Data security is an important problem in digital campus construction. It is urgent to find a way to detect the risk and vulnerabilities of digital campus security. Therefore, a digital campus etwork security detection prototype was designed based on the improved BP algorithm. The data flow and nformation coming from the underlying network protocols(TCP) will be collected and pre-handled. The trained neural network module will react to these data and information, which gives the clue to determine the existing attack or scanning behavior in current network data flow. Rapid detection of digital campus existing vulnerabilities and security risks can prevent and reduce the attack and destruction.