How big can your PDF page be?

This tweet reflects an out-of-date understanding of PDF (or rather, PDF implementation) limitations. In fact, the most recent specification of PDF, PDF 2.0, includes no such limit in the file format specification. 

PDF 1.6 introduced the UserUnit key which is effectively a multiplier of the default 1/72 inch coordinate system used by PDF. UserUnit is explicitly described as follows: ”The range of supported values shall be implementation-dependent”. 

In modern 64-bit operating systems and applications, and since PDF is widely used in cartography, geospatial and astronomical applications, specialized PDF applications may support very large UserUnit values, potentially resulting in PDF applications capable of supporting ginormous page sizes!

Whether or not your authoring application is capable of supporting a PDF large enough for a 1:1 map of Europe… that’s another matter.

PDFacademicBot for July 2023

Vishnu, N.S. et al. (2022) ‘PDF Malware Classifiers – A Survey, Future Directions and Recommended Methodology’, in Information Security Handbook. 1st edn. Boca Raton, USA: CRC Press, p. 24. Available at: https://www.taylorfrancis.com/chapters/edit/10.1201/9780367808228-7/pdf-malware-classifiers-survey-future-directions-recommended-methodology-vishnu-sripada-manasa-lakshmi-kavita-sahil-verma-awadhesh-kumar-shukla.

Vishnu, N.S. et al. (2022) ‘PDF Malware Classifiers – A Survey, Future Directions and Recommended Methodology’, in Information Security Handbook. 1st edn. Boca Raton, USA: CRC Press, p. 24. Available at: https://www.taylorfrancis.com/chapters/edit/10.1201/9780367808228-7/pdf-malware-classifiers-survey-future-directions-recommended-methodology-vishnu-sripada-manasa-lakshmi-kavita-sahil-verma-awadhesh-kumar-shukla.

Vishnu, N.S. et al. (2022) ‘PDF Malware Classifiers – A Survey, Future Directions and Recommended Methodology’, in Information Security Handbook. 1st edn. Boca Raton, USA: CRC Press, p. 24. Available at: https://www.taylorfrancis.com/chapters/edit/10.1201/9780367808228-7/pdf-malware-classifiers-survey-future-directions-recommended-methodology-vishnu-sripada-manasa-lakshmi-kavita-sahil-verma-awadhesh-kumar-shukla.

Symeon (no date) Grammar based fuzzing PDFs with Domato, Grammar based fuzzing PDFs with Domato. Available at: https://symeonp.github.io/2020/04/18/grammar-based-fuzzing.html.

Tabernero-Rico, R.D., Pozo-González, S.-F. and Prats-Galino, A. (2022) Management of a 3D Visualization Program From Radiological Images in Neuroradiology, Technological Adoption and Trends in Health Sciences Teaching, Learning, and Practice. IGI Global. Available at: https://doi.org/10.4018/978-1-7998-8871-0.ch010.

Stefanovitch, N. (2022) ‘Recovering Text from Endangered Languages Corrupted PDF documents’, in Proceedings of the Fifth Workshop on the Use of Computational Methods in the Study of Endangered Languages. ACL-ComputEL 2022, Dublin, Ireland: Association for Computational Linguistics, pp. 78–82. Available at: https://aclanthology.org/2022.computel-1.10.

Nguinabe, J. et al. (2023) ‘Fals-Ism: A Graph Isomorphism Framework for Multi-Level Detection of Falsified PDF Documents’, Journal of Computer Science, 19(5), pp. 667–676. Available at: https://doi.org/10.3844/jcssp.2023.667.676.

Tullsen, M., Harris, W. and Wyatt, P. (2022) ‘Research Report: Strengthening Weak Links in the PDF Trust Chain’, in. 2022 IEEE Security and Privacy Workshops (SPW), San Francisco, USA: IEEE (LangSec’22), pp. 152–167. Available at: https://doi.org/10.1109/SPW54247.2022.9833889.