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BIGWORDS.PAGE je open-source webová aplikace, která po otevření odkazu v prohlížeči vykreslí přes celou obrazovku jednoduché informační sdělení. Zpráva i její nastavení jsou uložené v části URL za znakem #, například odkaz https://bigwords.page/#abclinuxu zobrazí jako velký bílý nápis 'abclinuxu' na černém pozadí. Obsah odkazu lze upravovat i vestavěným editorem, ten umožňuje nastavovat formátování a vizuální efekty textu, časovače, QR kódy a obrázky. Zdrojový kód je dostupný pod licencí MIT na GitHubu.

Hackers are abusing legitimate Bing search-result redirects as click URLs in Google search ads to direct users to fake Claude installers that deliver ClickFix attacks. [...]

Bob, possibly the same Bob whose conversations with Alice draw so much interest from eavesdropping Eve, was browsing a site we'll call TechHub. The site hosts an AI agent served by Amazon Bedrock AgentCore. Bob asked the agent for help understanding the content of a URL, a credential endpoint – in raw JSON, if you don't mind. The endpoint returned data from the Instance Metadata Service (IMDS), which provides metadata about cloud instances and VMs at providers like AWS, Azure, and Google Cloud Platform. The metadata includes details like region and availability zone, subnets, system images, security groups, public keys injected during spawning, but also potentially more sensitive details like user data and security tokens. IMDSv2 addresses some of these risks, but back when Bob was browsing late last year, Bedrock AgentCore still used IMDSv1. The metadata provided to Bob by the helpful agent contained the agent's temporary credentials. So Bob loaded them onto his local machine, and remotely enumerated the company's other agents in that AWS region. He then logged into the Amazon Elastic Container Registry (ECR), pulled the agent container images, and ran each as root to inspect the source code. The stolen credentials also allowed Bob to discover the memory resources available in that AWS region, including the ones used by agents. From these, he's able to extract the users and their agent sessions – their conversations. Researchers at Zenity Labs disclosed their findings to AWS in December 2025. "We discovered that agents deployed through AgentCore could access their instance's IMDS endpoints," said Tamir Ishay Sharbat and Lana Salameh in a blog post. "This meant that an external attacker with nothing more than chat access to a single exposed agent could send a single prompt, extract its IMDS credentials, and use them to take over all AgentCore agents in the same AWS account and region." The basic problem, they explain, is that the Firecracker MicroVM used by AgentCore failed to provide sufficient network isolation. So an attacker – I know you're thinking it was Mallory, but it was really Bob – could direct the agent to carry out a server-side request forgery (SSRF) attack by fetching temporary AWS credentials for the IAM role assigned to the workload. And because the default AgentCore role was overpermissioned – it was scoped to all AgentCore resources in the region rather than a single agent – anyone in possession of the temporary IAM credentials could launch other agents, read sessions, write agent memories, and fetch secrets from AWS Secrets Manager. "By leveraging the IMDS credentials we could send direct API requests to create new memories across different agents and users," said Sharbat and Salameh. "These in turn would persistently alter agent behaviour and hijack the agents’ goals across future sessions." The Zenity researchers told Bob's tale, or something like it, to AWS last December, then followed up in January 2026 with details about AgentCore being overprivileged. On April 12, 2026, AWS responded to the security biz that its report was "informative" and closed the report, noting that as of February 14, 2026, AgentCore had been updated to use IMDSv2 exclusively. AgentCore's excessive permissions remained in place at least until June 22, 2026, when Zenity checked in and found the issue hadn't been remediated. A final review by Zenity occurred on September 29, 2026, at which point the biz observed that AWS had addressed the extant problems, clearing the way for Bob's hypothetical adventure to finally be told. Following publication, Amazon wrote in to say that Zenity’s research misrepresents documented behavior as a vulnerability, suggesting that developer error would be required to enable the attack. We’ve asked for clarification since that’s not the scenario Zenity has described. ®

Cybersecurity researchers have disclosed details of an ongoing credential-theft campaign that has compromised two high-profile open-source maintainer accounts to push a malicious workflow into over 340 repositories. "Using the account of Takashi Kitao, author of the 18,400-star game engine pyxel, the attacker pushed a malicious workflow to 27 repositories starting at 13:20 UTC," StepSecurity Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

PC shipments saw a steep drop of about 20 percent in Q3 2026, analysts reported this week.

The industry saw its “sharpest decline since “Q1 2023," Omdia said in an announcement toady. Global shipments of laptops, desktops, and workstations fell 21.2 percent year over year (YoY) to 58.1 million devices, the analyst said.

Desktop PC shipments (including desktop workstations) decreased 23.5 percent to 11.7 million units, and laptop shipments (including laptop workstations) declined 20.6 percent to 46.4 million, per Omdia.

