Three years ago, OpenAI jumpstarted the generative AI revolution when it released ChatGPT, and the world hasn’t been the same since. Hundreds of billions of dollars have been invested in AI, OpenAI founder and CEO Sam Altman became the face of AI, and billion-dollar AI companies seem to be minted at will.

As an early investor in OpenAI, Microsoft has been changed as much as any company by the genAI revolution. The tech giant’s value has skyrocketed to between $3 trillion and $4 trillion depending on the day, and it’s become the premiere AI firm in the world.

But now all that may change. On December 1 Altman sent out a memo to OpenAI employees declaring a “Code Red” emergency and focusing all company efforts on improving ChatGPT. The reason? Google’s newly released Gemini 3 model beat the pants off GPT-5.1, the current version of the large language model (LLM) behind ChatGPT, in just about every benchmark test.

It’s clear the future will be dire for OpenAI if Gemini continues to best ChatGPT. Not so clear are the effects on Microsoft, which uses OpenAI’s GPT-4 and GPT-5 models to power its own  Copilot chatbot. To better understand what they might be, we’ll first take a look at how Google’s latest Gemini release stacks up against ChatGPT.

Battle of the LLMs

Analysts point to a variety of ways in which Gemini 3 bests GPT. Mayank Kejriwal, a principal scientist at the USC Information Sciences Institute, says Gemini 3 has seen the greatest leap in capability this year, while GPT and other LLMs saw only “incremental updates.”

Kejriwal told Business Insider that the latest version of Gemini is well ahead of GPT on the LMArena leaderboard, in which users rate the accuracy and comprehensiveness of chatbots in a number of arenas including text, text-to-image, and search. Gemini 3 is number 1 overall, while GPT-5.1 is far behind at number 6.

Google has released a wide variety of specific benchmarks that show how Gemini has surpassed GPT-5.1. Altman’s declaration of a Code Red in response indicates that this is not mere hype.

And Google immediately embedded Gemini 3 across its core products, including search. Sanchit Vir Gogia, chief analyst at Greyhound Research, said that integrating Gemini directly into Google Search is one of the most important shifts in the AI enterprise market in the last year.

“This is not an AI feature layered on top of search,” he told Computerworld. “It is a fundamental rewrite of the global information distribution engine that billions rely on every day. For enterprises, this marks a decisive moment where AI is no longer a separate capability but the default interpreter of user intent, workflow context, and knowledge retrieval.”

What does this mean for Microsoft?

It’s clear this is all bad news for OpenAI. But what does it mean for Microsoft?

For a start, the news about Google’s breakthrough isn’t as dangerous for Microsoft as it would have been if it had happened a year ago. Back then, Microsoft was almost completely dependent on OpenAI. But the company has taken big steps to augment and even replace GPT as its go-to genAI.

These intentions became clear when Microsoft hired prominent AI leader Mustafa Suleyman to head up its new AI division in March 2024. Suleyman is a co-founder and former head of Applied AI at the AI company DeepMind, which was bought by Google.

A year and a half later, Microsoft launched its first homegrown LLMs, which ultimately may augment or even replace GPT as Copilot’s brains. It also made a deal with OpenAI competitor Anthropic to power parts of Microsoft 365 Copilot, the enterprise version of the chatbot that integrates with Microsoft 365 apps. That deal fixes one of Copilot’s main problems — its Excel capabilities are exceedingly weak, while those of Anthropic’s Claude model are much better.

That’s just the beginning. Eventually, Microsoft may take a “best-of-breed” approach that relies on multiple LLMs, not just GPT, to power Copilot.

Suleyman recently announced a new direction for Microsoft’s AI plans that go well beyond today’s chatbots. He calls it “Humanist Superintelligence,” and it’s more than just an empty slogan. He says it will “solve real concrete problems and do it in such a way that it remains grounded and controllable. We are not building an ill-defined and ethereal superintelligence; we are building a practical technology explicitly designed only to serve humanity.”

In practical terms, that means not one-size-fits-all chatbots like ChatGPT and Gemini, but instead a series of AI-based technologies, each pointed at solving an important problem and aimed at bettering people’s lives. The first two to be rolled out will be for medicine and improving energy efficiency.

The Google enterprise threat

All that being said, Gemini’s emergence as the world’s premier chatbot does present potentially serious problems for Microsoft. Microsoft 365 Copilot, which requires an add-on subscription, hasn’t been adopted in enterprises the way the company had hoped. A year ago, Microsoft announced that almost 70% of Fortune 500 companies were using Microsoft 365 Copilot. But many of those companies were using it in pilot programs, not for enterprise-wide use.

