Programmatic Generation of Synthetic Encrypted PDF Datasets for Automated Testing of Batch-Decryption Utilities

Validating document processing and decryption software requires diverse sets of test files, including password-protected and standard PDF formats. However, utilizing real-world documents introduces significant privacy and confidentiality risks. This paper presents a lightweight, script-based synthetic PDF generator developed in Python. The utility generates controlled datasets for batch-testing decryption software by programmatically constructing documents with varying structural layouts and applying user-level encryption, all without exposing sensitive operational data.