News
WhatsApp Tests Unique Usernames To Hide Phone Numbers
The new feature lets users chat through handles, marking a shift in how Meta manages privacy.
WhatsApp is trialing a username system that lets people message without exposing their phone numbers — a bold move that could reshape privacy on the world’s largest messaging app.
Early versions for Android and iOS show users can set unique handles instead of numbers. WABetaInfo, which tracks WhatsApp updates, says Meta is checking for duplicates before a wider release that’s expected soon. The test appears in Android beta version 2.25.28.12, where users can already “reserve” their chosen names ahead of launch.
The change fits Meta’s push to move away from phone-based identity and tighten control over personal data. Users will be able to start chats or join groups using only a username, keeping their number hidden from strangers and spammers. Reports suggest the platform will also let users display only their handle when joining new groups — a move likely to appeal to businesses and communities managing large public channels.
Reports from several media outlets say group participants may soon appear under usernames only. In addition, an unnamed source familiar with the rollout said the aim is to make “interactions between individuals and businesses safer and more controlled”.
Also Read: Microsoft Tightens Windows 11 Setup To Enforce Online Accounts
Registration will still require a phone number, but beta testers can already reserve usernames. Each handle must include at least one letter and can use lowercase characters, numbers, periods, or underscores.
For WhatsApp’s two billion users, it’s a clear signal of the platform’s new stance: privacy is being rebuilt around identity, not contact lists. The update also brings the messaging service closer to rivals such as Telegram, which have long supported handle-based communication — underscoring how Meta is adapting its messaging products to modern privacy expectations.
News
ESET Bets On Specialized Security AI At 0.5% The Training Cost
ESET says NeoCortex can estimate an attacker’s next move, with a kill switch and human oversight built in to keep it from going rogue.
A sign-in anomaly, a suspicious process launch and an unusual connection may look harmless alone. Together, they can describe an intrusion that is hard for security to teams to piece together.
To solve that problem, ESET announced ESET NeoCortex on November 4, 2026: a specialized foundational AI model for cybersecurity. It powers ESET LiveCortex, available within the ESET PROTECT Platform, which connects fragmented security signals and turns them into actionable incidents.
Filtering is the main selling point, with LiveCortex processing billions of raw telemetry events daily, and just 0.00111% of them contributing to incidents presented to customers. The aim is less alert fatigue and more analyst time spent on threats that matter.
NeoCortex is built on world-model architecture, learning how digital environments behave and how events relate. ESET says that lets it reconstruct missing incident context, recognize similar past cases and estimate an attacker’s likely next step – what the company calls “minus-one-day defense,” a chance to intervene before the next stage unfolds. ESET points to Black October, the week leading up to October 25, 2026, when critical security issues affecting PHP, Linux, GitLab and other key systems demanded rapid, prioritized responses, as the kind of moment where that context matters.
ESET’s internal research also suggests a specialized model like NeoCortex can be trained at up to 200 times lower cost than a large general reasoning model, while delivering more accurate, defense-focused results. The company credits optimized training, a focus on cybersecurity vocabulary, lower computing requirements and privately owned hardware.
Also Read: Dubai Says Its Deepfake Detector Needs Just 7 Seconds Of Video
“AI is accelerating both cyberattacks and cyberdefenses. With ESET NeoCortex, we are applying our AI investment to develop specialized foundational cybersecurity intelligence that remains under our control and strengthens, rather than replaces, human expertise,” said Juraj Malcho, Chief Technology Officer at ESET.
As part of the design, NeoCortex forms part of a layered architecture combining specialized models, deterministic controls, correlation logic, validation, auditability and expert human oversight. Safeguards include restricted sandboxes, read-only tools, continuous monitoring, defined usage and token limits, a kill switch and human oversight of critical response decisions. The model is also developed and self-hosted on ESET’s own infrastructure, which the company says reduces exposure to shifts among third-party AI providers, including commercial and geopolitical ones.
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