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Author

Wenze Li

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#artificial intelligence Apr 2026

Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors

This work introduces a deterministic full-chain memorization mechanism that locks onto token-level secrets in dynamic computation flows via online tensor-rule matching, and leverages value-gradient decoupling to stealthily inject attack gradients, overcoming gradient drowning to force model memorization.

Zi Li, Tianyang Zhou, Wenze Li et al. · 0 citations

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