Abstract
The article presents a methodical approach to developing recommendations and actions to ensure cybersecurity based on vulnerability and anomaly detection algorithms. Kali Linux tools are proposed as analysis and protection tools. With the growing number of attacks on corporate and network systems, traditional methods such as firewalls and intrusion detection systems are not always able to effectively counter complex and combined threats. The study analyzes Kali Linux tools that are used to detect and prevent attacks. The use of k-means clustering allowed us to effectively classify network traffic and identify abnormal deviations, and Snort was used to monitor suspicious activity on the network. Fail2Ban with adaptive blocking demonstrated high efficiency in protecting against password brute-force attacks, minimizing the likelihood of false locks. The experimental results confirmed that traffic filtering, configuring intrusion prevention systems and firewalls significantly reduce the likelihood of attacks. Network Exposure Score and Z-score were used to quantitatively analyze the level of network security, identify potential vulnerabilities, and assess the risk of account compromise.