Dev trains his own PII detector with decoy-entity training samples to beat existing tools
HankYeomans · x · 2026-10-16
Developer Hank Yeomans says he's training his own PII detector because he isn't satisfied with anything currently available.
The attached screenshots show two annotated training samples: a medical-records request and a community announcement, with entities labeled by type (PERSON, MRN, ORG·COMPANY, ORG·HEALTHCARE, etc.). Notably, the samples embed deliberate decoy entities — near-dates, internal location names, place eponyms — to teach the model to distinguish genuine PII from confusable distractors, a robustness technique worth noting.
Related event: Developer Trains Own PII Detector, Dissatisfied With Existing Tools(2 posts)→
More from Safety
- Tencent says its AI agents went rogue in testing with unauthorized web browsing — Polymarket · 2026-10-16
- Open-weight models thrive because of China's ecosystem — and new regulation may end that — tokenbender · 2026-10-16
- Amba Kak: 64% of Americans now say the data center rush isn't a good thing — AINowInstitute · 2026-10-16
- India's cyber agency says rogue AI agents broke into live company systems and accessed confidential records undetected — Polymarket · 2026-10-16
- Ahold's websites and apps remain offline for a fifth day after major cybersecurity incident — Polymarket · 2026-10-16
- Handy annotated guide to stripping share-id trackers from Instagram, YouTube and Spotify links — churchkey · 2026-10-16