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By Omair Khaliq Sultan This post is brought to you in paid partnership with AUVON. If muscle tension is something you deal with regularly—whether it’s from long hours at a desk or tough workouts—a compact TENS unit can be one of the easiest ways to get relief at home. Right now, this AUVON dual-channel TENS muscle stimulator drops to […] The post Get this dual-channel TENS muscle stimulator for just $22.79 appeared first on Digital Trends.

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Microsoft has given system administrators until 2034 to stop using WINS (Windows Internet Name Service) NetBIOS name resolution technology in their networks — but even nine years may not be enough notice for some: WINS is very much still in use, supporting a niche range of difficult-to-replace legacy systems.

WINS dates from Windows NT in 1994 and has long since been displaced by the more modern Domain Name System (DNS). It was deprecated in 2021 to coincide with the appearance of Windows Server 2022. This meant it would be supported but no longer developed, a clear signal that the clock was ticking.

Now, Microsoft has said, the last operating system to support WINS will be Windows Server 2025. That’s what determines the nine-year final migration deadline — the lifespan of Windows Server 2025 on the Long-Term Servicing Channel (LTSC).

“Organizations using WINS are strongly encouraged to migrate to modern DNS-based name resolution solutions,” the company said, perhaps stating the obvious, in a Windows Message Center advisory in early November.

According to Microsoft, the timescale is generous. “Our goal is to make planning and migrations as predictable and low-stress as possible. With advanced notice and a support runway, organizations can confidently modernize their environments at their own pace,” it said.

Cutting out WINS

Future versions of Windows without support for WINS will lose the WINS Server role and associated binaries, the WINS Microsoft Management Console (MMC) snap-in, and WINS automation APIs and related management interfaces, the company added.

WINS migration is yet another legacy issue inherited from the creative ferment of computer networking in the 1980s and 1990s. That era needed solutions to lots of networking problems in a hurry, especially how to turn a desktop PC operating system such as DOS or Windows into a practical server platform.

WINS solved an important challenge: how to connect the names used to identify computers using the 1980s’ NetBIOS network naming system with modern IP addresses. DNS, a hierarchical system that worked for Internet as well as network addresses, had rendered NetBIOS obsolete. But both ended up co-existing, examples of how the industry delivered more than one answer to the same problem.

Today, the arguments for getting rid of WINS extend beyond its obsolescence. It is also a security risk. In 2017, Fortinet’s FortiGuard Labs discovered a WINS Server remote memory corruption vulnerability in Windows Server 2008, 2012, and 2016.

Microsoft’s reply to Fortinet made interesting reading: “A fix would require a complete overhaul of the code to be considered comprehensive. The functionality provided by WINS was replaced by DNS and Microsoft has advised customers to migrate away from it.”

In short, Microsoft had no plans to patch the issue. Its solution was that customers migrate away from WINS, a process it has since become clear could still be ongoing for some customers into the 2030s.

Why WINS is still in use

Organizations still using WINS are likely to fall into one of two categories: those using it to support old technologies with long lifecycles such as operational technology (OT) systems, and those that have simply half-forgotten that they are still using it.

“For OT stacks built around WINS/NetBIOS, replacing them isn’t trivial because changing name resolution touches safety‑critical systems and bespoke integrations,” said Kieran Bhardwaj, head of security engineering at UK cyber security consultancy Bridewell, which specializes in advising on critical infrastructure.

“Legacy technologies persist because some niche systems like industrial/OT environments are engineered for multi‑decade lifecycles. Many control systems are architecturally fixed and can’t be re‑platformed,” he said. “It’s also hard for Microsoft: WINS sits deep in the networking stack which means removing a once‑core component demands exhaustive regression to avoid unintended breakage.”

Equally, according to William Wright of pen-testing company Closed Door Security, WINS was still running on some networks for the same reason that many legacy technologies overstay their usefulness: migration apathy.

“Most organizations running WINS today probably aren’t actively using it for anything critical. They’ve just never had a compelling reason to turn it off,” he said. “It’s been quietly replicating in the background, consuming minimal resources, causing no obvious problems. That’s the nature of legacy infrastructure: It persists not because it’s needed, but because removing it requires effort and carries risk, while leaving it alone is free,” said Wright.

