In recent years, we have seen an exponential increase in the exposure of synthetic face videos on the Internet. This surge poses several serious risks, including threats to the authenticity of digital content and the facilitation of misinformation and identity-related fraud. The currently existing methods to identify these deepfakes are significantly less effective against the newly developed synthetic faces implemented with advanced technologies. Therefore, we introduce this work, which will work flawlessly in identifying synthetic faces and differentiating the content as authentic or fake. Real humans exhibit synchronized biological rhythms. Utilizing this fact, we have trained a model that can extract these rhythms, and their absence can be used for identifying synthetic faces.