Engineer hacks Whoop 5.0 tracker to bypass $199/yr subscription in just 24 hours
Imagine buying a sleek piece of health tech only to realize it becomes a useless plastic brick unless you feed the corporate overlords a fat annual ransom. Welcome to modern hardware, where you own nothing and pay forever. But one hero had enough.
A developer known as bennett took matters into his own hands by reverse-engineering the Whoop 5.0 fitness band to work entirely offline and subscription-free. In just one single day of intense coding, he built Goose, an open-source local companion app that completely replaces the official paid platform.
The sleek tracker is famous for monitoring sleep, strain, and recovery, but its business model relies on a hefty subscription. Without the app, the physical band is literally a paperweight. bennett started his coding sprint by establishing a local Bluetooth connection and hooking up a Rust backend to process live heart rate data in his first hour.
By the third hour, he had built a polished mobile user interface, synchronized backlog data, and actually went for a run to compare the raw sensor outputs against his Apple Watch. Six hours in, the app gained full workout statistics, resting heart rate calculations, and even a local AI coach running directly inside the iOS application.
After a quick nineteen-hour pause to sleep and test the sleep-tracking capabilities, the developer emerged with a fully functional local app. The resulting tool, Goose, extracts everything from heart rate variability to skin temperature and blood oxygen levels directly from the device's hardware sensors, proving that corporate cloud servers are mostly just expensive gatekeepers.
This weekend project exposes the absolute scam of the modern 'hardware-as-a-subscription' trend, proving that a single motivated developer can replace an entire corporate software ecosystem in a day. Of course, setting it up currently requires compiling Rust and messing with Xcode, so average users will have to wait for the public beta or start learning how to code.
Source: GitHub
Comments
This is where the magic happens: AI reads your discussion and rewrites the article based on the most interesting comments. Each strong comment adds points to the meter below. Once the meter is full, the article updates live — no page reload needed.