Chinese AI lab says it can match Anthropic’s all-poweful Claude Mythos at sniffing security bugs


For the past few weeks, Anthropic’s Mythos has been viewed as the gold standard for AI-powered cybersecurity. That lead may already be shrinking. According to a new report from The Wall Street Journal, security researchers say Chinese AI startup Z.ai’s GLM-5.2 can now match Mythos when it comes to finding software security vulnerabilities, even if it still trails Anthropic and OpenAI in broader reasoning tasks.

GLM-5.2 is closing the gap in one very important area

As per the report, researchers found GLM-5.2 performs on par with Mythos in identifying software bugs, a capability that’s becoming increasingly important as companies race to patch vulnerabilities before hackers can exploit them. The model is also open-source, meaning anyone can download, modify, and run it on their own hardware without relying on a cloud provider. That flexibility makes it attractive for enterprises, but it also raises concerns that cybercriminals could adapt it for offensive purposes.

The report is careful to point out that this doesn’t mean China has overtaken the U.S. in AI overall. GLM-5.2 still lags behind Anthropic and OpenAI across many general-purpose tasks. But in cybersecurity, where even small improvements can have outsized real-world consequences, the performance gap has narrowed dramatically. According to benchmark data cited by the Journal, GLM-5.2 has even outperformed Claude Opus 4.8 in some security evaluations, while researchers say additional prompting allows it to reach Mythos-level bug-finding performance.

The bigger story isn’t who wins. It’s how fast the gap is closing

Interestingly, this all comes at a rather awkward time for the U.S. AI industry. While companies like Anthropic and OpenAI have spent the past few weeks restricting access to their most advanced frontier models over national security concerns, Chinese labs have been racing in the opposite direction by releasing increasingly capable open-weight alternatives that anyone can download and run.

The funny thing is that this debate was already playing out in public. Just days ago, Elon Musk predicted Chinese AI labs would probably catch up to Anthropic’s flagship Fable 5 by Q1 2027, at least in terms of benchmark performance. Zhipu AI founder Tang Jie quickly pushed back, replying, “won’t take that long.” Musk then clarified his position, arguing that while China might match Anthropic on benchmarks by then, achieving the same level of “true usefulness” would be a much tougher milestone, crediting Anthropic’s focus on practical intelligence.

On benchmarks, yes, but as measured by true usefulness even Q1 would be very impressive.

Anthropic has rightly focused on maximizing useful intelligence, which does not show up in benchmarks, but definitely shows up in revenue.

— Elon Musk (@elonmusk) June 18, 2026

Now, The Wall Street Journal’s latest report gives Tang’s optimism a little more weight. Instead of talking about coding benchmarks, it suggests GLM-5.2 is already matching Anthropic’s Mythos at finding security vulnerabilities, arguably one of the most valuable real-world AI applications today. That doesn’t suddenly make China the leader in frontier AI, but one thing is becoming increasingly difficult to ignore: the AI race is no longer a comfortable lead for the United States.



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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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