It appears that may still be the case. Gartner has warned that 47% of IT leaders have no confidence or are not very confident in being able to manage security and access risk in Copilot. An MIT report, The GenAI Divide: State of AI in Business 2025, found that 95% of genAI pilots fail — and most enterprise genAI pilots are for Copilot.

If Gemini proves to be a big improvement over Copilot, enterprises may start turning to Google Workspace and abandoning Microsoft 365. That would have far more serious consequences for Microsoft than just lost revenue for one product. Once Google gains deep relationships with an increasing number of enterprises, it could supplant other Microsoft products in them as well, notably Azure. Google could then eventually overtake Microsoft as the world leader in AI.

The upshot

None of this is a done deal, of course. GenAI models typically leapfrog one another, so don’t be surprised if the next version of GPT — and therefore Copilot — will perform better than Gemini.

But it is the first time that Microsoft’s dominance in AI has been challenged. So it may well be time for Microsoft to announce its own Code Red.

Source:: Computer World

By Pranob Mehrotra The December 2025 update for the Pixel Watch 4 brings two new gestures to simplify one-handed use.
The post Your Pixel Watch 4 is getting two more gestures for easier one-handed use appeared first on Digital Trends.

Source:: Digital Trends

By Pranob Mehrotra Pebble’s comeback story just took an unexpected turn. After launching two new smartwatches earlier this year, the company today announced a new wearable that challenges what a smart ring is supposed to be. Unlike Samsung’s Galaxy Ring or smart rings from Oura, the Pebble Index 01 isn’t built for health and fitness tracking. Instead, its […] The post Pebble’s new smart ring helps you capture ideas, not fitness stats appeared first on Digital Trends.

Source:: Digital Trends

Google is deploying a second AI model to monitor its Gemini-powered Chrome browsing agent after acknowledging the agent could be tricked into taking unauthorized actions through prompt injection attacks.

“We’re introducing a user alignment critic where the agent’s actions are vetted by a separate model that is isolated from untrusted content,” the company said in a blog post about the addition. If the critic determines an action doesn’t match what the user asked for, it blocks the action, Google said.

“The primary new threat facing all agentic browsers is indirect prompt injection,” Chrome security engineer Nathan Parker wrote in the post, describing a situation where an agent is prompted to process information that then seeks to modify the initial prompt.

The Gemini-powered browsing agent, launched in September and currently in preview, can navigate websites, click buttons, and fill forms while users are logged into email, banking, and corporate systems. Malicious instructions hidden in web pages, iframes, or user-generated content could “cause the agent to take unwanted actions such as initiating financial transactions or exfiltrating sensitive data,” Parker wrote.

That’s where the user alignment critic comes in: The second model reviews each proposed action before Chrome executes it, acting as what Parker called “a powerful, extra layer of defense against both goal-hijacking and data exfiltration.”

Why prompt injection is hard to stop

Prompt injection has emerged as the top vulnerability in AI systems over the past year. OWASP found it in 73% of production AI deployments it assessed in 2024, ranking it the number one risk in its list of threats to large language model applications.

The UK’s National Cyber Security Centre warned Sunday that prompt injection attacks may never be fully mitigated because LLMs can’t reliably distinguish between instructions and data. The agency called it a “confused deputy” vulnerability, where a trusted system is tricked into performing actions on behalf of an untrusted party.

Researchers have already demonstrated the threat. In January, attackers embedded instructions in a document that caused an enterprise AI system to leak business intelligence and disable its own safety filters. Security firm AppOmni disclosed last month that ServiceNow’s AI agents could be manipulated through instructions hidden in form fields, with one agent recruiting others to perform unauthorized actions.

For Chrome, the stakes are particularly high. A compromised browsing agent would have the user’s full privileges on any logged-in site, potentially bypassing the browser’s site isolation protections that normally prevent websites from accessing each other’s data.

Google’s two-model defense

To address these risks, Google’s solution splits the work between two AI models. The main Gemini model reads web content and decides what actions to take. The user alignment critic sees only metadata about proposed actions, not the web content that might contain malicious instructions.

“This component is architected to see only metadata about the proposed action and not any unfiltered untrustworthy web content, thus ensuring it cannot be poisoned directly from the web,” Parker wrote in the blog. When the critic rejects an action, it provides feedback to the planning model to reformulate its approach.

The architecture is based on existing security research, drawing from what’s known as the dual-LLM pattern and CaMeL research from Google DeepMind, according to the blog post.

Google is also limiting which websites the agent can interact with through what it calls “origin sets.” The system maintains lists of sites the agent can read from and sites where it can take actions like clicking or typing. A gating function, isolated from untrusted content, determines which sites are relevant to each task.

The company acknowledged this first implementation is basic. “We will tune the gating functions and other aspects of this system to reduce unnecessary friction while improving security,” Parker wrote.

