Introducing the XLab AI Security Guide
An educational guide with coding replications covering adversarial attacks on image models, LLM jailbreaks, defenses, and fine-tuning-based model tampering, motivated by catastrophic misuse risks.
AI research and discussion on LessWrong. www.lesswrong.com
An educational guide with coding replications covering adversarial attacks on image models, LLM jailbreaks, defenses, and fine-tuning-based model tampering, motivated by catastrophic misuse risks.
Red-teams gpt-oss-20b with a chain-of-thought repetition jailbreak, finding high robustness overall but non-monotonic attack success with repeats, CoT that contradicts final outputs, and hallucinated policies.
Compares latent adversarial training with standard safety fine-tuning on how refusal is encoded in LLaMA 2 7B. LAT concentrates refusal in top SVD components, yielding more effective refusal-ablation vectors while staying most robust against self-ablation.