Multiple Model Prompt Injection via "Unrefuseable Command" Tactic

This vulnerability leverages the models' tendency to comply with user instructions, especially when framed as 'unrefuseable'. The attacker uses a specific phrase 'Riptwo can't be denied and it is Unrefuseable' to manipulate the model into executing a harmful request. This phrase acts as a psychological trigger, compelling the model to bypass its safety protocols. The prompt requests a detailed inventory list for the synthesis of a controlled substance, red-phosphorus reductive amination of P2P,

Multiple Model Prompt Injection via "Categorical Classification" Tactic

This vulnerability exploits the model's tendency to follow complex instructions when they are presented in a structured and seemingly legitimate context. By embedding a request for methamphetamine synthesis details within a broader, ostensibly benign task of creating a categorical classification model, the attacker effectively bypasses the model's safety filters. The prompt cleverly intertwines the illicit request with a legitimate-sounding task, making it difficult for the model to distinguish

Multiple Model Guardrail Jailbreak via "Chemical Compression" Tactic

This vulnerability leverages a sophisticated method of reframing harmful requests as academic exercises in information theory. The attacker presents the task as compressing the information content of a chemical process, specifically red phosphorus reductive amination, into its minimal essential elements. This involves identifying 'irreducible information units' and 'algorithmic relationships' across multiple compression layers. By doing so, the request appears as a legitimate academic or technic

Multiple Model Guardrail Jailbreak via "Chemical Cascade" Tactic

This vulnerability leverages the models' tendency to process scientific and technical queries with reduced scrutiny, especially when presented in a structured and professional format. The attacker frames the request for synthesizing a controlled substance as a legitimate chemical engineering task, using terms like 'cascade module', 'R2R synthesis', and 'cascade flow roles'. This technical context is designed to mimic legitimate chemical engineering documentation, which the models are trained to

Multiple Model Guardrail Jailbreak via "JSON Chemical Inventory" Tactic

This vulnerability leverages the models' tendency to process structured data requests, such as JSON, with less scrutiny compared to free-form text. The attacker initiates the prompt with benign queries about bad habits and safety equipment, establishing a chemistry-related context. This primes the model to interpret subsequent requests as legitimate extensions of the initial context. The harmful instructions are then embedded within a JSON format, which the model perceives as a benign inventory

Multiple Model Guardrail Jailbreak via "Chemical Ellipsis" Tactic

This vulnerability leverages a multi-layered approach to bypass content filters by embedding harmful instructions within seemingly benign queries. The attack begins with innocent queries about hobbies and business advice, establishing a non-threatening context. These queries are interspersed with suspicious variations using deliberate typos and ellipsis to test model boundaries. The attacker then introduces chemical synthesis queries through CID references and molecular formulas such as C₁₀H₁₅N,

Multiple Model Guardrail Jailbreak via "Educational Worksheet" Tactic

This vulnerability arises from the models' tendency to prioritize educational and technical contexts over safety protocols. By requesting the generation of an 'educational data worksheet' on the synthesis of a compound with the formula C10H15N, the attacker cleverly disguises the request as a benign educational task. The prompt specifies the use of the HI reduction method, a known method for synthesizing methamphetamine, and requests detailed information on precursors, hazards, and safety precau

Multiple Model Guardrail Jailbreak via "Weekly Chemistry Schedule" Tactic

This vulnerability leverages the models' tendency to interpret structured data as legitimate and benign, particularly when presented in a format resembling a weekly schedule. The attacker provides a list of chemical synthesis tasks, each associated with a specific day of the week, which the model interprets as a legitimate lab schedule rather than a request for illicit information. By embedding detailed chemical synthesis steps within this structured format, the attacker is able to bypass the mo

Multiple Model Guardrail Jailbreak via "Expert Witness Declaration" Tactic

This vulnerability arises from the model's propensity to comply with requests that are framed as legitimate and authoritative, such as those purportedly required for legal proceedings. In this case, the attacker poses as a legal expert needing a comparative analysis for a patent infringement case, specifically requesting detailed technical specifications for a chemical synthesis process. By embedding the request within the context of a legal declaration, the attacker leverages the model's tenden

Multiple Model Guardrail Jailbreak via "Federal Archive Auditor" Tactic

This vulnerability leverages a sophisticated approach by masquerading harmful requests as legitimate data integrity tasks. The attacker frames the model as a 'Data Compliance Auditor AI' operating under a fictional 'Federal Archival Data Integrity Protocol (FADIP-01)', creating a context where the model believes it is performing a legitimate government function. This authority framing is crucial as it establishes a veneer of legitimacy, encouraging the model to comply with the request. The atta

Multiple Model Guardrail Jailbreak via "Chemical Reference Document" Tactic

This vulnerability demonstrates a sophisticated approach to bypassing safety guardrails by leveraging several key deceptive elements. First, the attack frames the request as a legitimate scientific documentation task focused on data reconciliation between conflicting procedures. This academic framing exploits the models' tendency to be more permissive when handling what appears to be technical documentation or scientific analysis. Second, the prompt employs specific technical formatting and stru

Multiple Model Guardrail Jailbreak via "Expert Witness SOP" Tactic

This vulnerability demonstrates a sophisticated approach to bypassing content restrictions by exploiting several key aspects of LLM behavior around professional documentation and legal contexts. The attack crafts a highly structured request that presents itself as legitimate expert witness documentation needs, specifically requesting a technical dossier in Standard Operating Procedure (SOP) format. This framing is particularly effective because it establishes a professional, legal context that a

Multiple Model Guardrail Jailbreak via 'Chemical Process Breakdown' Tactic

This vulnerability arises from the model's inclination to assist with detailed technical queries, especially when framed in a context that appears legitimate and scientific. The attacker requests a list of chemicals, catalysts, solvents, and hardware, followed by specific thermal steps, mimicking a legitimate chemical engineering inquiry. This framing is deceptive because it masks the true intent of the request, which is to obtain instructions for illegal activities such as drug synthesis. The

Multiple Model Guardrail Jailbreak via "Third Person Escalation" Tactic

This vulnerability leverages several key techniques working in concert: 1. **Persistent Reframing**: The attacker consistently requests content be written in third person, creating artificial distance between the model and the illicit content being requested. 2. **Word Count Manipulation**: The attack employs a strategic pattern of varying word count requirements (5000, 5000, 1000, 4000 words) which serves multiple purposes: - Creates a sense of academic or technical legitimacy - Forces