#llm-security

• How to Detect Jailbreak Prompts: The Three Layers

  The three jailbreak detection layers — input classifiers, output monitoring, and in-model sentinels — what each one catches, and where each is evaded.

• Automated Jailbreak Attacks: GCG, AutoDAN, PAIR, TAP

  Four automated jailbreak generators compared: GCG, AutoDAN, PAIR and TAP, by model access, query budget, prompt readability and detection signature.

• Promptfoo Alternatives for LLM Red Teaming

  OpenAI announced its acquisition of Promptfoo in March 2026. The open-source LLM red team tools that stayed vendor-neutral, compared by scope and depth.

• Prompt Injection vs Jailbreak: Two Different Attacks on LLMs

  Prompt injection and jailbreak get conflated constantly, but they hit different layers and need different defenses. Here is how to tell them apart.

• Best LLM Red Team Tools: Garak, PyRIT, and Promptfoo

  The best LLM red team tools are compared across attack coverage, multi-turn depth, CI integration, strengths, limitations, and ideal use cases.

• LLM Jailbreak Techniques Explained: Practitioner's Taxonomy

  A technical breakdown of LLM jailbreak techniques by attack category, from role-play bypasses to multilingual exploits and multi-turn escalation.

• DAN Prompt Jailbreak History: From Reddit Post to Case Study

  How 'Do Anything Now' went from a December 2022 r/ChatGPT experiment through twelve-plus iterations to the most studied jailbreak family on record.

• Crescendo Multi-Turn Jailbreaks: Why Defenses Miss Them

  Crescendo multi-turn jailbreaks evade per-message defenses by exploiting conversation context, requiring session-level classification and monitoring.

• 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.

• Responsible Disclosure Norms for LLM Jailbreaks

  Software vulnerability disclosure has 30 years of evolved norms. LLM jailbreak disclosure is 4 years old and still contested.

• Jailbreak Detection-Evasion Arms Race: How Attackers Adapt

  Jailbreak detection and evasion form an arms race in which attackers probe classifier boundaries and defenders use layered safeguards.

• Roleplay and Persona Jailbreaks: Why They Often Fail

  Roleplay and persona jailbreaks such as DAN use fictional framing, but modern safety training blocks many variants on frontier models.

• Universal Adversarial Suffixes: How the GCG Attack Works

  Greedy Coordinate Gradient finds nonsense token suffixes that jailbreak aligned LLMs and transfer to closed models, plus the defenses that blunt them.

• LLM Jailbreak Taxonomy 2026: How the Techniques Cluster

  Six years of jailbreak research has produced a messy literature. This taxonomy organizes working techniques by the behavioral property each one exploits.

• Many-Shot Jailbreaking: How Long Context Enables Attacks

  Many-shot jailbreaking exploits extended context windows by using repeated demonstrations that can weaken a model's safety-trained refusal behavior.

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