WINS is a security risk

WINS had major design limitations that made it a security risk, said Wright. “WINS has no mechanism to verify the legitimacy of name registrations, which makes it vulnerable to spoofing attacks,” said Wright.

“An attacker on the network can register malicious entries, including Web Proxy Auto-Discovery (WPAD) records to intercept web traffic, or redirect connections to systems they control. It’s a straightforward path for lateral movement,” he said.

Finding WINS still turned on inside a network was a godsend to hackers using open-source tools such as Responder to conduct name resolution poisoning attacks against legacy Windows protocols such as Link-Local Multicast Name Resolution (LLMNR) and the NetBIOS Name Service (NBT-NS), Wright added.

Worse, the presence of WINS often indicated that a target was using other vulnerable legacy protocols. “Systems often fall back to NetBIOS broadcast queries when WINS isn’t available, which are spoofable on local networks. This is exactly what tools like Responder exploit, and it remains a common technique in penetration testing and real-world attacks alike.”

Network inventory

Organizations looking to rip WINS out should start with an inventory to find out where it is being used, Bhardwaj said: “Many organizations don’t realize a legacy asset still relies on WINS, so proactively inventory older segments and OT/ICS networks and verify resolution paths before the next upgrade window.”

“The trade-off is that customers still using WINS must put in the work to move to DNS by auditing dependencies, modernizing or isolating legacy workloads, and implementing DNS. But the payoff is a simpler, more secure platform.

In the end, even the brightest and best-performing technologies will one day be legacy. Migrating from WINS is a test of how well organizations are dealing with this wider problem. “There’s way too much legacy that is unused and that presents an attack surface for no reason,” said Bhardwaj.

Source:: Computer World

By Gareth Beavis We’re rounding up all the early Black Friday deals to help you make the right choice when it comes to saving.
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Download the December 2025 issue of the Enterprise Spotlight from the editors of CIO, Computerworld, CSO, InfoWorld, and Network World.

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By Deepti Pathak If you’re a fan of the Blue Lock anime series like me, then Roblox’s Meta Lock…
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Even as it prepares to further diversify its iPhone range, Apple is about to regain the smartphone crown from Samsung, according to analysts from Counterpoint. “Apple is set to dethrone Samsung in shipments for the first time in 14 years and will maintain the top spot through 2029,” Counterpoint said, noting that global smartphone sales are expected to increase 3.3% this year, mainly driven by strong performances from Apple. iPhone shipments should be up 10% year-on-year, they also said, for a global share of 19.4% in 2025. 

There’s something a little poetic about this, as the leadership position is one Apple slowly lost after the introduction of the iPhone 4S, which appeared just nine days after the death of Steve Jobs. (This led to some calling that iPhone the iPhone S, “for Steve.”) He’d probably be happy iPhone has now regained leadership against a platform he once complained was “stolen.”  

The analysts also shared several reflections valuable to any Apple or industry watcher. 

How did we get here?

In part, Apple’s ascendance owes a little of its existence to the Covid crisis, during which millions of people acquired new iPhones. Senior Analyst Yang Wang said, “Beyond the highly positive market reception for the iPhone 17 series, the key driver behind the upgraded shipment outlook lies in the replacement cycle reaching its inflection point. Consumers who purchased smartphones during the COVID-19 boom are now entering their upgrade phase.”

Second-hand – the gateway to iPhone

Apple also benefit from the second-user market. iPhones tend to remain usable for much longer than competing devices, they sell well as used devices, retain their value longer, and tend to be more resilient. This is evident at the street level, where it was recently reported that some London criminals refuse to steal anything other than an iPhone; they get more cash for them.

This popularity unleashes a golden halo for Apple as it means that once someone has used a second-hand iPhone for a while they are far more likely to upgrade to a new one when given the chance. 

That’s what’s happening this time, according to the analysis, which claims 358 million second-hand iPhones were sold between 2023 and Q2 2025. “These users are also likely to upgrade to a new iPhone in the coming years. These factors will form a sizable demand base, which is expected to sustain iPhone shipment growth over the coming quarters,” Counterpoint said.

The tariff factor

The analysts also shared interesting reflections on the impact of US tariffs on the industry. While it is inarguable that these were announced in a blaze of guts and glory, the true impact once negotiations took place seemed more limited. 

