This paper introduces a novel method for detecting images generated by Generative Adversarial Networks (GANs) by analyzing their unique frequency-domain 'fingerprints'. It leverages the 2D Discrete Fourier Transform to reveal subtle periodic artifacts, achieving significantly higher accuracy than spatial-domain methods when combined with a ResNet50 classifier.