AI Red Teaming Security

AI red teaming is adversarial testing of large language models (LLMs) and AI systems. Red teamers attempt to break models by: crafting adversarial prompts that trigger unsafe outputs, injecting malicious instructions into retrieval contexts, extracting model weights via API queries, manipulating system messages, and testing alignment with stated values. The goal is finding vulnerabilities before malicious actors do. Red teaming combines prompt engineering, cybersecurity thinking, and model understanding. It's systematic: build a taxonomy of attacks, test each category, document findings, propose defenses, iterate.