In recent years, Text-to-Image (T2I) models have seen remarkable advancements, gaining widespread adoption. However, this progress has inadvertently opened avenues for potential misuse, particularly in generating inappropriate or Not-Safe-For-Work (NSFW) content. Our work introduces MMA-Diffusion, a framework that presents a significant and realistic threat to the security of T2I models by effectively circumventing current defensive measures in both open-source models and commercial online services. Unlike previous approaches, MMA-Diffusion leverages both textual and visual modalities to bypass safeguards like prompt filters and post-hoc safety checkers, thus exposing and highlighting the vulnerabilities in existing defense mechanisms.

翻译：近年来，文本到图像（T2I）模型取得了显著进展并得到广泛采用。然而，这一进展无意间为潜在滥用打开了渠道，尤其是在生成不适宜或不宜公开浏览（NSFW）内容方面。我们的工作提出了MMA-Diffusion框架，该框架通过有效规避开源模型和商业在线服务中的现有防御措施，对T2I模型的安全构成重大且现实的威胁。与以往方法不同，MMA-Diffusion同时利用文本和视觉模态绕过诸如提示过滤器与事后安全检测器之类的防护机制，从而揭示并凸显现有防御体系中的脆弱性。