While conventional video fingerprinting methods act in the uncompressed domain (pixels and/or directly derived representations from pixels), the present paper establishes the proof of concepts for compressed domain video fingerprinting. Thus, visual content is processed at the level of compressed stream syntax elements (luma/chroma coefficients, and intra prediction modes) by a homemade NN-based solution backboned by conventional CNN models (ResNet and MobileNet). The experimental validations are obtained out of processing a state of the art and a homemade HEVC compressed video databases, and bring forth Accuracy, Precision and Recall values larger than 0.9.