Meta Adds Face-Recognition Code to Smart-Glasses App

Meta embedded unreleased face-recognition code, internally named "NameTag," into the Meta AI app used with Ray-Ban and Oakley smart glasses, according to a WIRED code review. The code, added as early as January, would convert faces into biometric "faceprints" stored on a user's phone and trigger notifications upon recognition, with the app downloaded over 50 million times. More than 70 civil-society groups, including the ACLU, have urged Meta to halt the plans, citing the company's past $650 million class-action settlement and $1.4 billion related settlement over biometric privacy.

Meta Adds Face-Recognition Code to Smart-Glasses App WIRED's code review found unreleased face-recognition functionality, internally called "NameTag," embedded in the Meta AI app , which the publication says has been downloaded more than 50 million times WIRED . The code, added to the live app as early as January, would convert faces captured by Ray-Ban and Oakley smart glasses into biometric "faceprints" stored or compared on a user's phone and trigger notifications when someone is recognized WIRED; Gizmodo . Cooper Quintin, a security researcher at the Electronic Frontier Foundation's Threat Lab who reviewed the code for WIRED, called the implementation "nearly ready to go" Gizmodo/WIRED . Civil-society groups including the ACLU have publicly urged Meta to halt or disavow these plans in a letter signed by more than 70 organizations Mashable; ACLU . What happened WIRED published a technical review finding unreleased face-recognition code, internally named NameTag, embedded in the Meta AI app , the companion app used with Ray-Ban and Oakley smart glasses WIRED . WIRED reports the app has been downloaded more than 50 million times and that core components were added to the live app as early as January WIRED . Per WIRED, the functionality would detect faces, crop them, convert them into biometric "faceprints," compare them against faceprints stored on a user's phone, and surface notifications when matches occur WIRED . Cooper Quintin, a security researcher at the Electronic Frontier Foundation 's Threat Lab who reviewed the code for WIRED, described the implementation as "nearly ready to go" Gizmodo; WIRED . Technical details Editorial analysis - technical context: Public reporting describes three on-device model roles being present in shipped app builds: face detection, face cropping/segmentation, and encoding faces into biometric signatures. Industry practice for on-device face systems is to keep inference local while enabling updates via model downloads; that architecture reduces some server-exposure risk but preserves a significant biometric attack surface on user devices. Reports also note the phone-side database is configured to accept updates from Meta, which observers treat as a functional design choice with operational implications WIRED . Context and significance The emergence of embedded face-recognition code matters because of Meta's past legal and regulatory history. WIRED notes Meta previously sunsetted its large-scale faceprint dataset in 2021 and paid a $650 million class-action settlement; WIRED also reports a $1.4 billion settlement the company agreed to in 2024 in related litigation WIRED . Civil-society opposition has been vocal: more than 70 groups including the ACLU have publicly demanded Meta halt or disavow the feature Mashable; ACLU . Public reporting also cites internal deliberations and memos about targeted rollouts and timing considerations TechCrunch . What to watch observers will monitor whether Meta enables the feature in production, how the phone-side faceprint database is provisioned and updated, whether the company publishes a technical privacy specification, and any regulatory or enforcement actions from state attorneys general or the FTC. Watch for concrete company disclosures about opt-in controls, retention windows, and third-party access to the biometric data; if those details are published, they are the factual basis for further technical and compliance assessment. Additionally, advocacy letters and potential state- or federal-level privacy legislation remain likely influence points on deployment decisions ACLU; TechCrunch . Editorial analysis: For practitioners, this episode reinforces a recurring pattern: embedding dormant or reversible biometric capabilities into consumer-facing apps accelerates adversarial and regulatory scrutiny. Security teams and product engineers building similar features should plan for high-scrutiny threat models, clear opt-in/consent flows, and auditable local data handling practices, because public code presence alone can trigger legal and reputational consequences even before a feature ships. Scoring Rationale Notable privacy and security implications for practitioners: an unreleased biometric pipeline appears embedded in an app downloaded by millions, and civil-society and legal precedents make regulatory scrutiny likely. The story affects product design, threat modeling, and compliance work. Practice with real Ad Tech data 90 SQL & Python problems · 15 industry datasets Active Search Campaigns by BudgetEasy /problems/sql/active-search-campaigns-by-budget High CPC Clicks & Poor Landing PagesMedium /problems/sql/high-cpc-clicks-poor-landing-page Campaign ROAS by Attribution ModelHard /problems/sql/campaign-roas-by-attribution-model 250 free problems · No credit card See all Ad Tech problems /problems/datasets/adtech