This LLM security sample covers model vulnerabilities, prompt injection attacks, red teaming, and practical defenses in a focused academic format.
This thesis systematically catalogs adversarial prompting techniques used to bypass safety filters in commercial LLMs. By constructing a red-teaming test suite of 200+ prompts across 6 attack categories, the study evaluates the robustness of current alignment methods and proposes a defense scoring framework for model developers.