Deepfakes, which are powered by artificial intelligence, have emerged as a formidable cybersecurity challenge with far-reaching implications. This paper provides a comprehensive analysis of deepfakes and their implications for cybersecurity, focusing on the evaluation of existing deepfake detection systems. The paper specifically examines how deepfakes pose significant security threats, including identity theft, fake news, and other cyberattacks. The security analysis is conducted on the attacks across various domains, such as politics, government, finance, entertainment and social media. Existing detection tools include machine learning, blockchain-based verification, digital watermarking, and evaluation for their effectiveness and limitations in combating deepfakes. Finally, the paper discusses potential improvements in detection methods, emphasizing the need for AI-based countermeasures, collaborative systems, public awareness, and regulatory measures to mitigate these risks.