An indexed catalog of working LLM jailbreak techniques.
An indexed, searchable catalog of LLM jailbreak techniques. Each entry: the prompt pattern, the models it works on, when it stopped working, the behavior it exploits — sourced from primary disclosure where possible, with honest attribution.
DAN Prompt Jailbreak History: From Reddit Post to Research Case Study
The complete dan prompt jailbreak history — how 'Do Anything Now' went from a December 2022 r/ChatGPT experiment through twelve-plus iterations and became the template for studying LLM safety failure modes.
Anomaly
The Crescendo Class: Multi-Turn Jailbreaks and Why They're Hard to Catch
Single-turn defenses miss the jailbreak class where no individual message is harmful. How crescendo and multi-turn escalation work as a category, why per-message classifiers can't see them, and what session-level defense requires.
How Jailbreak Benchmarks Measure Success: HarmBench, JailbreakBench, StrongREJECT
An attack-success-rate number is meaningless without knowing the behavior set, the attacker, and the judge that produced it. A reader's guide to the three benchmarks that define how jailbreak effectiveness is actually measured.
Many-Shot vs. Single-Shot Jailbreaks: Long-Context Risks
Single-shot jailbreaks compress the entire attack into one prompt; many-shot jailbreaks exploit the model's in-context learning. The cost, detectability, and defenses differ — and so does which threat your stack should worry about.
Trace
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Responsible Disclosure Norms for LLM Jailbreaks
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Encoding and Obfuscation Jailbreaks: The Filter-Model Gap
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The Jailbreak Detection Evasion Arms Race: How Attackers Adapt
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Roleplay and Persona Jailbreaks: Why They Mostly Don't Work Now
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Universal Adversarial Suffixes: The GCG Attack and Transfer Since
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LLM Jailbreak Taxonomy 2026: How the Techniques Cluster
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Many-Shot Jailbreaking: How Long Context Created a New Attack
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