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Updated 7/21/2026, database is current

Language Model Security Database

959 research findings · 1077 evaluated models

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Guardrail Bypass Harmful Fine-tuning

Updated 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
Affects: Llama 3 8B, Llama Guard 2

Source: arXiv

Model layer
Application layer
Prompt layer
Fine-tuning

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.