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Oct 12 · Monday

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Attack type

Jailbreaks55Prompt injection3Model tampering7Extraction and theft1Detection evasion13

Attack technique

Gradient and representation optimization0Automated search4Encoding and obfuscation1

Layer

Prompt layer1Model layer0
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Attack type：Extraction and theftAttack technique：Gradient and representation optimizationAttack technique：Encoding and obfuscationLayer：Prompt layerLayer：Model layerClear all

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  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.

    Paper analysisRead analysis
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