In this paper, we propose TONO, a high-quality synthetic dataset for the development and evaluation of systems aimed at verifying face image compliance to the ISO/ICAO standard for electronic Machine Readable Travel Documents (eMRTD). The requirements outlined in this standard, such as frontal face, neutral expression and gaze in camera, are key elements in ensuring the effectiveness of biometric identity face-based verification systems. These tools, crucial for national security, are used for instance in automated gates within international airports. Despite the importance of this topic, the availability of public datasets representing adequately the different requirements is very limited. TONO is the first synthetic privacy-compliant dataset publicly released ( https://miatbiolab.csr.unibo.it/tono-synthetic-dataset ) for training and evaluating such systems. In the experimental evaluation, two commercial SDKs and public ISO/ICAO compliance verification software are evaluated on TONO.