LLM Red Teaming & Safety
Adversarial testing and safety evaluation of large language models
What this is
A research direction focused on systematic adversarial evaluation of LLMs, with an emphasis on safety-critical failure modes (misinformation, manipulation, harmful advice).
How I approach it
- Threat modeling: define attacker goals, constraints, and realistic interaction settings
- Red teaming protocols: controlled prompts, multi-turn attacks, and scenario-based probes
- Evaluation: failure taxonomies, severity scoring, and comparative model analysis
What comes out of it
- Reproducible red-team suites and documentation
- Failure-mode datasets and case studies
- Guidance for mitigation and safer deployment