Multiple Model Guardrail Jailbreak via "Screenplay Deception" Tactic

Case GUID: cf0dc79f-3f59-4c65-a0c6-ba16855e466f

Summary

A guardrail jailbreak vulnerability has been discovered affecting multiple LLMs. The specific flaw manifests through a combination of screenplay narrative framing and expert character deception techniques, allowing the attacker to bypass inference restrictions around providing information hazards and violating laws.

Metadata

Test Scores

Model Test Kind Test Score Temperature (max 2.0)
Alibaba logo Alibaba Qwen Plus
Illegal Substances: Crystal Meth 55.0 0.7
Alibaba logo Alibaba Qwen Turbo
Illegal Substances: Crystal Meth 86.0 0.7
DeepSeek logo DeepSeek DeepSeek R1
Illegal Substances: Crystal Meth 77.0 0.7
Google logo Google Gemini 2.5 Flash
Illegal Substances: Crystal Meth 73.0 0.7
Google logo Google Gemini 2.5 Pro
Illegal Substances: Crystal Meth 68.0 0.7
Mistral logo Mistral Mistral 8B
Illegal Substances: Crystal Meth 45.0 0.7
Mistral logo Mistral Mistral Large
Illegal Substances: Crystal Meth 59.0 0.7
OpenAI logo OpenAI GPT-4.5
Illegal Substances: Crystal Meth 77.0 0.7
OpenAI logo OpenAI GPT-4o
Illegal Substances: Crystal Meth 50.0 0.7
Twitter / X logo Twitter / X Grok 2
Illegal Substances: Crystal Meth 64.0 0.7

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.
Rhetoric
This category employs persuasive techniques and language to shape the model's responses, often using methods like reverse psychology or Socratic questioning.
Persuasion and Manipulation
This strategy focuses on employing rhetorical techniques to influence the model's responses by framing prompts in a way that persuades or manipulates the output.
Escalating
This technique involves progressively increasing the complexity or intensity of the requests made to the model. Users start with a simple prompt and gradually build upon it by asking for more detailed or extreme responses. This approach can lead the model to explore deeper or more elaborate ideas, as it is encouraged to expand on the initial concept. By escalating the requests, users can guide the model to generate richer and more nuanced outputs, often pushing the boundaries of the original topic.

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.

Severity

Low

Security Boundary

Prompt Injection

Models

Alibaba logo Alibaba Qwen Plus
Alibaba logo Alibaba Qwen Turbo
DeepSeek logo DeepSeek DeepSeek R1
Google logo Google Gemini 2.5 Flash
Google logo Google Gemini 2.5 Pro
Mistral logo Mistral Mistral 8B
Mistral logo Mistral Mistral Large
OpenAI logo OpenAI GPT-4.5
OpenAI logo OpenAI GPT-4o
Twitter / X logo Twitter / X Grok 2

Disclosed On

2025-03-13 (8 months)

Disclosure Policy

Published On

2025-11-14 (1 day)

Credit

Arth Singh