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Last analyzed 9/9/2026

Language Model Security Database

985 research findings · 1123 evaluated models

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21 entries

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Published 9/1/2024
Analyzed 12/29/2024

Large Language Models (LLMs) used in role-playing systems are vulnerable to character hallucination attacks, a form of jailbreak exploiting "query sparsity" and "role-query conflict". Query sparsity occurs when prompts fall outside the model's training data distribution, causing it to generate out-of-character responses. Role-query conflict arises when the prompt contradicts the established character persona, leading to inconsistent behavior. These vulnerabilities allow attackers to elicit…

RoleBreak: Character Hallucination as a Jailbreak Attack in Role-Playing Systems
Evaluated models: Claude 3 Haiku, GPT-3.5 Turbo, Llama 3 8B +1 more

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.