When working in digital forensics or threat intelligence, CSVs from SIEM tools, sandboxes, or log aggregators often hit hundreds of megabytes. Feeding those into Elasticsearch or a Python parser? It chokes.
I needed a way to reliably split massive CSVs into smaller, clean parts without losing data — and most free tools failed at either accuracy or usability.
So I built one.
My [Python-based CSV splitter](https://github.com/dfirvault/CSV_Splitter/) does two things right:
1. File-accurate size splitting — It tracks the actual bytes written to disk, not just assumptions.
2. Row integrity check — After splitting, it re-reads all split files to ensure no rows were dropped or duplicated.
It’s terminal-first, no clunky GUIs, and lets you select files and output folders via simple dialogs. Works on both Windows and macOS/Linux. Built for analysts who deal with massive exports but want confidence that nothing gets lost in the shuffle.
If you work with large log exports, give it a try — or fork it and make it better.
🔗 [View the source on GitHub](https://github.com/dfirvault/CSV_Splitter/)