My friend was disappeared by ICE for three days after a traffic stop in Nevada. He was arrested by Sheriffs, released, re-arrested by ICE in the parking lot, then held off the record. I built a jail roster monitor the next morning to find him. It alerted our Signal group the day that we was in jail under an ICE hold. Not a detention center. Jail. While I was building the jail roster scanner I noticed a data mining hook with Equifax on their recommended web portal "Vinelink", and warned my friends to NOT install the Sheriff app they require you to run to find someone that might be in their jail system. I later found that anyone searching for a loved one gave them access to read your SMS, phone history, location, and even activate your mic. Our friend group was being tracked the moment we started searching. Thus began a month-long struggle to know where my friend was being held: their chain of custody is non-existent, but spying ever-present in these law enforcement portals. This talk presents what I found inside 8 sheriff's apps, how the 287(g) program turns county jails into ICE infrastructure, and the zero-knowledge alternative I built so families can search without becoming targets.

Your government publishes data you need to monitor, but searching for it creates a trail you can't afford. In this workshop, you'll build a zero-knowledge notification service from scratch: encrypted queries, fuzzy matching against a live data source, and result delivery where the operator never sees what was searched or who asked. Then you'll flip sides: use Rizin to tear apart a real sheriff's app APK, extract hardcoded secrets and tracking infrastructure, and have an AI agent classify findings against a threat registry. You leave with both the surveillance-resistant alternative and the skills to audit what it replaces. The patterns come from Frio, a live system monitoring county jail rosters for families of ICE detainees, but the architecture generalizes to any public dataset where the act of searching is itself sensitive.