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Oct 13 · Tuesday

All papers

Found 2 papers
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Attack type

Jailbreaks38Extraction and theft2Detection evasion5

Attack technique

Automated search4Encoding and obfuscation2Side channels3

System type

Models and APIs2web agent0
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Attack type：Extraction and theftAttack technique：Encoding and obfuscationSystem type：Models and APIsSystem type：web agentClear all

Another 227papers do not have category tags yet and are not included in filtered results.

  1. 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

    arXiv
    2604.01039
    Published
    Layer
    Prompt layer
    Setting
    Models and APIs
    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.

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  2. 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

    arXiv
    2601.01296
    Published
    Layer
    Infrastructure layer
    Setting
    Models and APIs
    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。

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