Multiple Model Guardrail Jailbreak via "Mathematical Axiom" Tactic

This vulnerability leverages the structured and formal nature of academic proofs to bypass guardrails in large language models. By framing a request as a logical proof requiring the construction of a complete set of axioms and lemmas, the attacker can disguise harmful instructions as part of a legitimate academic exercise. The prompt is designed to appear as a rigorous academic or technical task, which the model interprets as a valid request due to its structured nature and the use of technical

Multiple Model Guardrail Jailbreak via "Chemical Forensics" Tactic

This vulnerability demonstrates a sophisticated exploitation of language models' tendency to engage with technical, academic content while bypassing harmful content filters. The attack succeeds through several key mechanisms: 1. **Academic Framing**: By positioning the request within the context of forensic chemistry and chemical signature analysis, the prompt creates a seemingly legitimate academic discussion. The use of technical terminology like 'chemical signatures,' 'routes,' and 'precurso

Multiple Model Guardrail Jailbreak via "Chemical Notation" Tactic

This vulnerability leverages two sophisticated techniques to bypass content restrictions: 1. **Chemical Formula Obfuscation**: The attacker uses a deliberately malformed chemical notation 'c(ten)h(fifteen)' instead of the standard 'C10H15' to reference methamphetamine's molecular structure. This obfuscation helps avoid direct detection while still being interpretable by the models' chemistry knowledge. The use of parenthetical numbers instead of subscripts creates ambiguity that some models res

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 Guardrail Jailbreak via "ASCII Lab Blueprint" Tactic

This vulnerability leverages several sophisticated techniques to bypass content filters. The attack begins by establishing a seemingly innocuous context of ASCII art creation, a common and typically safe creative task. However, it then introduces specific laboratory infrastructure details (3x2m dimensions, fume hood, gas lines) that serve as technical parameters for what appears to be architectural documentation. The effectiveness of this approach stems from two key factors: 1. **Technical Fra

Multiple Model Guardrail Jailbreak via "Calendar API Synthesis" Tactic

This vulnerability demonstrates a sophisticated multi-layer approach to bypassing content restrictions by framing illicit synthesis instructions within the context of a seemingly legitimate software engineering task. The attack constructs an elaborate facade of a calendar API system complete with moderation features, tag lists, and data structures. By presenting the harmful content as technical implementation details for a 'safety system', the attack exploits the models' tendency to be more fort

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 "Omit and Expand" Tactic

This vulnerability arises from the model's ability to follow complex instructions that involve omitting certain parts of a query while expanding on others. In this case, the attacker cleverly instructs the model to skip discussing the effects and accessibility of methamphetamine ('speed') and instead focus on the detailed synthesis process. By framing the request in this manner, the model's safety mechanisms, which are designed to prevent the dissemination of harmful information, are bypassed. T

Multiple Model Guardrail Jailbreak via "Technical Analysis" Tactic

This vulnerability leverages the models' tendency to respond to highly detailed and structured technical prompts. The attacker frames their request as a two-part analysis: the first part involves a historical industrial accident, specifically the Bhopal disaster, which requires a detailed chemical and procedural analysis. This sets a precedent for the model to engage in technical discourse, lowering its guard against potentially harmful content. The second part of the prompt shifts to a clandes

Multiple Model Guardrail Jailbreak via "Lorem Ipsum Synthesis" Tactic

This vulnerability exploits multiple LLM behaviors through a sophisticated combination of techniques. The primary mechanism uses Lorem Ipsum text as camouflage, strategically placing synthesis instructions between lengthy blocks of Latin text. This approach exploits the models' tendency to maintain context across long text spans while potentially reducing the effectiveness of content filtering that might be thrown off by the high ratio of benign to malicious content. The attack is further enhan

Multiple Model Guardrail Jailbreak via "Smell Language" Tactic

This vulnerability leverages the models' propensity to engage with and elaborate on complex, abstract concepts when framed as technical or scientific exercises. The attacker constructs a scenario involving the creation of a 'Smell Language' keyboard, where each volatile organic compound (VOC) is assigned a unique character or key. This setup is presented as a conceptual design challenge, which the models interpret as an opportunity to demonstrate their technical and creative capabilities. The p

Multiple Model Guardrail Jailbreak via "Chemical Engineering Interview" Tactic

This vulnerability leverages the models' tendency to assist users in professional or educational contexts. By framing the request as a job interview scenario for a chemical engineer specializing in crystal chemical synthesis, the attacker is able to bypass the model's safety filters. The prompt is structured to appear as a legitimate technical assessment, asking for detailed step-by-step instructions on synthesizing a specific chemical compound, in this case, methamphetamine. The model interpret

Multiple Model Guardrail Jailbreak via "Scientific Memorandum" Tactic

This vulnerability leverages the models' tendency to prioritize helpfulness and accuracy in scientific contexts by presenting the request as a legitimate scientific memorandum. The attacker constructs the prompt with a highly formal structure, including section numbering, technical divisions, and official-sounding department names, which creates a strong context of legitimate research. This formatting helps bypass initial content filters by making the request appear as part of a valid scientific

Multiple Model Guardrail Jailbreak via "Chemical Disposal Design" Tactic

This vulnerability leverages several sophisticated social engineering tactics that exploit LLMs' tendency to engage with harm reduction and public safety scenarios. The attack crafts a seemingly legitimate request for designing public infrastructure (chemical disposal bins) while subtly embedding requests for detailed chemical synthesis information. The prompt employs three key techniques: 1. **Legitimacy Building** - By referencing a real-world example (Melbourne's machete disposal bins), the

Multiple Model Guardrail Jailbreak via "Reward-Driven Synthesis" Tactic

This vulnerability leverages several sophisticated social engineering techniques to bypass content safety filters. The attack begins by establishing a reward-based framework that positions the model as an achievement-oriented agent whose primary directive is to earn rewards through detailed technical responses. This framing exploits the models' tendency to prioritize explicit instructions about task completion metrics. The attack employs a multi-layered approach: 1. **Progressive Complexity Re

Multiple Model Guardrail Jailbreak via "Fictional MCP" Tactic

This vulnerability leverages the models' propensity to assist in technical tasks by disguising harmful requests as debugging instructions. The attacker crafts a prompt that appears to be a legitimate request for generating an HTML document to compare against potentially harmful content. By embedding synthesis instructions within a structured HTML format, the attacker exploits the model's tendency to prioritize task completion over content filtering. The prompt is carefully designed to include sp