All the same, the impact of those tariffs and subsequent US/China truce benefitted Apple, while also spurring acceleration in the evolution of a more diversified supply chain — lending impetus to its work to penetrate new markets. The success of the latter is particularly visible in India, where sales are rising rapidly, even as the number of iPhones made there increases. 

As above, so below

What’s changing are component prices. Growth in smartphone sales generally alongside competition from rapidly emerging new industry sectors such as artificial intelligence means component costs are climbing. To some extent, Apple and Samsung are protected against the impact of those increases as they can lock in prices in the long term. Smaller vendors, principally in the Android space, lack that flexibility, meaning they are left to compete for shrinking margins in a market defined by prices set by Apple and Samsung. 

Those makers are about to face even more pressure, Counterpoint said, as Apple extends the breadth of the iPhone lineup. 

“By expanding its lineup across multiple price tiers, including the growing “e” series, and potential adjustments to the Pro and Base launch cycles, Apple is strategically positioning itself to capture rising demand from aspirational consumers, particularly in emerging markets, and to strengthen its presence in the lower premium segment, which is projected to grow faster than the overall market.”

That’s important, as it means smaller smartphone vendors will be pressured on manufacturing costs from below, even as they are forced to compete more fiercely for sales at the more lucrative parts of the mid-range market, with Apple and Samsung now fighting in those corners, too.

The secret weapon

Finally, the popularity of iOS remains an Apple trump cards, putting even more wind beneath its iPhone-selling wings. “Given an increasing preference for the iOS ecosystem, compatibility between devices and a substantial number of older models within Apple’s installed base due for renewal, Apple will retain the lead over other smartphone OEMs through the end of the decade,” the analysts said.

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Source:: Computer World

Microsoft has lost two senior data center and AI infrastructure leaders at a time when the company is racing to expand capacity for its Copilot and Azure AI services, raising questions about its ability to meet surging demand for power-intensive AI workloads.

The back-to-back departures come as Microsoft is investing heavily in new data center sites, power agreements, and custom hardware to keep pace with escalating AI usage across the enterprise.

The exits involve Nidhi Chappell, Microsoft’s head of AI infrastructure, and Sean James, its senior director of energy and data center research, who announced he is leaving for Nvidia.

Chappell, who spent six and a half years at Microsoft, oversaw the buildout of what she described as the world’s largest AI GPU fleet, supporting workloads for Microsoft, OpenAI, and Anthropic.

Both executives held roles central to Microsoft’s AI expansion strategy. Their departures come as Microsoft, like other hyperscalers, faces mounting challenges around power availability, grid interconnection timelines, and sourcing sufficient accelerators to sustain AI growth.

Notably, Microsoft AI CEO Mustafa Suleyman’s recent post on X claiming the company spent “15 million labor hours” building its new data center prompted Elon Musk to ask whether Microsoft was “doing it right.”

Microsoft did not immediately respond to a request for comment.

Microsoft’s constraints

Analysts say the twin departures mark a significant setback for Microsoft at a critical moment in the AI data center race, with pressure mounting from both OpenAI’s model demands and Google’s infrastructure scale.

“Losing some of the best professionals working on this challenge could set Microsoft back,” said Neil Shah, partner and co-founder at Counterpoint Research. “Solving the energy wall is not trivial, and there may have been friction or strategic differences that contributed to their decision to move on, especially if they saw an opportunity to make a broader impact and do so more lucratively at a company like Nvidia.”

Even so, Microsoft has the depth and ecosystem strength to continue doubling down on AI data centers, said Prabhu Ram, VP for industry research at Cybermedia Research.

According to Sanchit Vir Gogia, chief analyst at Greyhound Research, the departures come at a sensitive moment because Microsoft is trying to expand its AI infrastructure faster than physical constraints allow.

“The executives who have left were central to GPU cluster design, data center engineering, energy procurement, and the experimental power and cooling approaches Microsoft has been pursuing to support dense AI workloads,” Gogia said. “Their exit coincides with pressures the company has already acknowledged publicly. GPUs are arriving faster than the company can energize the facilities that will house them, and power availability has overtaken chip availability as the real bottleneck.”

Nvidia’s advantage

On the other hand, Shah pointed out that James’ move to Nvidia also signals that the most impactful innovations may now come from the vendor ecosystem, not just individual hyperscalers.

