Automated Vulnerability Assessment

Abstract

Vulnerability assessment of end devices is not a new thing, but as the devices and generated data is increasing day by day, it requires even more complex system to ensure that all functionalities are working properly and patched against cyber attacks. In this project I have developed such a one-stop solution using a web portal which utilizes React, Flask framework and a number of open-source tools to identify vulnerabilities in network, operating systems, web applications and databases. Once a target is assessed, user can view a detailed report against target to prioritize vulnerability patching. First, user interacts with the developed application to provide input which is then utilizes to discover any kind of vulnerabilities or misconfigurations (if any) on specified target. Under the hood, It utilizes Nmap, Wapiti and a database of known vulnerabilities, along with their corresponding "signatures," or patterns of data that can be used to identify the vulnerability. It then compares the data collected from the target system to the signatures in its database to determine whether the system is vulnerable to any known exploits. One of the benefits of using a signature-based vulnerability scanning tool is that it can quickly and accurately identify known vulnerabilities, as it is based on a comprehensive database of known vulnerabilities. This can help administrators to quickly identify and fix vulnerabilities before they are exploited by attackers. For example, It might be used to scan a system’s network traffic, looking for patterns that match known vulnerabilities in a particular software application. If it finds a match, it will flag the system as potentially vulnerable to that exploit. There are several different types of data that It can analyze in order to identify vulnerabilities, including; specific patterns in network traffic that are known to be associated with particular vulnerabilities (For example, if it sees a certain type of HTTP request being sent to a web server, it might flag the server as potentially vulnerable to a particular type of web application attack), contents of files on the target system, looking for patterns that match known vulnerabilities (For example, it might look for specific strings of code or specific types of data that are known to be associated with a particular vulnerability), configuration settings of the target system, looking for settings that are known to be associated with vulnerabilities (For example, it might look for weak passwords or insecure network configurations) etc. It is worth mentioning that this kind of tool is generally considered to be less effective at detecting unknown vulnerabilities than other types of scanners, such as those that use machine learning or behavioral analysis techniques. However, It can be useful for identifying known vulnerabilities and for providing a baseline level of security for a system and should be used in conjunction with other security measures, such as a firewall and regular software updates.