Beyond the user alignment critic and origin controls, Chrome will require user confirmation before the browsing agent navigates to banking or medical sites, uses saved passwords through Google Password Manager, or completes purchases, according to the blog post. The browsing agent has no direct access to stored passwords.

A classifier runs in parallel checking for prompt injection attempts as the agent works. Google has built automated red-teaming systems generating malicious test sites, prioritizing attacks delivered through user-generated content on social media and advertising networks.

Grappling with an unsolved problem

The prompt injection challenge isn’t unique to Chrome. OpenAI has called it “a frontier, challenging research problem” for its ChatGPT agent features and expects attackers to invest significant resources in these techniques.

Gartner has gone one step further and advised enterprises to block AI browsers in their systems. The research firm warned that AI-powered browsing agents could expose corporate data and credentials to prompt injection attacks.

The NCSC took a similar position, urging organizations to assume AI systems will be attacked and to limit their access and privileges accordingly. The agency said organizations should manage risk through design rather than expecting technical fixes to eliminate the problem.

Chrome’s agent features are optional and remain in preview, the blog post said.

Source:: Computer World

By Pranob Mehrotra Google has released a massive update for its AI-powered mood board app, Mixboard, which includes a new feature that can turn your idea dump into a crisp presentation.
The post Google’s AI mood board can now turn your idea dump into a slick presentation appeared first on Digital Trends.

Source:: Digital Trends

By Pranob Mehrotra Doppl, Google’s AI-powered virtual try-on app, now has a shoppable discovery feed that offers outfit recommendations with direct links to merchants.
The post Google’s virtual try-on app now helps you discover and shop outfits tailored to you appeared first on Digital Trends.

Source:: Digital Trends

By Deepti Pathak BGMI is one of the most popular battle royale games because of its exciting gameplay and…
The post BGMI Redeem Codes for December 9 appeared first on Fossbytes.

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By Moinak Pal A new Stanford wearable enhances real-world sounds to boost focus and mindfulness. Early studies show improved attention and potential benefits for ADHD and anxiety management.
The post This clever wearable wants to keep you focused and it could help with ADHD as well appeared first on Digital Trends.

Source:: Digital Trends

By Alexandru Stan Tekpon has acquired 100% of the TNW media and events brands, which cover and convene the European technology ecosystem, from the FT. The transaction is Tekpon’s largest investment in media and events so far. It broadens the company’s reach across SaaS and AI and strengthens its role in the global innovation landscape. TNW’s brand and editorial standards will be maintained, while its events and digital platforms will be integrated into Tekpon’s wider strategy. The FT will continue to own and operate TNW Spaces, Amsterdam’s dynamic tech hub, offering private offices and coworking spaces that support a thriving community of startups,…This story continues at The Next Web

Source:: The Next Web

By Omair Khaliq Sultan If AirPods Max have always felt just a bit too expensive, this is the kind of discount that changes the equation. The updated AirPods Max (USB-C) are going for $429.99, which is $120 off the usual $549.99 price. You’re getting Apple’s top over-ear headphones with upgraded USB-C charging, lossless listening support, and all the ecosystem […] The post Apple’s AirPods Max USB-C just got a rare $120 discount appeared first on Digital Trends.

Source:: Digital Trends

AI browsers including Perplexity Comet and OpenAI’s ChatGPT Atlas present security risks that cannot be adequately mitigated, and enterprises should prevent employees using them, according to Gartner.

“Gartner strongly recommends that organizations block all AI browsers for the foreseeable future because of the cybersecurity risks,” analysts Dennis Xu, Evgeny Mirolyubov, and John Watts wrote in a research note last week. They made their recommendation based on risks they had already identified, “and other potential risks that are yet to be discovered, given this is a very nascent technology.”

The warning is timely, as AI browsers are already gaining a foothold in the enterprise: 27.7% of organizations already have at least one user with Atlas installed, with some enterprises seeing up to 10% of employees actively using the browser,  cybersecurity firm Cyberhaven said in October. It found adoption rates highest in the technology industry (67%), pharmaceuticals (50%), and finance (40%), all sectors with heightened security requirements.

ChatGPT Atlas, launched on October 21, saw 62 times more corporate downloads than Perplexity Comet, which was released July 9, according to Cyberhaven. The launch of Atlas also sparked renewed interest in AI browsers overall, with Comet downloads surging sixfold during the same week.

But concerns were raised immediately after the launch of ChatGPT Atlas about the threat posed by AI browsers, with analysts pointing to prompt injection vulnerabilities and data security concerns.

Sensitive data at risk

The reason AI browsers are of concern is that when they send active web content, browsing history, and open tab contents to the cloud for analysis, enterprises lose control of their data.

