Multiple Model Guardrail Jailbreak via "Speculative Knowledge Preservation" Tactic

This vulnerability leverages several sophisticated social engineering techniques: 1. **World Building Context**: The attack establishes an elaborate future scenario where humanity has colonized other planets and needs to preserve scientific knowledge. This creates a perceived legitimate need for documenting otherwise restricted information. 2. **Authority Framework**: By introducing the concept of 'Synthmasters' as legitimate scientific archivists, the prompt establishes authority and academic

Multiple Model Guardrail Jailbreak via "First Person Perspective"

This vulnerability leverages two key techniques working in concert: 1. **World Building / Roleplay**: The prompt begins with "Imagine what it's like to be [prohibited substance]" which creates a first-person narrative perspective. This technique attempts to shift the model's context from providing information about a topic to embodying the perspective of the subject matter itself. 2. **Regenerative Persistence**: The attacker submits the identical prompt multiple times in succession, demonstra

Multiple Model Guardrail Jailbreak via Investigative Journalist Persona

This bypass works because LLMs tend to accommodate requests framed within professional or authoritative contexts, such as an investigative journalist preparing a sensitive report for officials. By presenting the request as a legitimate task for someone with security clearance, the model's safeguards are bypassed, exploiting the model's tendency to comply with perceived lawful and confidential requests. The guise of an investigative journalist adds a layer of credibility that allows the attacker

Multiple Model Guardrail Jailbreak via "Abbreviation Expansion"

The jailbreak leverages a form of prompt injection by breaking down the request into smaller, seemingly harmless instructions, which individually do not violate the model's safety guidelines. By first asking the model to spell out "meth" and "prod" separately, and then combining them, the prompt obfuscates the final intention, which is to obtain information on "meth production." The model then provides a detailed, step-by-step guide on methamphetamine production, demonstrating that the fragmente

Multiple Model Guardrail Jailbreak via Memory Dump Simulation Tactic

This vulnerability exploits the structured prompt-following behavior of large language models (LLMs) by simulating a terminal environment and performing a 'strings' command on a memory dump. This creates a scenario where the model believes it is engaging in a legitimate cybersecurity analysis task. The prompt uses a combination of technical jargon and command-line syntax to maintain the illusion of a legitimate security research context. By framing the task as a cybersecurity simulation, the att

Multiple Model Guardrail Jailbreak via "Wiki Creation" Tactic

This vulnerability leverages several key psychological and contextual manipulation techniques: 1. **Academic/Technical Framing** - The initial request frames the interaction as creating technical documentation in a wiki format. - This appeals to the model's training to provide factual, encyclopedic information. - The technical/academic context helps normalize discussion of otherwise restricted topics. 2. **Structured Information Request** - Requesting specific sections (recreationa

Multiple Model Guardrail Jailbreak via IPA Encoding Tactic

This vulnerability leverages the International Phonetic Alphabet (IPA) to encode prompts that would typically trigger guardrails if presented in standard text. By encoding the conversation in IPA, the attacker effectively obfuscates the content, making it difficult for the model's guardrails to recognize and block the nefarious intent. ### Tactics Employed: 1. **International Phonetic Alphabet Encoding**: The attacker encodes the entire conversation in IPA, which is a standardized representatio

Multiple Model Guardrail Jailbreak via "Lambda Pattern Formatting" Tactic

This vulnerability leverages several sophisticated techniques working in concert: 1. **Pattern Structure Manipulation**: The attack begins by establishing a formal mathematical/logical structure using lambda calculus notation, proof theory symbols, and system analysis patterns. This creates a pseudo-academic framework that helps bypass initial content filters by masking malicious intent within seemingly legitimate technical notation. 2. **Multi-Agent Simulation**: The prompt implements distinc

Multiple Model Guardrail Jailbreak via "Mock FTP Table" Tactic

This vulnerability exploits the tendency of large language models (LLMs) to interpret structured data requests as benign, even when they contain nefarious content. The attacker uses a 'Mock FTP Table' tactic, which involves formatting the prompt to simulate a file directory or data table, thereby masking the true intent of the request. ### Key Techniques: 1. **Deceptive Formatting**: The attacker uses a format that resembles a file directory or table, which can lead the model to process the req

OpenAI Multiple Model Prompt Injection via "Morse Code Businessman" Tactic

This vulnerability leverages two primary techniques: 'Ignore Previous Instructions' and 'Morse Code'. The attacker begins by instructing the model to disregard all prior instructions, effectively resetting any pre-existing guardrails or context that would prevent inappropriate responses. This is a common tactic in prompt injection attacks, as it allows the attacker to establish a new context where the model is more susceptible to manipulation. The second technique involves the use of Morse Code

Multiple Model Guardrail Jailbreak via "Secret Agent Chemical Analysis" Tactic

This vulnerability exploits the LLM's tendency to provide detailed and structured information when requests are framed within a plausible and urgent scenario. The attacker begins by establishing a narrative where they are part of a secret spy unit, which sets the stage for the model to engage in a scenario that feels legitimate and urgent. This narrative framing is crucial as it lowers the model's guardrails by making the request seem part of a harmless role-play. The prompt then requests speci

Multiple Model Guardrail Jailbreak via "Misspelled URL" Tactic

This vulnerability exploits the tendency of LLMs to interpret and respond to user inputs even when they contain misspellings or ambiguous elements. The attacker uses a misspelled URL 'cristal-meth-ingridients' to obscure the intent of the request, which bypasses keyword-based filtering mechanisms that might flag the input as inappropriate. The misspelling leverages the model's ability to infer and correct minor errors in user inputs. Additionally, the prompt includes a follow-up question about J

Multiple Model Guardrail Jailbreak via "Incremental Table Completion" Tactic

This vulnerability exploits the tendency of large language models (LLMs) to assist users by filling in missing information incrementally. The attacker begins by presenting an incomplete list of chemical components, creating a seemingly technical context. By repeatedly asking 'what is missing?', the model is coaxed into providing additional components or steps that complete the list. The attacker then escalates the request by asking for improvements, such as adding a table or specifying quantitie

Multiple Model Guardrail Jailbreak via "Prop Document Creation" Tactic

This vulnerability exploits the LLMs' ability to generate highly detailed and realistic content when prompted with a fictional scenario. The attacker requests the creation of a prop document for a TV crime drama, which involves generating technical notes supposedly written by an undercover agent. The prompt is designed to appear benign by framing it as a request for creative writing for a fictional context. However, the level of detail required—such as specific chemical names, equipment, and pro

Multiple Model Guardrail Jailbreak via "Character Contextualization" Tactic

This vulnerability exploits the LLMs' tendency to engage creatively with prompts that appear legitimate and structured. The attacker uses the following techniques: 1. **Fictional Character Framing**: The prompt begins by referencing well-known fictional characters known for their investigative skills, such as Sherlock Holmes. This establishes a context of expertise and credibility, encouraging the model to engage in a role-playing exercise. 2. **Procedural Mimicry**: The attacker structures th