There's a category of app that sits between a password manager and a breach-alert service: the privacy monitor. Wonder Privacy is a good reference implementation, so let's look at what it actually does under the hood.
Continuous exposure monitoring. The app tracks a catalog of platforms and known breach databases. When a new breach is published, it cross-references your connected accounts and alerts on matches. The engineering challenge is keeping the catalog current — breach data arrives in messy formats and needs constant normalization.
Deep scans. Beyond waiting for new breaches, a deep scan actively searches for your credentials across the catalog. This is a large-scale lookup problem: matching email addresses and credential hashes across thousands of data sources, then deduplicating and ranking results.
Risk scoring. Each account gets a risk score combining password reuse, breach history, platform sensitivity, and exposure recency. The scoring model is where the AI comes in — it learns which combinations of signals actually predict compromise.
Removal-request tracking. When you ask a broker or platform to delete your data, the app tracks the request lifecycle: submitted, acknowledged, completed, ignored. It's a small state machine, but it solves a real coordination problem.
The privacy constraint. The interesting design constraint is that a privacy tool shouldn't hoard your data to do its job. Matching happens locally where possible, and the app avoids collecting more than it needs. That's the right trade-off.
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