To improve the effectiveness of campus network security vulnerability detection, this paper proposes a vulnerability scanning system based on SSA-LSTM (Sparrow Search Algorithm-Long Short-Term Memory), which is optimized for the defects of LSTM such as difficult parameter selection and slow convergence speed. In terms of network intrusion detection, malware identification, abnormal behavior analysis and data leakage prevention, the application of artificial intelligence technology can not only quickly discover and deal with threats, but also effectively prevent and reduce security risks. Finally, through practical cases and effect analysis, the practical application effect of artificial intelligence technology in campus network security is verified. The experimental analysis shows that the application of SSA-LSTM vulnerability scanning system proposed in this paper in campus network environment can effectively improve the security of campus network.