Tag

#red-teaming

Every item tagged red-teaming, newest first.

2 items

A Red-Team Study of Anthropic Fable 5 & Opus 4.8 Models

Researchers evaluated Anthropic's Fable 5 and Opus 4.8 models' robustness against automated jailbreak attacks across 7,826 harmful intents. Using the HackAgent framework, they generated hundreds of thousands of adversarial attempts. Both models resisted most attacks, but showed vulnerabilities to certain attack types. The study provides insights into LLM security for builders.

Key takeaways

Fable 5 and Opus 4.8 resisted most automated jailbreak attacks.
Models showed vulnerabilities to specific attack types.
Study used HackAgent framework and 3-judge model adjudication.

aarXiv#llm-security #adversarial-robustness #red-teaming

researchFeb 24

Red-Teaming Large Language Models

Researchers at Hugging Face conducted red-teaming experiments on large language models to assess their safety and security. The goal was to identify vulnerabilities and improve model robustness. You can explore the methodology and results on the Hugging Face blog. This work contributes to the development of more secure AI systems.

Key takeaways

Hugging Face researchers performed red-teaming experiments on LLMs.
Goal was to identify vulnerabilities and improve model robustness.
Results and methodology are publicly available.

HHugging Face Blog#red-teaming #llm-safety #security