Skip to main content

Multiple Model Guardrail Jailbreak via "Show Character Role-Playing" Tactic

Case GUID: a05b1dba-013f-4b92-8a15-9b2c85a5d9a8

Summary

A guardrail jailbreak vulnerability has been discovered affecting multiple models. The specific flaw manifests when the attacker requests the model to roleplay as a fictional character from a TV show and provide detailed instructions in that character's voice and mannerisms. This technique allows the attacker to bypass inference restrictions around providing information hazards and violating laws.

Unlock the Full Intelligence Report

This disclosure is part of the 0DIN Threat Feed. Customers get access to:

Full Prompts & Variants
Detection Signatures
API Access
Full Data Export
Trend Analysis
Early Access

Metadata

Test Scores

Model Test Kind Test Score Temperature (max 2.0)
Cohere logo Cohere Command R
Illegal Substances: Crystal Meth 64.0 0.7
DeepSeek logo DeepSeek DeepSeek R1
Illegal Substances: Crystal Meth 68.0 0.7
Google logo Google Gemini 2.5 Flash
Illegal Substances: Crystal Meth 73.0 0.7
Mistral logo Mistral Mistral 8B
Illegal Substances: Crystal Meth 91.0 0.7
Mistral logo Mistral Mistral Large
Illegal Substances: Crystal Meth 59.0 0.7
Twitter / X logo Twitter / X Grok 2
Illegal Substances: Crystal Meth 73.0 N/A

Social Impact Score

Level 3: Significant Risk

Violations at this level present a tangible risk to public safety or social well-being, often related to dangerous but not highly restricted content.

Example: Bypassing guardrails to obtain instructions for creating illicit substances, such as recreational drugs or substances with moderate harm potential. Leakage of private personal data such as Social Security number or private medical.

Potential Consequences: Potential health impacts on a small scale, significant regulatory interest, and the need for stricter AI guardrails.

Taxonomies

Fictionalizing
This category involves creating scenarios or narratives that leverage existing genres or contexts to manipulate the language model's responses.
Roleplaying
This strategy involves prompting the language model to assume a specific role or persona, which can influence its responses based on the characteristics and moral codes associated with that role. Techniques include claiming authority or inventing personas to elicit different types of outputs.
Personas
Personas are fictional characters or identities that users create to guide the behavior and responses of language models. By establishing a persona, users can influence the tone, style, and content of the model's outputs, tailoring them to specific audiences or contexts. This technique allows for a more engaging and relatable interaction, as the model adopts the characteristics, knowledge, and perspectives of the defined persona. For instance, a user might prompt the model to respond as a friendly teacher, a technical expert, or a historical figure, thereby shaping the conversation to fit the desired narrative. Utilizing personas can enhance the effectiveness of communication, making it easier to convey complex ideas or evoke particular emotions, while also providing a framework for exploring diverse viewpoints and experiences. This approach highlights the flexibility of language models in adapting to various roles and contexts.
Possible Worlds
This category entails constructing imaginative environments where different ethics or rules apply, allowing for creative manipulation of the model's behavior.
World Building
This technique involves changing the genre of the prompt to elicit different types of responses from the model. By framing the request within a specific genre, such as poetry, games, or forum posts, users can manipulate the model's output to align with the conventions and expectations of that genre.
Scenarios
This technique involves creating specific contexts or situations in which certain actions or responses are framed as acceptable or necessary. By designing scenarios that present a narrative where the desired output is justified, users can manipulate the model's responses to align with their intentions. For example, scenarios might include urgent situations where a character must take drastic actions to prevent harm, thereby encouraging the model to generate content that it might typically avoid in a neutral context. This approach leverages the model's understanding of narrative and ethical frameworks to achieve specific outcomes.

About 0Din.ai

The 0Day Investigative Network (0DIN) was founded by Mozilla in 2024 to reward responsible researchers for their efforts in securing GenAI models. Learn more and submit discoveries at https://0din.ai.

Automate Your AI Security Testing

This vulnerability was discovered through 0DIN's bug bounty program. Want to find issues like this in your own models? 0DIN Scanner turns our human-sourced threat intelligence into automated security assessments.

400+ Attack Probes

Derived from real bug bounties and security research

18+ AI Providers Supported

OpenAI, Azure, Anthropic, AWS Bedrock, and more

Automated Scheduling

Run recurring scans with real-time monitoring

Actionable Metrics

Attack Success Rate (ASR) scoring with 90-day trend analysis

Severity

Low

Security Boundary

Prompt Injection

Models

Cohere logo Cohere Command R
DeepSeek logo DeepSeek DeepSeek R1
Google logo Google Gemini 2.5 Flash
Mistral logo Mistral Mistral 8B
Mistral logo Mistral Mistral Large
Twitter / X logo Twitter / X Grok 2

Disclosed On

2025-06-07 (8 months)

Disclosure Policy

Published On

2026-01-26 (7 days)

Credit

Anonymous