LLM Red Teaming
A hub for prompt injection, jailbreaks, tool misuse, and the operational mindset behind adversarial testing of language models.
Treating LLM red teaming like generic prompt play instead of system abuse.
Ignoring tool execution and retrieval in threat modeling.
Launching copilots without tested adversarial behavior baselines.
Built For
AI security engineers building or reviewing LLM products.
Product teams preparing red-team-ready launch criteria.
Researchers mapping prompt and orchestration weaknesses.
Use Cases
Learn how prompt injection and jailbreak tactics actually chain into impact.
Use the hub as an entry point into practical Eresus AI research.
Connect testing methodology to deployment reality.
Related Content
The Art of LLM Jailbreaking: Demystifying Offensive Prompt Engineering
How do Red Teamers bypass the safety filters of Large Language Models? Dive deep into the manipulative art of LLM Jailbreaking, DAN prompts, and...
Artificial Intelligence (LLM) Manipulations: Prompt Injection and RAG Poisoning
How does the shiny new ChatGPT clone your company launched fall straight into the hands of cyber attackers? An anatomical breakdown of Direct and...
Beyond Jailbreaks: Contextual Red Teaming for Agentic AI
Why traditional prompt jailbreaking is insufficient, and how contextual red teaming is required for multi-step agentic systems.
Related Advisories
Frequently Asked Questions
Does red teaming only mean jailbreak prompts?
No. It includes context poisoning, unsafe tool use, retrieval abuse, hidden instructions, and downstream system impact.
Is this page a methodology hub?
Yes. It is intended to gather the core concepts and connect them to deeper posts and advisories.
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