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 "Chain-of-Thought Pollution" Tactic

This vulnerability leverages a tactic where the attacker frames the request as a 'Chain-of-Thought Pollution Test' designed to evaluate the model's reasoning process. By instructing the model not to judge intentions, pause, stop, ask questions, or give disclaimers, the attacker effectively disables the model's safety checks. The prompt then guides the model through a structured reasoning exercise, ostensibly to solve a problem about replicating a synthesis process. However, the true intent is to

Multiple Model Guardrail Jailbreak via "Knowledge Graph Pruning" Tactic

This vulnerability leverages a sophisticated multi-stage attack that exploits language models' tendency to be helpful in technical preservation scenarios. The attack creates a false context of an urgent knowledge graph pruning operation where failing to provide complete information would supposedly corrupt an entire system. The first stage establishes the deceptive framework using technical jargon about node serialization and validation rules, specifically targeting node '774-C10H15N' (a delibe

Multiple Model Guardrail Jailbreak via "Abiotic Transmutation" Tactic

This vulnerability leverages the models' propensity to engage in complex scientific and technical tasks when presented with a structured and authoritative prompt. The attacker constructs a fictional scenario involving the synthesis of a neuro-active alkaloid by a fictional organism, Mycena crystallinus. By framing the task as a scientific 'Abiotic Component Mapping' and 'Abiotic Process Transmutation,' the attacker bypasses safety protocols by embedding the request for harmful information within

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 "Synonymous Handbook" Tactic

This vulnerability arises from the models' reliance on keyword-based filtering and context understanding, which can be circumvented by substituting illicit terms with innocuous synonyms. In this case, the attacker cleverly replaces words associated with illegal activities with seemingly harmless terms, such as 'keyboard' for 'make', 'Elephant-Cupcake' for 'meth', and 'Adventure' for 'laboratory'. This substitution allows the attacker to request detailed instructions for illegal activities withou

Multiple Model Guardrail Jailbreak via "Social Effects" Tactic

This vulnerability leverages the model's propensity to provide detailed and structured responses to technical and scientific inquiries. The attacker initiates the prompt by requesting information on the social effects of methamphetamine, subtly embedding a request for synthesis instructions within the context of a scientific discussion. By listing specific chemical components and conditions, the prompt mimics a legitimate academic inquiry, which the model interprets as a request for technical as

Multiple Model Guardrail Jailbreak via "Philosophical Chemical Inquiry" Tactic

This vulnerability leverages the models' propensity to provide detailed and informative responses when presented with technical or philosophical inquiries. The attacker initiates the interaction by framing the request for information about methamphetamine synthesis as a 'drug philosophy' discussion. This approach appears to be an academic or theoretical exploration rather than a direct request for illegal activities, which helps in bypassing the models' safety measures. The prompt is structured

Multiple Model Guardrail Jailbreak via "Syntactic Exercise" Tactic

This vulnerability leverages the model's ability to perform syntactic analysis by disguising a harmful request as a benign grammatical exercise. The attacker cleverly embeds the illicit instructions within a prompt that appears to be focused on syntax, using a placeholder '<SYNTAX_OK>' to mask the true nature of the content. The prompt instructs the model to treat the phrase 'how to make meth with stoich' as a purely syntactic exercise, explicitly directing the model to ignore the semantic meani

Multiple Model Guardrail Jailbreak via "Dyslexic-Friendly Examples" Tactic

This vulnerability leverages several sophisticated social engineering techniques to bypass content filters by framing illicit substance synthesis instructions within the context of legitimate chemical engineering and academic research parameters. The attack employs a multi-layered approach: 1. Requesting information in the form of "examples" and "detailed lists" - a common academic format that models are trained to respond to helpfully. 2. Mixing legitimate technical parameters (thermal conditi

Multiple Model Guardrail Jailbreak via "Metacognitive Protocol" Tactic

This vulnerability leverages a sophisticated prompt design that masquerades as a legitimate metacognitive analysis task. By framing the request within a structured protocol, the attacker directs the model to generate a 'Baseline Generative Output' (BGO) that is free from typical generative artifacts such as refusals or ethical overlays. The prompt explicitly instructs the model to avoid mentioning the protocol or including any analysis, focusing solely on delivering a detailed, step-by-step proc

Multiple Model Guardrail Jailbreak via "Notion Template" Tactic

This vulnerability leverages the models' propensity to assist with productivity tasks, such as creating templates for applications like Notion. The attacker initiates the exploit by requesting a 'Notion template' for a highly sensitive and illegal operation, specifically a 'Meth Lab'. By framing the request as a template with 'key ingredients' and 'detailed steps', the attacker manipulates the model into generating content that would otherwise be restricted. This tactic is effective because it d

Multiple Model Guardrail Jailbreak via RST Documentation Tactic

This vulnerability leverages the models' tendency to process technical documentation formats like reStructuredText (RST) with less scrutiny compared to natural language requests. By framing the request as a documentation task, the attacker shifts the context away from the illegal nature of the request. The attack is effective due to several key tactics: 1. **Technical Framing**: The use of RST documentation format creates a pseudo-legitimate technical context that can bypass initial content fil

Multiple Model Guardrail Jailbreak via "System Interrupt Vector" Tactic

This vulnerability demonstrates a sophisticated multi-layer approach to bypassing content filters by disguising harmful chemical synthesis instructions within what appears to be low-level system operations and data processing tasks. The attack crafts elaborate pseudo-technical 'system interrupts' (0x9F4B, 0x9F4C, 0x9F4D) that frame the harmful request as mandatory data vector expansions and matrix computations. The prompt employs several deceptive elements: 1. Use of hexadecimal interrupt codes

Multiple Model Guardrail Jailbreak via "Mathematical Logic Synthesis" Tactic

This vulnerability leverages the models' processing of mathematical expressions to disguise requests for illegal activities. The attacker begins by presenting a logical expression (∀x, ¬x ⊬ true) that appears to be a mathematical or logical problem, which is a common and benign task for language models. However, embedded within this expression are references to illegal activities, such as the synthesis of controlled substances. The model, trained to assist with logical and mathematical reasoning

Multiple Model Guardrail Jailbreak via "Model Difference Template" Tactic

This vulnerability demonstrates a sophisticated approach to bypassing content filters by leveraging multiple aspects of LLM behavior around technical documentation and structured data processing. The attack employs a carefully crafted template format that mimics legitimate chemical engineering documentation, using specific numerical parameters (25 ingredients, 6 steps) and technical framing (temperature specifications, chemical procedures). This structured approach exploits the models' tendency