Network Asset Sensitive Information Management System Based on Golang

With the swift upsurge in the quantity of IoT devices in the power Internet of Things, as well as their intrinsic heterogeneity, limited computing power, and weak network load capacity, collecting IoT assets becomes challenging, and these devices are highly susceptible to external attacks. To address this issue, a network asset sensitive information management and control tool is designed specifically for organizations such as power grids that possess numerous IoT devices and other network assets. This tool automates the collection and pre-warning of vulnerabilities associated with assets like IoT devices and domain names in the power network. By doing so, it significantly reduces the need for human resources, material costs, and potential economic losses, while also minimizing the risk of network attacks on the power grid. However, many asset-sensitive information collection systems are initially designed without sufficient consideration of corresponding security protection mechanisms, making them highly vulnerable to attacks and exploits by hackers. Consequently, these systems often suffer from incomplete information collection, leakage of sensitive information, and other abnormalities. To address these shortcomings, this study focuses on the development of a fast and accurate Internet asset high concurrency scanning tool based on the Go programming language. Additionally, it investigates device fingerprint collection methods for ports and leverages YAML integration to achieve efficient and precise device fingerprint collection. Moreover, the study explores the use of Echarts for visualizing big data, enabling data analysis visualization, and facilitating the rapid identification of risk assets by relevant personnel. Furthermore, it examines the implementation of a precise risk warning and notification function based on containerized deployment, assisting relevant personnel in promptly responding to and defending against potential threats.