Meta pulled facial recognition code from its smart glasses app one day after WIRED found it


TL;DR

Meta stripped NameTag facial recognition code from its AI app one day after WIRED exposed it on 50 million phones. Meta says no decision has been made.

Meta removed nearly all traces of an unreleased facial recognition system from its smart glasses companion app on Friday, one day after WIRED reported that the software had been quietly embedded in an app installed on more than 50 million phones. The feature, which Meta internally called NameTag, was designed to convert faces captured by the company’s Ray-Ban smart glasses into unique biometric signatures and compare them against a database stored on the user’s device. WIRED also found that faces the system failed to recognise were cropped, indexed, and stored locally for future processing.

Andy Stone, Meta’s vice president of communications, told WIRED on Monday that the feature is “purely exploratory,” adding that no final decision has been made on what to do with it. That characterisation sits uneasily with the evidence WIRED documented. The version of Meta AI published the day of WIRED’s Thursday report contained several code libraries explicitly named for face recognition, a process for running the NameTag recognition pipeline, and a “Person recognised” alert the app would have shown if someone were identified.

Friday’s release stripped all of it out, along with a folder where the app would have stored the cropped images and biometric signatures of unrecognised faces. Meta did not answer WIRED’s questions about why the code was removed or whether the changes were planned before the story was published. A few fragments remain in the latest version, including an internal debug menu label and a dormant link meant to open a recognised person’s profile, pointing to parts of the system that are no longer there.

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The gap between Meta’s public statements and the code WIRED found is the central tension. Before the Thursday report, Stone dismissed the findings by writing that the company could not answer questions about how the system would work because “the feature does not exist.” Andrew Bosworth, Meta’s chief technology officer, called the reporting “incredibly misleading” and “absolutely dishonest.” Yet the code was functional enough to include three AI models, one to detect faces, another to crop them, and a third to encode them as biometric data, all embedded in the companion app for a product already at the centre of a mounting privacy crisis.

Meta declined to answer ten questions WIRED posed before publishing, including whether it had already created the database of face profiles NameTag uses, how long the app retains photographs and biometric data of unrecognised people, and whether that data would ever be sent back to Meta’s servers. The company also did not respond to questions about whether it was building NameTag for blind or low-vision users, or to criticism from privacy advocates who warned the system could let stalkers and abusers identify strangers in public.

NameTag first surfaced in February, when The New York Times, citing internal Meta documents, reported that the company was developing face recognition for its smart glasses and considering a launch as early as this year. One internal memo reportedly described releasing the feature during a “dynamic political environment” when privacy and civil liberties advocates would be distracted by other concerns. WIRED subsequently found that much of NameTag’s machinery had been built into the Meta AI app as early as January, months before any public acknowledgement, adding another layer to the company’s pattern of shipping first and disclosing later when it comes to its smart glasses.

Kade Crockford, director of the technology for liberty programme at the American Civil Liberties Union of Massachusetts, said the removal does not undo the original decision to ship the code and pointed to it as evidence that consumer privacy needs stronger legal protection than Congress has been willing to provide. The Massachusetts House of Representatives last week unanimously passed a consumer privacy bill that, if enacted as written, would impose strong enforcement provisions including a private right of action allowing aggrieved users to sue. “State lawmakers need to do their job and step up to protect consumer privacy,” Crockford said.

Meta’s sneaky tactics in slipping the face-recognition code into its smart glasses show exactly why data privacy bills need the teeth of strong enforcement,” Crockford added. “Companies like Meta prioritise their bottom line, so lawmakers need to speak in the only language its C-suite understands.” Whether a code removal prompted by investigative reporting constitutes a victory or merely a tactical retreat depends on what Meta does next, and on whether the regulatory pressure building on both sides of the Atlantic produces enforceable consequences before the feature quietly returns under a different name.



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Ghost CMS flaw abused to push ClickFix attacks on hundreds of sites

Pierluigi Paganini
May 25, 2026

Threat actors are actively exploiting a security flaw, tracked as CVE-2026-26980, in Ghost CMS that was fixed months ago in real attacks against unpatched websites. According to Qianxin, the campaign has already affected more than 700 sites, including well-known organizations and universities.

The vulnerability is an SQL injection issue in Ghost’s Content API that can let an attacker read data from the database without logging in. In the worst case, this can expose the Admin API key, which can allow attackers to take over the site.

That key matters because it can be used to change published content. In this campaign, attackers used it to edit articles on compromised Ghost sites and insert malicious JavaScript at the end of pages. The goal was not just defacement, but to turn trusted websites into launch points for further malware delivery.

“After an in-depth investigation and analysis, we determined that this was not a targeted intrusion against the customer, but rather a large-scale poisoning campaign by an in-the-wild attack group targeting Ghost CMS. Although CVE-2026-26980 was publicly disclosed as early as February 19, a large number of users did not patch and upgrade in time, providing an opportunity for attackers.” reads the advisory published by Qianxin. “At least two groups are currently actively conducting such poisoning operations, and some sites have even become the target of competition between the two parties, with different malicious code being implanted one after another within a single day.”

The inserted code led visitors through a two-step chain. First, the page loaded a remote script that checked the browser and decided what the visitor should see. Then real victims were redirected to a fake verification page that looked like a normal “I’m human” check.

This is where the ClickFix part began. The page told users to press Windows+R, paste a command, and hit Enter. In practice, that command downloaded and started a malware payload on the victim’s machine. It was a classic social engineering trick: make the user do the dangerous part themselves.

Qianxin says the first signs of this activity appeared in early May. The malicious code found in the campaign had a compilation date of February 16, the same day Ghost announced the fix for CVE-2026-26980. That suggests the attackers moved quickly once they saw how many sites had not been updated.

The affected websites cover a wide range of sectors. Roughly half are personal blogs or independent sites, but the list also includes technology blogs, AI sites, media outlets, crypto projects, and educational institutions. Qianxin researchers say victims include sites linked to Harvard, Oxford, and DuckDuckGo.

The attack chain was also designed to be flexible. The loaders could fetch different payloads depending on the target, and the operators changed infrastructure several times.

“entire attack process has obvious five-stage characteristics of “CMS Takeover → Page Poisoning → Two-stage Loading → Social Engineering Lure (FakeCaptcha/ClickFix) → Malware Delivery”, and the entire process is highly automated: bulk vulnerability scanning → automatic key extraction → bulk injection → dynamic C2 distribution.” states the report.

In some cases, they switched domains after detection, keeping the campaign alive even when part of the chain was blocked.

“Through feature scanning of publicly accessible pages, we have cumulatively identified more than 700 poisoned victim domains, and have proactively contacted the sites for which contact information could be obtained, notifying them of the poisoning.” continues the report.

Qianxin also believes at least two different groups are involved. In some cases, the same site was hit more than once, with one attacker replacing the code left by another. That makes the campaign harder to clean up and shows how attractive compromised Ghost sites have become for abuse.

For site owners, the advice is straightforward. Ghost should be updated immediately, all credentials should be rotated, and site logs should be reviewed for suspicious admin API activity. Any injected scripts should be removed from the database itself, not just from the visual editor. Visitors who may have reached a poisoned site should also be warned.

The report includes Indicators of Compromise (IoCs) for the attacks observed by the researchers.

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Pierluigi Paganini

(SecurityAffairs – hacking, Ghost CMS)







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