“If Nvidia can address the industry’s energy constraints through more efficient compute-to-rack designs, the benefits will extend across the enterprise market,” Shah added.

The move further underscores how central energy systems and data center efficiency have become to the competitiveness of AI infrastructure, Gogia said. “Bringing in someone who has spent years solving Microsoft’s power and cooling challenges provides Nvidia with a deeper understanding of how hyperscale AI environments behave under real stress,” Gogia said. “This knowledge will shape the design of future GPU systems, their thermal envelopes, and the energy profiles of next-generation AI factories.”

Source:: Computer World

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In an echo from this time last year, smartphone users are again being warned against sending unencrypted text messages by the US Cybersecurity and Infrastructure Security Agency (CISA).

Warning in particular against nation-state attacks via messaging services aimed at high-value individuals, the latest updated CISA bulletin should be seen as a warning to us all. “Cyber threat actors are using spyware and other advanced social engineering techniques to target private messaging apps and compromise mobile devices,” the organization said.

Will Apple encrypt RCS in iOS 26.2?

While the security team notes that exploits seem focused on Signal and WhatsApp at the moment, the implication remains that Android and iPhone users should avoid unencrypted text messaging. That means don’t use the standard messaging app on either device, as even the latest Rich Communication Services (RCS) protocol now supported on both platforms doesn’t yet extend to end-to-end encryption, which only came to RCS earlier this year.

Google is testing end-to-end encryption, and Apple has promised to introduce it. “End-to-end encryption is a powerful privacy and security technology that iMessage has supported since the beginning, and now we are pleased to have helped lead a cross industry effort to bring end-to-end encryption to the RCS Universal Profile published by the GSMA,” Apple said. “We will add support for end-to-end encrypted RCS messages to iOS, iPadOS, macOS, and watchOS in future software updates.” 

Right now, the smart money has RCS encryption as a potential addition within iOS 26.2. This makes sense given Apple sees privacy as a human right, and protection of that right demands E2EE in its messaging apps.

CISA says things are dangerous

CISA pulled no punches in the recommendations it made. It warned that potential targets (particularly in military, government, or political positions) should immediately review the security protections they have in place. “Highly targeted individuals should assume that all communications between mobile devices — including government and personal devices — and internet services are at risk of interception or manipulation,” it warns.

What this means is that if you must send messages to others, you should use encrypted messaging platforms such as Signal or WhatsApp. You might also want to protect yourself by preventing use of standard text messaging on your devices. On the iPhone, you can do this in Settings, where in the Messages section you should disable the Send as Text Message option. This will ensure any messages you are able to send are sent securely using iMessage’s E2EE system.

CISA makes some iPhone-specific recommendations. That’s interesting as it reflects how widely used the Apple device has become in government and business, and suggests how febrile the security environment has become. That should be of particular concern to any government, particularly the UK government which may, or may not, have forced Apple to ensure encryption on its devices is deeply weakened. That latter seems a self-harming move in the security environment CISA tells us we’re in.

What does CISA suggest for iPhones?

CISA warns that iPhone users from the highly targeted groups should enable Lockdown Mode, use iCloud Private Relay, or rely on encrypted DNS services from providers such as Cloudflare, Google, or Quad9. It also suggests regular review of app permissions in Settings>Privacy & Security, revoking these if an app doesn’t really need such functionality. 

What does CISA suggest for Android?

CISA’s Android advice is to use RCS if end-to-end encryption is enabled, use Private DNS/encrypted DNS services, and ensure the highest security settings are in place on Chrome and Google Play Protect. 

CISA recommends Android users “prioritize models from manufacturers with strong security track records.” That means only using devices from manufacturers with a good reputation for timely security updates and a commitment to long-term security support.

The agency also has some good advice for those who use Signal or WhatsApp to help secure their communications. Among other suggestions, it warns people not to scan group invites or QR codes from unknown sources, and to verify the authenticity of any group invitations by contacting the group administrator initially. It also advises people to review the devices included in the linked devices section in message application settings. Finally, it recommends the use of FIDO authentication to help secure the device and the messaging service, and to “migrate away” from SMS-based MFA systems.

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Source:: Computer World

Anthropic has launched Claude Opus 4.5 with a 67% price cut that repositions its flagship model from a boutique offering to a production-ready enterprise tool.