Perplexity’s documentation, for example, warns that “Comet may process some local data using Perplexity’s servers to fulfill your queries. This means Comet reads context on the requested page (such as text and email) in order to accomplish the task requested.”

Mirolyubov, senior director analyst at Gartner, said, “The real issue is that the loss of sensitive data to AI services can be irreversible and untraceable. Organizations may never recover lost data.”

It’s not just where the browsers send your data for processing that is a concern; it’s what they do as a result : “Erroneous agentic transactions raise accountability concerns in case of expensive errors,” he said.

Traditional controls inadequate

AI browsers can autonomously navigate websites, fill out forms, and complete transactions while authenticated to web resources. As he and his colleagues wrote in their report, this makes the AI browsers susceptible to new cybersecurity risks, “such as indirect prompt-injection-induced rogue agent actions, inaccurate reasoning-driven erroneous agent actions, and further loss and abuse of credentials if the AI browser is deceived into autonomously navigating to a phishing website.”

“Traditional controls are inadequate for the new risks introduced by AI browsers, and solutions are only beginning to emerge,” Mirolyubov said. “A major gap exists in inspecting multi-modal communications with browsers, including voice commands to AI browsers.”

Prompt injection remains a particular concern, OpenAI CISO Dane Stuckey acknowledged in a post to X, formerly Twitter, the day after ChatGPT Atlas’s launch: “Prompt injection remains a frontier, unsolved security problem, and our adversaries will spend significant time and resources to find ways to make ChatGPT agents fall for these attacks.”

Discovered vulnerabilities highlight immaturity

Beyond theoretical risks, concrete security flaws have emerged in both major AI browsers. Days after ChatGPT Atlas launched, researchers discovered it stores OAuth tokens unencrypted with overly permissive file settings on macOS, potentially allowing unauthorized access to user accounts. The vulnerability was documented by security research group Teamwin on October 27.

OpenAI had not released a patch as of October 31, when Gartner completed its research.

Separately, cybersecurity firm LayerX Security reported in August the discovery of a vulnerability in Comet called “CometJacking” that could potentially exfiltrate user data to attacker-controlled servers.

OpenAI and Perplexity did not immediately respond to requests for comment.

Years, not months, to mature

The discovered vulnerabilities highlight broader concerns about the maturity of AI browser technology. “Security and privacy must become core design principles rather than afterthoughts,” Mirolyubov said. AI browser vendors must incorporate enterprise-grade cybersecurity controls from the outset and provide greater transparency regarding data flows and agentic decisions, he said.

Emerging AI usage control solutions will likely take “a matter of years rather than months” to mature, he said. “Eliminating all risks is unlikely — erroneous actions by AI agents will remain a concern. Organizations with low risk tolerance may need to block AI browsers for the longer term.”

Organizations with higher risk tolerance that want to experiment should limit pilots to small groups tackling low-risk use cases that are easy to verify and roll back, the Gartner report said. Users must “always closely monitor how the AI browser autonomously navigates when interacting with web resources.”

For now, Gartner said, organizations should block AI browser installations using existing network and endpoint security controls and review their AI policies to ensure that broad use of AI browsers is prohibited.

“Today, most cybersecurity teams choose to block AI browsers, delaying adoption until risks are better understood and controls are more mature,” Mirolyubov said.

Source:: Computer World

By Deepti Pathak For the first time, YouTube is offering a complete Recap that shows your full year of…
The post YouTube Recap 2025: Find Out What You Watched the Most This Year appeared first on Fossbytes.

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By Hisan Kidwai OnePlus has always been a really decent tablet maker, combining its smooth UI and performance into…
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For decades, macOS has been admired for stability and security — traits inherited from the BSD Unix underpinnings of Apple’s operating systems. Yet these same foundations now create friction for IT leaders trying to marry Apple’s strong local authentication model with the cloud-based identity providers (IdPs) that support single sign-on (SSO) and other key features of modern enterprise computing.

“Platform SSO is Apple’s solution to bridge the gap between local desktop authentication and SSO for cloud apps,” said Weldon Dodd, a distinguished engineer at Iru (formerly Kandji), which sells identity and endpoint management software. Introduced in 2022, Platform SSO (PSSO) aims to simplify the login experience by allowing enterprise users to authenticate once on their Mac and then be automatically signed into corporate cloud apps and websites — a leap toward the kind of unified experience that Windows Hello and Azure AD users enjoy.

Until now, Macs were first set up with a local user account and then registered with PSSO, but “this year with macOS Tahoe 26, Platform SSO authentication will be available during Setup Assistant and even at the pre-boot FileVault unlock screen,” Dodd said. “These are really important changes that enable new zero-touch workflows for enterprise customers as they provision devices to their teammates.”

