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Misinformation on social media has become an alarming problem in recent years; the advent of social media platforms as a news source serves as a critical factor. Let alone misinformation; recently, social media platforms have faced a new challenge of tampered impersonated content (i.e., Tweets). Although several approaches have been proposed to detect misinformation, there is not much attention has been given to detecting impersonated fake content (i.e., Tweets). With the free tools available on the internet, it is very easy to generate a fake screen capture of a tweet. These tools are intended for fun, but the problem arises when they get weaponized to generate fake news and impersonated content. In this paper, we propose a framework that can help to detect tampered and impersonated tweets on other social media platforms or any digital platforms. We validate the results of the proposed framework with the …