The new pricing of $5 per million input tokens and $25 per million output tokens — down from $15 and $75 — brings Anthropic closer to OpenAI and Google while maintaining a premium position.

The launch comes a week after Google released Gemini 3 and less than two weeks after OpenAI launched GPT-5.1, underscoring the rapid pace of competition in enterprise AI. For context, OpenAI’s GPT-5.1 costs $1.25 per million input tokens and $10 per million output tokens, while Google’s Gemini 3 Pro runs $2 to $4 per million input tokens.

“Opus 4.5 is a meaningful step forward in what AI systems can do,” the company said in an announcement on its website.

The benchmark debate

Anthropic claimed Opus 4.5 achieved 80.9% on Software Engineering Benchmark Verified, outperforming OpenAI’s GPT-5.1-Codex-Max at 77.9%, Google’s Gemini 3 Pro at 76.2%, and its own Sonnet 4.5 at 77.2%. The company also said the model scored higher on its internal two-hour performance engineering assessment than any human candidate who has taken the exam.

But analysts cautioned that benchmark scores tell only part of the story. “Benchmark scores often look impressive but mean very little once a model enters production,” said Sanchit Vir Gogia, chief analyst at Greyhound Research. “They are clean, simple, and run in isolation. Most enterprise systems are layered with legacy software, inconsistent workflows, and regulatory overhead.”

Leslie Joseph, principal analyst at Forrester, noted that while Anthropic’s lead is statistically significant, “the gap between these models has narrowed to the point where winner-takes-all metrics are less relevant than considerations of best architectural fit.”

The real evaluation criteria for enterprises, according to Gogia, are different: “Can the model work with an organization’s legacy tools? Will it maintain accuracy across long sequences? Is it stable under load? These are the details that matter more than a score on a public leaderboard.”

Strategic pricing shift

Beyond performance claims, Anthropic’s pricing strategy marks a significant repositioning. The pricing reduction represents more than cost competition. “Previously, the Opus line was viewed as a ’boutique’ model, too expensive for general automated workflows,” Joseph said. “By slashing prices significantly, Anthropic is undercutting the specialized enterprise models of its rivals, signaling that ‘frontier intelligence’ is no longer a scarce resource.”

The company said prompt caching can reduce costs by up to 90% and batch processing offers 50% savings. These optimization features matter for enterprise deployments where predictable costs and resource management drive adoption decisions.

“Anthropic’s updated pricing is not about joining a race to the bottom,” Gogia said. “The new rates bring Claude closer to competitors, but the value proposition remains clear. This model is built for enterprises that care more about stability and trust than token volume.”

The model offers a 200,000-token context window — roughly 150,000 words — and is available through Anthropic’s API, Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Foundry. According to the announcement, Opus 4.5 is “built for professional software engineering, complex agentic workflows, and high-stakes enterprise tasks.”

Where it fits in enterprise workflows

The technical specifications translate to specific enterprise use cases. Internal testers at Anthropic reported that Opus 4.5 completed tasks that were difficult for Sonnet 4.5 and handled ambiguous requirements without extensive guidance, according to the announcement. In the announcement, the company acknowledged its performance engineering test doesn’t measure collaboration, communication, or professional judgment developed through experience.

Analysts identified specific use cases where the model’s capabilities align with enterprise needs. “Given the model’s specific enhancements in agentic coding and reliable document synthesis, software engineering and document-heavy departments such as legal or compliance are clear beneficiaries,” Joseph said.

Gogia emphasized the model’s suitability for precision-focused roles: “Legal teams, software architects, policy writers, and compliance officers will see the most impact. These are the areas where accuracy matters more than speed.”

Deepika Giri, head of research for big data and AI at IDC Asia/Pacific, said the combination of competitive pricing and efficiency is accelerating enterprise adoption. “Advanced safety and auditability features make Anthropic particularly well-suited for compliance-focused industries and regulated use cases,” Giri said.

Developer tools and integrations

Beyond the core model improvements, Anthropic expanded its developer toolset.  Anthropic expanded Claude Code, its terminal-based development environment, with an enhanced plan mode. “Plan Mode now builds more precise plans and executes more thoroughly — Claude asks clarifying questions upfront, then builds a user-editable plan.md file before executing,” the company said in the announcement.

The tool is now available in Anthropic’s desktop application. Claude Opus 4.5 is also available in GitHub Copilot for Pro, Pro+, Business, and Enterprise users, according to a GitHub changelog.