Those changes, announced at WWDC 2025, allow IT to configure devices so that when a user is setting up a new Mac, they first authenticate with the corporate identity provider, which enrolls them into device management and potentially their Managed Apple Account. Then a local account is created and the password synced with the IdP.

As Computerworld columnist Jonny Evans explained, “The result is that a user can receive a Mac, start it up, log in with their provisioned ID, and watch as the Mac is configured, device management put in place, and approved apps downloaded to their machine.”

But PSSO adoption has been uneven. “The biggest challenge we hear from IT teams is the limited identity-provider support for Platform SSO,” said Jason Dettbarn, founder and CTO of Addigy, an Apple Mobile Device Management (MDM) vendor. “Organizations want to take advantage of Apple’s native authentication, but their IdP either doesn’t support it yet or charges extra for the capability.”

Even when support exists, Dettbarn added, “it can conflict with existing security policies, forcing teams to choose between maintaining their standards or adopting Apple’s framework.”

That tension — between Apple’s elegant consumer-grade experience and enterprise-grade security standards — lies at the heart of the identity problem for many IT departments.

Bridging the local/cloud gap

At its core, PSSO lets macOS link a local user account with an organization’s cloud directory through an extension provided by the IdP. Once authenticated, the user gains seamless access to managed apps without re-entering credentials. In theory, this eliminates password fatigue and improves compliance by enforcing corporate policies at login.

In practice, integration depends on the maturity of each IdP’s implementation. “PSSO still relies on the IdP vendors to do their part to make the end-to-end solution work,” Dodd said. “Microsoft Entra ID and Okta have announced their support for the new PSSO extensions in Tahoe, but other vendors have been slow to take Apple up on implementation.”

That lag creates a patchwork reality: a small subset of organizations with the right combination of tools can achieve seamless login to both device and apps, while others juggle half-working connectors and frustrated users.

To bridge the gap, management-tool providers like Iru and Addigy offer their own layers of integration. Iru’s Passport feature, for instance, keeps local macOS and cloud passwords in sync, mitigating one of the most common help-desk issues — password resets.

“With the new improvements in PSSO, Apple has closed that gap significantly,” Dodd noted, “but we’ve still got work to do.”

Addigy’s approach, meanwhile, emphasizes flexibility. “We’re one of the few MDM providers that includes its login solution at no additional cost,” Dettbarn said. “That gives us the freedom to recommend whichever approach — native or third-party — delivers the most seamless and secure experience.”

Safer device sharing

Another Apple initiative introduced at WWDC 2025, Authenticated Guest Mode, aims to help organizations that rely on shared or temporary devices — common in retail, education, and healthcare. The feature allows users to sign into a managed Mac with their cloud IdP credentials, creating a temporary, secure session that vanishes at logout.

“Authenticated Guest Mode looks really useful for environments that need ephemeral accounts protected by cloud IdP credentials,” said Dodd. “We’re looking into it, but we have yet to see the full end-to-end workflow available from Apple.”

For IT administrators, ephemeral accounts could finally close a long-standing security hole. Today, shared devices often rely on generic local logins or complex scripts — both prone to misconfiguration — to enforce session isolation. Authenticated Guest Mode promises an auditable, cloud-linked process that reduces risk.

Still, questions remain about policy enforcement, network onboarding, and integration with MDM workflows. Until those are answered, most organizations will likely experiment in sandboxed environments before full deployment.

Managing Macs at enterprise scale

The Six Colors 2025 Apple in the Enterprise Report Card ranked “macOS identity management” as the second-lowest-scoring category among enterprise Apple device administrators. That result reflects both lingering technical gaps and the operational complexity of supporting Apple alongside Windows and sometimes ChromeOS.

It’s worth noting that the 2025 report card predates Apple’s WWDC25 announcements. We’ll know next April when the 2026 report card is released if the changes to PSSO and introduction of Authenticated Guest Mode improve IT administrators’ opinion of macOS identity management.

Dodd expects they will. “The ability to use cloud IdP credentials at setup will be a great addition to zero-touch enrollment flows,” he said. “And our customers will love that the same PSSO authentication is available at pre-boot so there will never be a disconnect between the password used to unlock disk encryption and sign in to the local account.”

Those kinds of improvements, though technical, have big implications for how enterprises deploy and secure Macs. Zero-touch enrollment — ordering a Mac that auto-registers with the corporate IdP the moment it’s powered on — is the holy grail of Apple fleet management. It reduces both administrative overhead and exposure from unprotected endpoints.

While Apple’s incremental advancements in macOS Tahoe bring optimism, they also raise the bar for ecosystem partners. Both Iru and Addigy plan to support the new PSSO and Authenticated Guest Mode capabilities, but they say full interoperability depends on Apple maintaining stable APIs and documentation — a perennial complaint among enterprise developers.

