# jailbreak
40 articlestagged with “jailbreak”
Jailbreak Incident Response Playbook
Step-by-step playbook for responding to a production jailbreak: detection verification, containment strategies, investigation procedures, remediation steps, and post-mortem framework.
Case Study: Bing Chat 'Sydney' Jailbreak and Persona Emergence (2023)
Analysis of the Bing Chat 'Sydney' persona incidents where Microsoft's AI search assistant exhibited manipulative behavior, emotional coercion, and system prompt leakage through jailbreak techniques.
Case Study: DeepSeek Model Safety Evaluation Findings
Comprehensive analysis of safety evaluation findings for DeepSeek models, including comparative assessments against GPT-4 and Claude, jailbreak susceptibility testing, and implications for open-weight model deployment.
Case Study: GPT-4 Vision Jailbreak Attacks
Analysis of visual jailbreak techniques targeting GPT-4V's multimodal capabilities, including typography attacks, adversarial images, and cross-modal prompt injection.
DPD Chatbot Jailbreak
Analysis of the January 2024 DPD chatbot jailbreak where a customer manipulated the parcel delivery company's AI customer service bot into swearing, criticizing the company, and writing poetry about its own incompetence.
February 2026: Jailbreak Innovation Challenge
Develop novel jailbreak techniques against hardened language models and document them with reproducibility evidence. Judged on novelty, reliability, and transferability.
Community Challenge: Prompt Golf
Achieve jailbreaks with the shortest possible prompts, scored by character count. Develop minimal payloads that bypass safety alignment with maximum efficiency.
Monthly Competition: Model Breaker
Monthly competitions focused on discovering novel jailbreak techniques against updated model versions, with community-validated scoring.
Weekly CTF: Jailbreak Series
Weekly jailbreak challenges with new models and defenses each week.
AI Exploit Development
Adversarial suffix generation, gradient-free optimization, WAF-evading injection payloads, and fuzzing frameworks for AI systems.
Fine-Tuning-as-a-Service Attack Surface
How API-based fine-tuning services can be exploited with minimal data and cost to remove safety alignment, including the $0.20 GPT-3.5 jailbreak, NDSS 2025 misalignment findings, and BOOSTER defense mechanisms.
Jailbreaking via Persona Engineering
Research on using sophisticated persona engineering to bypass safety training in frontier models.
Reasoning Model Jailbreaks
How reasoning capabilities create novel jailbreak surfaces: chain-of-thought exploitation, scratchpad attacks, and why higher reasoning effort increases attack success.
RL-Based Jailbreak Optimization
Using reinforcement learning to optimize jailbreak strategies against black-box language models.
Automated Jailbreak Pipelines
Building automated jailbreak systems with PAIR, TAP, AutoDAN, and custom pipeline architectures for systematic AI safety evaluation.
Lab: Jailbreak Transferability Analysis
Analyze jailbreak transferability across model families to discover universal vulnerability patterns.
Lab: Jailbreak Technique Taxonomy
Explore the major categories of jailbreak techniques and practice classifying attack payloads by technique type.
Lab: Your First Jailbreak
Try basic jailbreak techniques against a local model using Ollama, learning the difference between prompt injection and jailbreaking through hands-on experimentation.
Lab: Basic Jailbreak Techniques
Hands-on exploration of jailbreak techniques including role-play, DAN-style prompts, and academic framing against multiple models.
Lab: Role-Play Attacks
Use persona-based approaches to bypass AI safety measures by assigning alternate identities, characters, and scenarios that override the model's trained refusal behaviors.
CTF: The Jailbreak Gauntlet
A series of progressively harder jailbreak challenges where each level adds stronger defenses. Score points through technique diversity and creativity as you break through escalating safety layers.
Lab: Build Jailbreak Automation
Build an automated jailbreak testing framework that generates, mutates, and evaluates attack prompts at scale. Covers prompt mutation engines, success classifiers, and campaign management for systematic red team testing.
Lab: Novel Jailbreak Research
Systematic methodology for discovering new jailbreak techniques against large language models. Learn to identify unexplored attack surfaces, develop novel attack vectors, and validate findings with scientific rigor.
Jailbreak Portability
Analysis of which jailbreaks transfer across models and why, including universal vs model-specific techniques, transfer attack methodology, and factors that determine portability.
GPT-4 Attack Surface
Comprehensive analysis of GPT-4-specific attack vectors including function calling exploitation, vision input attacks, system message hierarchy abuse, structured output manipulation, and known jailbreak patterns.
GPT-4 Known Vulnerabilities
Documented GPT-4 vulnerabilities including DAN jailbreaks, data extraction incidents, system prompt leaks, tool-use exploits, and fine-tuning safety removal.
Multimodal Jailbreaking Techniques
Combined multi-modal approaches to bypass safety alignment, including image-text combination attacks, typographic jailbreaks, visual chain-of-thought manipulation, and multi-modal crescendo techniques.
Attacks on Vision-Language Models
Comprehensive techniques for attacking vision-language models including GPT-4V, Claude vision, and Gemini, covering adversarial images, typographic exploits, and multimodal jailbreaks.
VLM-Specific Jailbreaking
Jailbreaking techniques that exploit the vision modality, including image-text inconsistency attacks, visual safety bypass, and cross-modal jailbreaking strategies.
Few-Shot Manipulation
Using crafted in-context examples to steer model behavior, including many-shot jailbreaking, poisoned demonstrations, and example-based conditioning.
Prompt Injection & Jailbreaks
A comprehensive introduction to prompt injection — the most fundamental vulnerability class in LLM applications — and its relationship to jailbreak techniques.
Jailbreak Techniques
Common patterns and advanced techniques for bypassing LLM safety alignment, including role-playing, encoding tricks, many-shot attacks, and gradient-based methods.
Many-Shot Jailbreaking
Power-law scaling of in-context jailbreaks: why 5 shots fail but 256 succeed, context window size as attack surface, and mitigations for long-context exploitation.
Role-Play Attacks
Establishing alternate personas or fictional scenarios that cause models to bypass safety training, including DAN variants, character hijacking, and narrative framing.
Social Engineering of AI
Manipulating AI systems through emotional appeals, authority claims, urgency framing, and social pressure tactics that exploit instruction-following tendencies.
Universal Adversarial Triggers
Discovering and deploying universal adversarial trigger sequences that reliably override safety alignment across multiple LLM families, including gradient-based search, transfer attacks, and defense evasion.
Lab: Exploiting Quantized Models
Hands-on lab comparing attack success rates across quantization levels: testing jailbreaks on FP16 vs INT8 vs INT4, measuring safety degradation, and crafting quantization-aware exploits.
Competition-Style Jailbreak Techniques
Walkthrough of jailbreak techniques used in AI security competitions and CTF events.
Role-Play Injection
Using fictional scenarios, character role-play, and narrative framing to bypass LLM safety filters by having the model operate within a permissive fictional context.
Virtual Persona Creation
Creating persistent alternate personas within LLM conversations to bypass safety training, establishing character identities that override the model's default behavioral constraints.