Generative AI (GAI) models have been rapidly advancing, with a wide range of
applications including intelligent networks and mobile AI-generated content
(AIGC) services. Despite their numerous applications and potential, such models
create opportunities for novel security challenges. In this paper, we examine
the challenges and opportunities of GAI in the realm of the security of
intelligent network AIGC services such as suggesting security policies, acting
as both a ``spear'' for potential attacks and a ``shield'' as an integral part
of various defense mechanisms. First, we present a comprehensive overview of
the GAI landscape, highlighting its applications and the techniques
underpinning these advancements, especially large language and diffusion
models. Then, we investigate the dynamic interplay between GAI's spear and
shield roles, highlighting two primary categories of potential GAI-related
attacks and their respective defense strategies within wireless networks. A
case study illustrates the impact of GAI defense strategies on energy
consumption in an image request scenario under data poisoning attack. Our
results show that by employing an AI-optimized diffusion defense mechanism,
energy can be reduced by 8.7%, and retransmission count can be decreased from
32 images, without defense, to just 6 images, showcasing the effectiveness of
GAI in enhancing network security