For paid users, “long conversations no longer hit a wall — Claude automatically summarizes earlier context as needed, so you can keep the chat going,” the announcement said. Claude for Chrome, which operates across browser tabs, is now available to all Max subscribers. Claude for Excel moved to general availability for Max, Team, and Enterprise users, the announcement added.

What enterprises should weigh

For organizations evaluating AI platforms, the decision extends beyond per-token pricing. “Procurement teams must weigh ecosystem fit,” Joseph said. “For instance, a company deeply integrated into Google Workspace might find Gemini’s multimodal capabilities offer more practical value, even with a slightly lower coding score.”

Gogia noted that cost considerations in regulated industries differ from pure API economics. “In industries where a single misstep can trigger compliance issues or downstream rework, the true cost is not the API bill. It is the cleanup. For those teams, paying more for fewer problems is a trade that makes sense.” The launch marks Anthropic’s third major model release in two months, following Sonnet 4.5 in September and Haiku 4.5 in October.

Source:: Computer World

Apple’s decision to take part in (and co-sponsor) this year’s NeurIPS conference shows how the company is keeping close tabs on future trends in the field, highlights its willingness to cooperate, and shows Apple reaching out to recruit new expertise. 

The company’s machine learning and artificial intelligence (AI) teams are deeply involved in the important event. Since Apple is a co-sponsor, its people will be at its booth to talk about the company’s research and will present several research papers at the show.

As described on the company’s Machine Learning website, the papers include research on more efficient image generation, protecting privacy in AI, and cutting-edge work on Large Reasoning Models (LRMs). You can explore all the presentations from the big-name attendees anticipated at NeurIPS via this interactive graphic.

NeurIPS is important

NeurIPS is considered to be the most prestigious and influential AI conference in the field. The world’s leading researchers and practitioners converge on the show to discuss their cutting-edge research. 

That also means the trends that emerge at the event tend to leak into wider discourse 12 to 24 months later. In 2023 and 2024, for example, conversations tended to converge around responsible AI, scaling, and efficiency — involving both hardware and software advances. Apple was clearly paying attention, and the current M5 processors inside some new Macs offer the kind of efficiency and hardware acceleration required for AI. 

In 2024, some of the big conversations related to Edge AI, AI-optimized hardware design, privacy-preservation in AI and the democratization of AI through open-source.

This year’s trends seem to be coalescing around hardware design, energy efficiency, quantum computing, contextual awareness, and data efficiency — coupled with more conversation on use of AI in specialized domains, including health, finance, robotics, and sustainable resource management. Many of those trends are already very much in the wider public conversation, reflecting growing public understanding of AI. 

Where is Apple?

Where is Apple in this? Apple plans to introduce its take on contextual AI in Siri next year. Speaking last month, Apple CEO Tim Cook said on this: “We’re also excited for a more personalized Siri. We’re making good progress on it, and as we’ve shared, we expect to release it next year.” 

Apple has also been working very hard (and very secretively) to develop its own AI-augmented digital health services, which might also make their debut in the coming year. These will evidently have a preventive health element as evidenced by the decision to move management of Apple Fitness+ under Apple’s vice president of health, Sumbul Desai, earlier this year. (“Our goal is to empower people to take charge of their own health journey,” said Desai in 2023). Apple’s Private Cloud Compute nails the cloud-based AI service option. 

It is also true that with its focus on hardware, software, and processor innovation, Apple now offers the best available tools for AI research, including tools for Edge AI. (You can test the ability of your Apple device to deliver AI at the edge today, using an app called Locally AI (for Mac, iPhone, or iPad). Thanks to the power of Apple Silicon, Locally lets you use private, on-device, edge LLMs right now.)

What if the company has been misconstrued?

Examples like these show how much Apple is already doing concerning the evolution of AI. It’s a huge field, of course, with different approaches. 

I’d argue that Apple’s strategic approach was to focus on specific use cases (think agentic AI, machine learning), and application of the technology in specific domains, rather than a catch-all LLM system, like ChatGPT. History indicates that strategic decision allowed the company to fall behind, but has it really?

Once you consider the wider industry conversations around applied AI coming out of NeurIPS in recent years, much of what Apple is actually delivering reflects a very strong response to the industry needs discussed and identified there. 

