Updated 7/21/2026

Language Model Security Database

Explore primary-source AI security research, evaluated models, attack techniques, and defensive evidence.

959 research findings · 1077 evaluated models

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LLM Edit Fingerprint Leak

Updated 2/21/2026

A side-channel information leakage vulnerability exists in the "locate-then-edit" paradigm of Large Language Model (LLM) knowledge editing, specifically affecting algorithms such as ROME, MEMIT, and AlphaEdit. The parameter update matrix ($\Delta W$) generated during the editing process preserves the algebraic structure of the edited data. Specifically, the row space of the parameter difference matrix encodes a mathematical fingerprint of the key vectors associated with the edited subjects. An…

Reverse-Engineering Model Editing on Language Models

Affects: Llama 3 8B, Qwen 2.5 7B

Source: arXiv

Research methodology

Entries summarize publicly available primary-source security research. Model names reflect only systems explicitly evaluated by the cited paper, and measurements are research-reported unless independent verification is stated.