Everyone uses Drata to automate evidence collection. But what happens when the source system spits out a malformed JSON or a CSV with missing columns? You upload it, Drata's engine flags it, and now you're scrambling to fix it during an audit window.
I wrote a simple pre-check script. It validates file structure, checks for required fields against a config, and ensures date formats are correct. Run it locally or in your CI/CD pipeline before the sync job kicks off. It won't catch everything, but it prevents the obvious junk from triggering a compliance fire drill.
The real cost in these platforms isn't the license fee—it's the labor wasted on cleanup and the risk of audit delays because of bad data. This script mitigates that. Find it on my GitHub. Use it, fork it, improve it. Don't let the vendor's tool dictate your evidence quality.