Technology has become an indispensable part of society and everyday life. Amidst the emerging technology, embedded devices have made a remarkably huge entry into the market, with the most popular category being IoT devices. These devices have firmware embedded in them. However, the firmware might be subjected to some vulnerabilities. This is a crucial issue in the present-day world that cannot be avoided knowing the increase in potential attack surface. Considering the importance of this issue, it is highly essential to build measures for the protection and prevention of these devices from the attacker. In the present world several devices like routers, printers, and smartphones have undergone vulnerability analysis and analysis reports of these devices are available online. A variety of analysis tools are available online but the shortcomings they face are their particularity. Most tools are intended for a specific aspect of firmware analysis. However, the aim of our project is to provide a compact backdoor analysis toolkit that would cater to IP cameras of vendors locally and internationally and perform a detailed security analysis on them. In this thesis, we developed a complete framework combining online existing tools using static and dynamic analysis to verify the complications and challenges that are faced in large-scale security analysis. We have collected firmware images belonging to both local and international vendors.