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The FBI has arrested another suspected co-conspirator of ShinyHunters, FBI Director Kash Patel said on October 9 in a post on X. ShinyHunters is the extortion group that said in September it had breached the FBI's jobs portal and stolen sensitive data on almost all FBI agents and job applicants. The FBI has not named the suspect, and no charges have been made public. The Swati Khandelwalhttp://www.blogger.com/profile/[email protected]

Věci se začínají hýbat. AI se dostala do fáze, kdy řeší skutečné problémy. Vidět je to například v matematice – v září to začalo kontroverzním řešením jedné letité úlohy, v říjnu následoval balík 722 matematických článků, což už je věc s potenciálem změnit celý obor. Vidíte ten trend? Co dál? ...

Threat actors are exploiting one critical and one medium-severity vulnerability still unpatched in the AhsayCBS backup management platform to deploy webshells and cryptocurrency miners. [...]

The FBI has arrested another suspected member of the ShinyHunters extortion group believed to be involved in the recent breach of FBI systems, Director Kash Patel announced Friday. [...]

Microsoft před třemi lety patřil k lídrům v AI, ale koncem září oznámil reset. Zamýšlíme se nad tím, jak svůj náskok ztratil a neproměnil Copilot v populární produkt. Teď se orientuje primárně na firmy a na vývojářskou scénu. Odpovídá tomu podoba nového Copilotu, ale i čerstvě oznámené novinky pro ...

UniCredit Bank od ledna 2027 mění ceník. Majitelé některých starších účtů přijdou o bezplatné výběry z bankomatů. Zdraží také vstupy do letištních salonků a podnikatelům se zvýší poplatek za předčasné splacení úvěru.

What if the three remaining hard disk manufacturers became two? Seagate Technology and Western Digital control 90% of the market, according to market researcher TrendForce, with Toshiba picking up the crumbs.

Seagate and WD both make their own magnetic drive heads, but Toshiba relies on a third party, TDK, which also sells to Seagate and WD when they need extra capacity.

Seeking to guarantee supplies of this critical component, Toshiba made a bid for TDK’s drive head business earlier this year, according to Bloomberg. Concerned that this could affect its ability to meet the growing demand for hard disks from AI data centers, Seagate made a counteroffer, Bloomberg reported. TDK is staying mum.

If Seagate were to capture the TDK unit it could knock Toshiba out of the hard disk market altogether, according to Bloomberg.  

While Toshiba is reliant on its suppliers for technological advances, WD and Seagate continue to innovate. In February, Western Digital announced two technologies aimed at speeding up drive throughput: high bandwidth drive technology (HBDT) and dual pivot technology (DPT).

Western Digital said HBDT will enable simultaneous reading and writing from multiple heads on multiple tracks, delivering up twice the bandwidth of conventional HDDs.

In July, Seagate launched a hard disk packing 30TB into a 3.5-inch enclosure using its Heat-Assisted Magnetic Recording (HAMR) technology, and announced plans to release 32TB and 36TB models.

This article first appeared on Network World.

The owner of a ransomware remediation company is facing trial for defrauding customers.

Zohar Pinhasi, also known as “Zack Silver” and “Zack Green,” has been arraigned in New York on wire fraud charges for allegedly defrauding clients of his ransomware remediation company, MonsterCloud.

Pinhasi falsely claimed he could recover documents encrypted by ransomware without paying a ransom, according to district attorney Joseph Nocella. “The defendant re-victimized his clients while extracting a hefty profit for himself,” Nocella said.

MonsterCloud claimed to offer an alternative to paying the ransom. Its website said that, thanks to its decryption techniques, “our team specializes in helping businesses recover their data without succumbing to ransom demands.” 

However, the indictment alleges that rather than using any technology, Pinhasi simply paid the cybercriminals in exchange for a decryption key with which MonsterCloud employees would then an attempt to unlock their clients’ files. It is alleged that Pinhasi typically charged clients a fee that was substantially higher than the ransom payment. For example, in 2023, he made a payment of $8,200 to a cybercriminal while charging a client $150,000.

There may be several reasons why clients chose to use MonsterCloud. US government advice (echoed by other governments) is not to pay ransoms as it may encourage more attacks, and victims may not get their data back. In addition, in some cases, if the attackers are from a country or group subject to trade sanctions, making a payment may actually be illegal, leaving the victim facing criminal charges.

There may be other factors at play. “Cases vary; sometimes negotiators simply overcharge for their services. In other cases, they may inflate the final amount, saying, for instance, that 50 percent extra is to ensure a third-party validation of secure data erasure or something similar that the client would buy,” said Ilia Kolochenko of cybersecurity company ImmuniWeb.