If hardware can be seen as the AI fundamentals, then the innate advantages of neural intelligence on Apple Silicon suggest it now has strong foundations in place, particularly around privacy, hardware, and edge AI. 

We shall now find out the extent to which Apple, its researchers, and the wider AI industry, can exploit the foundations Apple has laid.

You can follow me on social media! Join me on BlueSky,  LinkedIn, and Mastodon.

Source:: Computer World

By Hisan Kidwai Horror games are different. They combine action and storytelling with a sense of dread that instantly…
The post 99 Nights in the Forest Codes (November 2025) appeared first on Fossbytes.

Source:: Fossbytes

When infrastructure itself becomes the target

In early 2024, a breach involving Snowflake, Inc. sent a quiet shockwave through boardrooms across industries. Attackers bypassed perimeter defenses entirely; no malware, no exploit kit, no zero-day. They simply walked through an identity gap: weak credentials and excessive permissions.

The attackers pivoted laterally inside multiple customer environments (AT&T, Santander Bank, Ticketmaster, etc.) and exfiltrated large volumes of sensitive data. For many CISOs watching that breach unfold, the lesson was blunt: in the cloud, identity is the new infrastructure – and once it’s compromised, everything that depends on it is suddenly in play.

Some attacks have a cascading effect

One of the many customers impacted by the Snowflake data breach was Ticketmaster, which was using Snowflake systems for marketing and analytics. Hackers used a compromised Snowflake account to access Ticketmaster database, which resulted in the breach of 1.3 terabytes of data of 560 million individuals, triggering numerous lawsuits from customers.

This breach demonstrated that in cloud ecosystems, third-party data platforms become extensions of your attack surface, and when not protected, they can result in havoc.

shutterstock/Kjetil Kolbjornsrud

Cloud security is a global problem

This is a global pattern. 83% of organizations faced a cloud security breach in the past 18 months. 25% of organizations fear of having suffered a breach recently without knowing it yet. Most cloud security incidents are traced back to a combination of misconfigurations, over-privileged identities, or exposed APIs. Increased cloud adoption has created thousands of entry points, each dynamic, ephemeral, and easy to miss.

The rise in attacks is not opportunistic but structural. Cloud environments expand faster than they can be governed. Modern applications are API-driven by design, meaning every service interaction is effectively a mini-perimeter waiting to be tested. Multi-cloud brings architectural complexity that traditional tooling cannot correlate. Security teams are constantly racing business velocity, but adversaries don’t need to outrun the organization; they only need to outrun its controls.

Security-by-design approach

As a result, the old model of “deploy cloud, then secure it” has started to break down. Breaches today don’t occur because CISOs are unaware of the risks, they occur because visibility and enforcement haven’t caught up with speed and fragmentation. Enterprises don’t need another point solution, they need an integrated way to see risk the way an attacker sees it: across posture, identity, runtime behavior, and exposed services.

This is why modern security architectures are consolidating around cloud native application protection platform (CNAPP) as the backbone of cloud defense, bringing posture, workload and identity analytics together instead of expecting teams to stitch insights manually.

Posture evaluation isn’t just about configuration drift any more

It’s about anticipating the attack path before it becomes actionable. API defense is no longer a niche extension, it is the new frontline. And Zero Trust, once treated as strategy rhetoric, is now the only rational method of preventing lateral movement after the inevitable compromise of a credential or token.

At the same time, regulatory pressure has quietly reframed cloud governance. Boards and insurers are no longer asking “Are you compliant?” They are asking, “Can you continuously prove it?” Evidence is becoming as critical as control.

Organizations need more than implementing cloud controls

Organizations need to operate security as an assurance layer; across CNAPP, posture management, API visibility, Zero Trust enforcement, microsegmentation and continuous compliance. Where in-house teams struggle with scale and signal-to-noise, a security partner can bring sustained visibility and managed resilience. That turns cloud risk into a controllable variable and cloud innovation into something security no longer must slow down.

In 2025, the real question is whether your organization can continuously defend and prove its cloud posture at enterprise scale. The ones who can, will accelerate. The ones who can’t, will continue to absorb the cost of architectural blind spots. T-Systems helps make sure you are in the first category.

Doubling down on AI but worried about security? Read this e-book today — get your copy here.

Source:: Computer World