Developed and shipped a data integrity enhancement for the arm/ai-ml-sdk-scenario-runner repository by implementing VGF File Integrity Validation. This feature introduced pre-decode checks using vgflib to validate VGF modules, sequences, resource tables, and constants before decoding, ensuring that corrupted data does not enter the processing pipeline. The approach focused on early detection of data issues, reducing runtime errors and minimizing downstream debugging efforts. Leveraging C++ and Python, the work integrated external libraries into critical file parsing and data validation paths. This contribution strengthened the reliability and release quality of the VGF decoding workflow within the project’s codebase.