The widespread application of AI can bring some challenges in network security, and it can also provide some solutions. Therefore, it is not possible to simply conclude that AI applications will make cybersecurity attacks easier or more difficult, but it will depend on the specific situation and how it is applied.

The potential impact of AI on network security is as follows:

1. Enhanced attack capabilities: Malicious use of AI technology may enhance the capabilities of attackers. They can use AI to conduct more effective cyber attacks, crack passwords, send phishing emails, and more. Through intelligent malware and attack techniques, attackers can better disguise and infiltrate target systems.

2. Detection and prevention: The application of AI technology in network security can also be used to detect and prevent threats. For example, AI can be used to monitor network traffic in real time, identify abnormal behaviors, automate the analysis of malicious code, etc. Through machine learning and deep learning, AI can help cybersecurity personnel better prevent and respond to attacks.

3. Countermeasures against attacks: AI can be used to counteract network security attacks. For example, AI technology can be used for automated defense, identifying and blocking malicious IPs, and simulating attacks to improve one's own security. By leveraging AI to automate response and remediation, cybersecurity teams can respond to and mitigate attacks faster.

In summary, the widespread application of AI may have a dual impact in the field of network security. It provides attackers with higher attack capabilities, while also providing network security workers with more tools and methods to deal with threats. The continuous optimization and improvement of network security requires the comprehensive use of multiple technologies, including AI technology, to maintain network security and protect user information.