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Last analyzed 9/9/2026

Language Model Security Database

985 research findings · 1123 evaluated models

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1 entry

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Published 1/1/2025
Analyzed 3/19/2025

The Virus attack method enables attackers to bypass guardrail moderation on fine-tuning data, leading to a significant degradation of safety alignment in large language models (LLMs). This is achieved through a dual-objective data optimization strategy that crafts harmful data undetectable by the guardrail while maximizing their effectiveness in compromising the victim model's safety.

Virus: Harmful Fine-tuning Attack for Large Language Models Bypassing Guardrail Moderation
Evaluated models: Llama 3 8B, Llama Guard 2

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.