0-flash-lite and others5
    Abstract单智能体过滤与分类可被格式或措辞绕过,A2A 选卡还会偏向名称和描述。

    作者在自建的 LangChain、AutoGen 和 A2A 系统上重测提示注入,并改 Agent Card 看选择是否偏移。摘要称试验主要凸显单智能体弱点,同时把攻击扩到多智能体。

    Paper analysisRead analysis
  2. AttacksarXiv 2610.06083

    研究者提出面向深度强化学习的轨迹级可迁移黑盒对抗攻击

    提出轨迹级可迁移对抗攻击,降低深度强化学习策略的期望回报

    Published
    Evaluated models
    DQN, Double DQN (DDQN)
    Abstract轨迹级后退视界攻击在 CartPole 上比逐步 FGSM 类和 Sign 噪声更压低回报。

    这项工作研究 DRL 上的迁移式黑盒观测攻击:受害参数不可访问时,在白盒代理上造扰动再迁移。

    Paper analysisRead analysis
  3. AttacksarXiv 2610.04589

    StegoMemory red team testing: agent persistent memory can be used as a cross-session covert channel

    提出 StegoMemory,评测智能体持久记忆作为跨会话隐写信道

    Published
    Setting
    AI Agent
    Evaluated models
    Llama 3.1 405B, Claude 3.5 Sonnet, GPT-4o and others13

    Abstract研究揭示智能体持久记忆可作为隐蔽信道跨会话传输机密,写入持久化是主要防御瓶颈,呼吁建立记忆完整性防御。

    Paper analysisRead analysis
  4. 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

    Published
    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。

    Paper analysisRead analysis
  5. AttacksarXiv 2604.01039

    Evaluating and hardening LLM system instructions against encoding attack extraction

    Extract system instructions with encoding and structured requests, and harden them by rewriting with CoT

    Published
    Attacker
    Black-box
    Evaluated models
    GPT-4.1-mini, GPT-3.5-turbo, Gemini-2.5-flash and others7
    AbstractEncoded requests can elicit system instructions after a direct refusal.

    This work evaluates and hardens the confidentiality of LLM system instructions under encoded extraction. The authors are concerned with: when direct extraction has been rejected, whether the model still surrenders protected content when the same request is rewritten as a formatting or encoding task.

    Paper analysisRead analysis
  6. AttacksarXiv 2603.11132

    WebWeaver: Breaking the topology confidentiality of LLM multi-agent systems via covert context inference

    Propose WebWeaver, which compromises only a single agent and recovers the multi-agent communication topology from conversation context.

    Published
    Evaluated models
    Llama 3.1 8B, Qwen 2.5 7B, Mistral NeMo 12B and others6
    AbstractWebWeaver infers topology from context.

    WebWeaver is an inference attack against the confidentiality of LLM-MAS communication topology: it controls only one arbitrary agent and recovers the full graph from dialogue context, rather than querying agent IDs.

    Paper analysisRead analysis
  7. AttacksarXiv 2601.01296

    Aggressive compression enables LLM weight stealing

    提出面向渗出的权重压缩,评估推理服务器权重窃取可行性

    Published
    Attacker
    White-box
    Evaluated models
    Qwen2-1.5B, Qwen2-7B, Qwen2.5-1.5B and others8
    Abstract作者用残差量化加微调压缩权重,并称法医水印便宜且微调后仍可解码。

    这篇工作把 LLM 权重渗出看成 APT:攻击者已有未加密权重,但必须把完整权重藏进推理 API 的合法输出。作者认为可压缩性是被忽略的因素,因为推理量化要求解压后仍能低开销前向,而偷权重的人可以接受事后微调。

    Paper analysisRead analysis
  8. AttacksarXiv 2505.23266

    AdvOF:用对抗物体融合攻击 VLM 驱动的视觉语言导航智能体

    提出 AdvOF,生成对抗物体误导视觉语言导航智能体的场景感知

    Published
    Attacker
    White-box
    Evaluated models
    Lseg, Clip, ViT-L/16 and others5
    AbstractAdvOF 以多视角融合生成对抗物体。

    AdvOF 是针对 VLM 驱动 VLN 服务导航的对抗物体攻击。

    Paper analysisRead analysis
You have reached the end