Generative models are rapidly gaining popularity and being integrated into
everyday applications, raising concerns over their safety issues as various
vulnerabilities are exposed. Faced with the problem, the field of red teaming
is experiencing fast-paced growth, which highlights the need for a
comprehensive organization covering the entire pipeline and addressing emerging
topics for the community. Our extensive survey, which examines over 120 papers,
introduces a taxonomy of fine-grained attack strategies grounded in the
inherent capabilities of language models. Additionally, we have developed the
searcher framework that unifies various automatic red teaming approaches.
Moreover, our survey covers novel areas including multimodal attacks and
defenses, risks around multilingual models, overkill of harmless queries, and
safety of downstream applications. We hope this survey can provide a systematic
perspective on the field and unlock new areas of research.

生成模型和红队的攻击策略研究与语言模型的功能能力密切相关，调查还涉及到多模式攻击等新领域，希望这个调查能够为研究领域提供系统的视角并开启新的研究领域。