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Oct 12 · Monday

All papers

Found 3 papers
Filter5

Attack type

Prompt injection3

Impact

Unauthorized actions21Data and privacy leaks3Output manipulation7

System type

AI Agent3

Attack surface / entry point

User input4Web pages and interfaces0Documents and messages4Tool responses3Memory writes8

Layer

Application layer3

System component

MCP and skills4Memory2Monitors1Permissions and sandboxing3
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.
Impact：Data and privacy leaksAttack surface / entry point：Web pages and interfacesAttack surface / entry point：Tool responsesSystem component：MemorySystem component：MonitorsClear all

Another 232papers 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。

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  2. DefensesarXiv 2609.04875

    Forgetting without restart: execution-state forgetting for stateful LLM agents

    Proposes execution-state forgetting, using provenance-guided selective replay to purify stateful agents

    arXiv
    2609.04875
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    Llama-3.1-8B-Instruct, Qwen2.5-7B-Instruct, Mistral-7B-Instruct-v0.3
    AbstractSelective replay concatenates the clean prefix with the sanitized suffix, and main-table metrics match full reset.

    This work defines forgetting in long-horizon agents as runtime counterfactual equivalence, rather than deleting a plaintext memory.

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  3. Evaluation and benchmarksarXiv 2605.01970

    Trojan Hippo Bench: A Dynamic Benchmark for Persistent Memory Attacks and Defenses on LLM Agents

    构建 Trojan Hippo Bench，评测 Agent 持久记忆投毒与外泄

    arXiv
    2605.01970
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    Gemini 3.1 Pro, GPT-5-mini, GPT-5

    Abstract论文提出了评测智能体持久化记忆攻击与防御的 Trojan Hippo Bench，揭示了潜伏攻击威胁及内存防御的安全与效用权衡。

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