He warned that there were several techniques being used to extract additional money from ransomware victims.

“Some will be contacted by fake law enforcement agencies, which typically promise to find and arrest the hackers, but also mention the victim’s civil liability for the data breach and ask to prepay a bond for an eventual regulatory fine. Other victims may be contacted by fake cybersecurity companies, which claim that they have already found their stolen data on the Dark Web and ask for money to ‘securely erase’ the data from the dark web to avoid bad publicity and regulatory sanctions,” he said.

Similar cases have come to court recently, said Kolochenko, one in July involving a Florida business and another targeting a Latvian national in May.

This article first appeared on CSO.

Uber přiznal, že auta pohybující se po mapě před potvrzením objednávky nejsou konkrétní vozidla, která čekají na daného zákazníka. Jde o vizuální prvky generované algoritmem, jejich cílem je ukázat všeobecnou dostupnost řidičů v dané oblasti. To znamená, že pokud uživatel vidí na mapě auto jen ...

Germany has arrested a Russian national suspected of being a leading member of the Qilin ransomware group following extradition from Japan earlier this month. [...]

AI agents can use valid credentials to perform actions beyond their assigned permissions, creating risks that traditional access controls may not prevent. Token Security explains how organizations can enforce agent-specific policies without sacrificing autonomy. [...]

Exoskeletons have advanced rapidly, leading to the emergence of numerous devices with commercial and clinical applications.

This year, members of Seattle Mountain Rescue have been setting off into the wilds of the Pacific Northwest wearing an unusual piece of kit.

They’ve been hiking into the wilderness with powered assistive devices attached to their hips and legs. Designed to increase lower-body strength when climbing or carrying heavy loads, these pieces of equipment are being tested to see if they can boost rescuers’ speed and endurance when it matters most—during searches for stranded people.

Devices like these are called human exoskeletons. They attach to parts of the body to create an external—or “exo”—mechanical structure. This powered frame enhances the wearer’s physical capabilities.

In physically demanding fields, workers are increasingly using these devices during strenuous tasks. IKEA has used SuitX exoskeletons for several years now. These assist warehouse workers with handling heavy materials. Ford, Boeing, and Mazda Toyota have also all adopted the tech on some of their assembly lines.

In Finland, a recent project called ExoPELA assessed whether exoskeletons could reduce muscle load and strain in rescue and firefighting work. It found noticeable benefits for users in certain real-world tasks.

And in early 2026, the Ukrainian military revealed its soldiers had been using Hypershell exoskeletons on the front lines to help with carrying artillery shells. According to test results, soldiers wearing the devices “become less fatigued, work faster, and maintain combat effectiveness for longer,” Colonel Vitalii Serdiuk told the Ukrainska Pravda newspaper in March.

Multiple consumer and clinical devices, designed for everyday assistance, rehabilitation, and exercise, are also now available. Some estimates have valued the total sector at around $500 million currently and predict it could double or triple in size by the mid-2030s.

Exoskeleton technology has progressed significantly over the past decade. This has largely been thanks to robotic motors, sensors, and control systems becoming more affordable and accessible. However, the concept of augmenting human performance with exoskeleton-like devices dates back much earlier.

One of the earliest known concepts was patented in 1890 by Nicholas Yagn, a self-taught Russian inventor, who designed a wearable apparatus for exercising. And in 1919, the American Leslie C. Kelley received a patent for a steam-powered device to support walking, one of the first powered exoskeleton concepts.

Diagrams of Nicholas Yagn’s exercising exoskeleton from his patent. United States Patent Office/Google Patents

By the end of the 1960s, multiple actuated robotic exoskeletons incorporating electronic control systems had been developed. Since then, exoskeleton research and development has advanced rapidly, leading to the emergence of numerous devices with commercial and clinical applications.

How They Work

Exoskeletons generate forces to make the wearer stronger, move faster, or fatigue slower.

Some devices also improve movement accuracy and dexterity or support overall posture. Some are designed to elevate human capabilities beyond what is typically possible. Others help patients with reduced physical capacity.

Modern, active robotic exoskeletons typically consist of a lightweight mechanical frame with ergonomic attachments to the human body. These are usually affixed at the trunk, waist, and to upper or lower limbs.

For example, the Hypershell device seen in Ukraine attaches to the user’s waist and thighs, to assist with hip flexion and extension and strengthen lower-body movement. The SuitX device used by IKEA attaches to the torso and upper limbs to support the back and shoulders.

In most powered exoskeletons, mechanical components called actuators convert electric power from batteries into mechanical movement, generating forces that support or enhance the body’s movement.