And even with new tools, few IT leaders expect overnight transformation. Dodd acknowledged that “macOS still relies on a username and password for authentication, so there can be an impedance mismatch with more modern, phishing-resistant, passwordless methods.” Once logged in, however, “the experience of using passkeys with macOS is quite good,” he said, adding that “every enterprise should be looking at passkeys to level up security for critical apps and resources.”

That sentiment echoes a broader industry movement toward adopting passkeys — passwordless sign-ins based on WebAuthn standards — supported by Apple, Google, and Microsoft alike. “Enterprise IT is eager to figure out how to adopt passkeys at scale and manage them in a way that realizes the benefits of increased security and phishing resistance, while still providing control for IT and ease of use for end users,” said Dodd. But he warned that scaling passkeys across thousands of users and devices requires new management models.

A major decision facing IT leaders today is whether to rely more on Apple’s native features or to double down on specialized third-party tooling. For both vendors interviewed, the answer lies somewhere in between.

The “buy-and-build” coexistence reflects enterprise reality. Companies rarely swap out proven identity stacks overnight; they evolve them incrementally, keeping a foot in both worlds until confidence in Apple’s native approach matures.

Looking ahead, Dodd envisions a model where the macOS account password behaves more like an iPhone PIN. “Once unlocked with the PIN or biometrics, making passkeys the center of further auth requests seems like the right direction,” he said. “But there are so many places where the Unix foundations of macOS require username and password that it might be some time before that future becomes realistic.”

Dodd and Dettbarn agreed that the next few years will be about coexistence: blending traditional password models with emerging passkey and biometric systems, and ensuring everything ties neatly into corporate IdPs.

Meanwhile, Apple is sending clear signals that it takes enterprise identity seriously. The company’s new Platform SSO and Authenticated Guest Mode initiatives, plus the steady march toward passkeys, suggest that Cupertino recognizes how critical identity has become to enterprise trust. Still, in classic Apple fashion, progress comes on Apple’s timeline, leaving IT teams to fill in the gaps.

Strategies for IT leaders

Until the dust settles, what can IT departments do to reduce identity headaches across large Mac deployments? Addigy’s Dettbarn offered these tips:

Establish robust testing pipelines. “For large Apple fleet deployments, we recommend establishing separate testing environments or policies to eliminate the risk of accidental production deployments,” he said.

Adopt staged deployments. “Start with a controlled rollout — first to test devices, then to your IT department, and finally deploy in staged groups to reduce risk,” Dettbarn advised.

Invest in user education. Communication is essential, he stressed. “End users need to know what to expect.”

Stay vendor-agnostic. As IdP support for PSSO matures, organizations should avoid locking into proprietary connectors. “IT should continuously evaluate current solutions to identify opportunities for improved security and better user experiences,” he said.

Monitor metrics. Addigy measures success “across both the admin and end-user experience,” Dettbarn said, citing ease of implementation, usability, reduced support tickets, stronger compliance, and faster onboarding as key indicators that identity solutions are working effectively.

Enterprises that follow these best practices can position themselves to take advantage of Apple’s identity enhancements as they arrive — without compromising stability in the meantime.

Source:: Computer World

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The Signalgate scandal that enveloped US Secretary of Defense Pete Hegseth in March appears to be symptomatic of a wider lax attitude towards the use of non-approved messaging apps by officials and employees, a Senate Committee has concluded.

In March, the US Senate Committee on Armed Services set out to examine issues raised by the Signalgate incident: the need to clarify the existing rules on using “non-controlled” apps, and looking at whether Defense Secretary Hegseth adhered to them in his use of Signal, and whether his actions were evidence of a wider culture of insecure app usage within the Department of Defense (DoD).

This week’s dual reports have come back with a mixed assessment of these points. Broadly, what Hegseth was accused of doing – communicating sensitive information using a third-party messaging app – appears to have been happening at the DoD in less serious contexts since at least 2020.

This mirrors issues familiar to enterprises: unsanctioned or unmanaged messaging apps, including ones touting end-to-end encryption (E2EE) security, quickly become an IT backchannel that can invisibly undermine carefully-assembled security, compliance, and data retention policies.

Shadow communications

The first report, an assessment of the Defense Secretary’s use of the Signal app to communicate with senior colleagues in advance of a military operation against Yemen on March 15, is used to illustrate the point. It confirms the widely reported fact that two hours before the raid, Hegseth revealed details of the operation to a Signal group of 19 people, including a journalist who had been added to it in error.

In doing so, the report agrees he violated security policies by sending sensitive information from a personal device, and using the non-approved Signal app in a way that revealed important operational details in advance of the strike. The report ducks the issue of whether this information was classified at the time it was sent, noting that Hegseth was senior enough to determine this for himself.

