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ZuckOff Is a Free App That Sees Meta Glasses Before They See You

You can’t always tell if someone is recording you with their smart glasses, but your phone can help.

ZuckOff Is a Free App That Sees Meta Glasses Before They See You

Meta's smart glasses have come under increasing scrutiny in recent months due to concerns over unsolicited filming, which poses a public safety threat. Some users have even been seen using these glasses to film their dates. In response, a free app called ZuckOff has been developed to help alert users to nearby Meta glasses. The app works by identifying Bluetooth signals emitted by various models of smart glasses, such as Ray-Ban Meta, Oakley Meta, and Snap Spectacles, and creating a digital fingerprint for each device.

Once a unique identifier matches with a manufacturer identifier, the app flags the presence of a specific model in the vicinity. The incident was brought to light by a BBC investigation that uncovered dozens of accounts posting content of women filmed in public by Meta glasses without their consent. In July, Meta announced plans to update its smart glasses to detect when the recording LED has been tampered with or destroyed, thus preventing people from filming using these cameras.

However, ZuckOff cannot determine if a nearby pair of glasses is actively recording nor can it identify the person wearing them. It provides rough proximity information based on signal strength, turning an invisible problem into a partially visible one. Though the app is free, a premium version called ZuckOff Pro is available for $25 and offers additional features such as history logging and continuous background monitoring.

Meta's smart glasses have sold roughly 7 million units in 2025, and California and other territories have enacted laws to penalize those who film people without their consent. Despite the app's limitations, it is still a valuable tool as legislators work on protective measures to address this growing issue.

Written by urgent.news from Wired's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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