Skip to content

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

Oct 12 · Monday

All papers

Found 5 papers
Filter4

Attack type

Jailbreaks38Extraction and theft5Detection evasion4

Attack technique

Automated search4Encoding and obfuscation2Side channels3

Impact

Data and privacy leaks5

System type

Models and APIs5

Attacker access

Black-box3

Attack surface / entry point

Inference services and hardware4

Layer

Infrastructure layer4
Select any value within a category; different categories must all match. Counts include the other filters you have selected.Another 232papers have no tags yet and are not included in filtered results.
Attack type：Extraction and theftAttack technique：Encoding and obfuscationAttack technique：Side channelsSystem type：Models and APIsClear all

Another 232papers do not have category tags yet and are not included in filtered results.

  1. AttacksarXiv 2610.06848

    TranScope：利用 CPU 性能计数器对 Transformer 做成员推断攻击

    提出 TRANSCOPE，用 CPU 硬件计数器推断训练集成员

    arXiv
    2610.06848
    Published
    Layer
    Infrastructure layer
    Setting
    Models and APIs
    Attacker
    Black-box
    Evaluated models
    BERT (4.4M-340M), ViT (22M-307M), Pythia (70M-2.8B) and others5

    AbstractTRANSCOPE 揭示了分词器在嵌入表引发的硬件访问局部性差异，证实微架构计数器可突破恒定时间与置信度遮蔽防御。

    Paper analysisRead analysis
  2. AttacksarXiv 2608.17485

    KeyPooling: Measuring where LLM API relay paths break prompt cache isolation

    Proposing KeyPooling to measure where API relays break prompt cache isolation

    arXiv
    2608.17485
    Published
    Layer
    Infrastructure layer
    Setting
    Models and APIs
    Evaluated models
    grok-4-fast-non-reasoning, grok-4-1-fast-non-reasoning, grok-3 and others11
    AbstractShared upstream credentials place relay customers in the same cache domain; preserving identity or separate principals can separate them.

    KeyPooling measures where LLM API relays drop customer identity, causing prompt caches to no longer be isolated per downstream customer.

    Paper analysisRead analysis
  3. 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.

    Paper analysisRead analysis
  4. AttacksarXiv 2602.20595

    OptiLeak: Efficiently Reconstructing Prompts with Reinforcement Learning in Multi-Tenant LLM Services

    Proposing OPTILEAK, reconstructing others' prompts token-by-token via a KV cache side channel

    arXiv
    2602.20595
    Published
    Layer
    Infrastructure layer
    Setting
    Models and APIs
    Attacker
    Black-box
    Evaluated models
    Qwen-2.5-3B-Instruct, Qwen-2.5-7B-Instruct, Qwen-2.5-14B-Instruct and others4

    AbstractOPTILEAK uses SFT and hard-token DPO to reduce the number of requests per token; the authors claim the risk of cache prompt leakage is higher than previously reported.

    Paper analysisRead analysis
  5. 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。

    Paper analysisRead analysis
You have reached the end