The second background report has uncovered evidence of a more general culture of shadow communications in the DoD, including widespread use of video-conferencing apps during the Covid 19 pandemic.  

The evidence gathered is sparse and partly redacted, making it difficult to assess the seriousness of any breaches. Because the scope of its remit was limited to the evidence from previous audits, one of the committee’s recommendations is to undertake a more comprehensive assessment of unsanctioned app usage inside the DoD. There’s also a question mark around how old audits analyzed by a Senate committee could accurately measure something that, by its nature, is hidden and only recorded on personal devices.

Nevertheless, the report says it is certain that Hegseth’s actions were not an isolated example, noting that staff had “used non-DoD-controlled electronic messaging systems for a variety of reasons. For example, some personnel used them because of the systems’ perceived appearance of security. As a result, DoD personnel increased the risk of exposing sensitive DoD information to our adversaries and did not comply with the legal obligation to retain and preserve official records.”

In short, while there was no evidence that unsanctioned app use is routine or normalized, it is likely that enough staff are using them to make a serious breach possible at some point. The report concludes that one of the reasons staff have taken to these messaging apps was that they lack convenient alternatives. It recommends developing approved apps to remove this need, implementing a training program to ensure existing communication regulations are complied with, and limiting the authority to use messaging apps to senior staff, in specific circumstances.

What’s surprising about this is that it has taken a major political row at government level to raise an issue that enterprise CISOs have been grappling with for years: the effects of BYOD, shadow IT (and now shadow AI), and unsanctioned apps that creep into organizations without anyone realizing it.

Over the last two decades, the rise of mobile devices, the cloud, and apps has radically de-centralized IT in ways that top-down management models struggle to control. Meanwhile, nothing has changed; the Signal app at the center of this scandal remains hugely popular on both sides of the political divide, despite the appearance of additional issues with the technology. 

This article originally appeared on CSOonline.

Source:: Computer World

The Signalgate scandal that enveloped US Secretary of Defense Pete Hegseth in March appears to be symptomatic of a wider lax attitude towards the use of non-approved messaging apps by officials and employees, a Senate Committee has concluded.

In March, the US Senate Committee on Armed Services set out to examine issues raised by the Signalgate incident: the need to clarify the existing rules on using “non-controlled” apps, and looking at whether Defense Secretary Hegseth adhered to them in his use of Signal, and whether his actions were evidence of a wider culture of insecure app usage within the Department of Defense (DoD).

This week’s dual reports have come back with a mixed assessment of these points. Broadly, what Hegseth was accused of doing – communicating sensitive information using a third-party messaging app – appears to have been happening at the DoD in less serious contexts since at least 2020.

This mirrors issues familiar to enterprises: unsanctioned or unmanaged messaging apps, including ones touting end-to-end encryption (E2EE) security, quickly become an IT backchannel that can invisibly undermine carefully-assembled security, compliance, and data retention policies.

Shadow communications

The first report, an assessment of the Defense Secretary’s use of the Signal app to communicate with senior colleagues in advance of a military operation against Yemen on March 15, is used to illustrate the point. It confirms the widely reported fact that two hours before the raid, Hegseth revealed details of the operation to a Signal group of 19 people, including a journalist who had been added to it in error.

In doing so, the report agrees he violated security policies by sending sensitive information from a personal device, and using the non-approved Signal app in a way that revealed important operational details in advance of the strike. The report ducks the issue of whether this information was classified at the time it was sent, noting that Hegseth was senior enough to determine this for himself.

The second background report has uncovered evidence of a more general culture of shadow communications in the DoD, including widespread use of video-conferencing apps during the Covid 19 pandemic.  

The evidence gathered is sparse and partly redacted, making it difficult to assess the seriousness of any breaches. Because the scope of its remit was limited to the evidence from previous audits, one of the committee’s recommendations is to undertake a more comprehensive assessment of unsanctioned app usage inside the DoD. There’s also a question mark around how old audits analyzed by a Senate committee could accurately measure something that, by its nature, is hidden and only recorded on personal devices.

Nevertheless, the report says it is certain that Hegseth’s actions were not an isolated example, noting that staff had “used non-DoD-controlled electronic messaging systems for a variety of reasons. For example, some personnel used them because of the systems’ perceived appearance of security. As a result, DoD personnel increased the risk of exposing sensitive DoD information to our adversaries and did not comply with the legal obligation to retain and preserve official records.”

In short, while there was no evidence that unsanctioned app use is routine or normalized, it is likely that enough staff are using them to make a serious breach possible at some point. The report concludes that one of the reasons staff have taken to these messaging apps was that they lack convenient alternatives. It recommends developing approved apps to remove this need, implementing a training program to ensure existing communication regulations are complied with, and limiting the authority to use messaging apps to senior staff, in specific circumstances.

What’s surprising about this is that it has taken a major political row at government level to raise an issue that enterprise CISOs have been grappling with for years: the effects of BYOD, shadow IT (and now shadow AI), and unsanctioned apps that creep into organizations without anyone realizing it.

Over the last two decades, the rise of mobile devices, the cloud, and apps has radically de-centralized IT in ways that top-down management models struggle to control. Meanwhile, nothing has changed; the Signal app at the center of this scandal remains hugely popular on both sides of the political divide, despite the appearance of additional issues with the technology. 

This article originally appeared on CSOonline.

Source:: Computer World

Music giant Warner Music Group announced last week that it had reached a “groundbreaking partnership agreement” with Suno, the AI startup at the forefront of AI-generated music it had sued for copyright infringement. After settling that fight, Warner Music signed new licensing models that allow Suno users to continue creating “music.”

Similar agreements have previously been inked with competitor Udio, and it seems highly likely that the other music giants will reach similar agreements. Whether it’s because record companies don’t want to risk making the “Napster mistake” again or they truly believe this is the future, AI services are here to stay.

Suno is undeniably popular. According to the company’s own figures, according to Billboard, users generate music equivalent to Spotify’s entire catalog every fortnight. The service has an admittedly high “wow” factor when tested. The results are impressive, technically speaking. But because it’s music, the question remains: who will listen to this?

I can understand the users, the people finding ways to express themselves creatively, even if it’s via prompts. If you think it’s fun to create AI-generated music, do it. Similarly, playing with Nano Banana for pictures, Sora for videos, or letting Chat GPT write a bedtime story is harmless. But just as no one wants to read an AI-generated book or be drowned in AI-generated images and clips, I don’t think music listeners are as keen on this.

If the services were intended solely for the creators themselves, the problem would be smaller. But unfortunately, the ambitions do not stop there. In its pitch deck to investors, Suno highlights the AI-created band Velvet Sundown, which became a talking point this summer: “Suno songs go viral outside the platform.”

And it’s that dream, to go viral or make a buck, that’s driving rivers of AI music to fill up streaming platforms. Spotify’s French competitor Deezer reports that more than 50,000 AI-generated songs are uploaded to the platform every day. And Spotify itself announced in September that it had removed more than 75 million songs that were considered pure AI garbage.

Sometimes it works. In addition to the aforementioned Velvet Sundown, country artist Breaking Rust recently gained attention when their song “Walk My Walk” topped Billboard’s country download chart and made it onto Spotify’s viral chart. (I hope these are the exceptions that prove the rule.)

A couple of weeks ago, I scrolled into a drama on Tiktok — as one tends to do on that platform — about the unknown artist Haven, whose song “I Run” topped Tiktok’s list of most popular songs. It had been revealed that the song was AI-generated and people were going crazy. Not because the song was bad, but because they felt cheated. Because it felt inauthentic. Because the music suddenly lost a lot of its value.

Authenticity should not be underestimated when it comes to music and other media. It may be that 97% of people can’t tell the difference between AI-generated and human-created music. But the feeling of being deceived is the same, whether it is disinformation in text and video or “good songs” created by AI. Artistic works also tend to be about an emotional connection to the work or to the creator, something I think a clear “AI labeling” of music would effectively kill.

Is there no use for AI-generated music then? Well, perhaps where that connection and authenticity doesn’t matter. A company like Sweden’s Epidemic Sound should be a little concerned. It licenses background music, what used to be called elevator music or muzak, for sound design in areas such as television and advertising. For those uses, AI music could be a cost-effective solution, just as AI-generated content is popular with marketers.

Haven had her song taken down from streaming platforms, and has now had to record a new version with real vocals instead of AI-generated ones. The singer whose voice was imitated, Jorja Smith, has demanded royalties through her record label.

How was the AI song made? With Suno. Maybe something for the next pitch deck.

This column is taken from CS Weekly, a personalized newsletter with reading tips, link tips and analysis sent directly from editor-in-chief Marcus Jerräng’s desk. Would you like to receive the newsletter on Fridays? Sign up for a free subscription here.

Source:: Computer World

By Adarsh Verma There’s nothing more exciting than planning a trip overseas — picking the perfect outfits, daydreaming about…
The post How To Avoid Roaming Charges When Travelling? appeared first on Fossbytes.

Source:: Fossbytes

By Deepti Pathak Buying clothes online is a gamble, because you can’t visualise how it’ll look on your body….
The post Google’s New Virtual Try-On Tool Lets You Try Clothes Using Just a Photo appeared first on Fossbytes.

Source:: Fossbytes