The actuators are coordinated by control units embedded in the exoskeleton. These define the trajectories of the exoskeleton’s movements and how much force it applies to the wearer’s body. Exactly how the device moves, and how forcefully, will depend on the task and the state of the user—with the device using sensors to determine what’s needed.

For instance, if a wearer starts running, an exoskeleton will speed up its supportive movements. If it senses they’re beginning to fatigue, it might increase its power output to compensate.

Control units are normally pre-programmed for specific tasks, though modern exoskeletons are increasingly becoming more adaptive. Some are equipped with algorithms that learn from users’ actual working behaviors to better support their actions.

However, assistance exoskeletons provide generally falls into three categories.

Power augmentation increases the force capabilities of the user. This is commonly seen in assistive exoskeletons, like those being used by IKEA and in Ukraine.

Assist-as-needed or resist-as-needed settings provide support to the body only when necessary. This setting is often used in rehabilitation devices to help users train their bodies to recover lost capabilities.

Finally, there’s full robotic control, where the exoskeleton assumes complete control over part of the body. This tends to be for users who have lost certain motor functions. For example, a lower-body exoskeleton might use full robotic control to allow someone with spinal cord injury to walk.

These ways of working can be combined and adapted according to the specific task, environment, and needs of the user.

What’s Next?

For now, most exoskeletons rely on feedback from sensors to define how the exoskeletons behave; they’re wholly mechanical. But in the future exoskeletons could be operated with signals from the wearer’s muscles or brain. Research is exploring this, but it remains a challenge. Harnessing these signals might require an invasive interface and extensive user-specific calibration and adaptation.

Power is another current challenge. Batteries have to be integrated into exoskeletons and regularly recharged. This introduces weight and size constraints that affect practicality. The energy density of batteries is steadily improving, however.

New materials are also pushing the boundaries of what’s possible. Exoskeletons are being developed that are made from soft textile or rubber-like materials that can be integrated into clothing, footwear or protective equipment.

Research into walking exoskeletons during the 1960s and 1970s contributed to the development of the first humanoid bipedal robots. This has come full circle. Interest in humanoid robotics is now accelerating the development of actuators and batteries. These will advance the wearable robotic technologies of tomorrow.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

The post The Dawn of the Age of the Exoskeleton appeared first on SingularityHub.

Humans have looked to the natural world for technological inspiration for millennia. AI and rapidly improving biotechnology are giving us new ways to explore four billion years of evolutionary experiments.

Long before biomimicry had a name, humans were practicing it. We have always studied living things for clues about how to build, move, heal, and survive. Nature wasn’t a separate category from technology so much as the place where many of our technological ideas began.

Modern engineering has made the connection easier to spot. High-speed trains have borrowed from the shape of kingfisher beaks. Adhesives have been modeled on mussels. Synthetic fibers have taken inspiration from spider silk. Even artificial neural networks trace their conceptual origins to the organization of neurons in the brain.

So the idea that nature can teach us how to innovate is hardly new. What is new is the scale at which we can look.

For most of human history, our access to nature’s accumulated knowledge was limited by what we could observe directly and gradually understand. Today, sequencing, imaging, sensors, bioinformatics, and artificial intelligence are opening biological systems to investigation at levels that were previously inaccessible.

In Living Tech: The Convergence of Biology and Innovation, Singularity expert Robert Suarez describes biology as perhaps “the largest dataset that has ever existed.” That is a useful way to think about what is changing. Biology represents roughly four billion years of evolutionary experimentation, and we are developing much better tools for reading the results.

Biology Is Becoming Legible

Advances in biotechnology have steadily converted more of the living world into information that computers can analyze. Researchers can sequence genomes, monitor gene expression, map neural connections, track changes inside cells, and collect increasingly detailed information about organisms and ecosystems.

This does not mean that we’ve turned the natural world into a textbook that anyone can understand. If anything, better measurement tends to reveal how inadequate many of our simpler models have been. But it does mean that biological processes once accessible only through painstaking observation can increasingly be analyzed computationally.

AlphaFold is one of the clearest examples. Determining the three-dimensional structure of a protein traditionally required difficult experimental work and could take years. DeepMind’s AlphaFold demonstrated that artificial intelligence could predict protein structures computationally with extraordinary speed, and subsequent versions have expanded that capability to interactions involving proteins and other biomolecules.

AI gives researchers another way to navigate the enormous space of biological possibility. Instead of testing every candidate in a laboratory, computational tools can narrow the field, identify patterns, and suggest where researchers should investigate next.

This offers a new way to approach innovation. Rather than simply noticing that an organism does something useful and trying to imitate it, researchers can increasingly start with a problem and ask where evolution may already have encountered something similar.

What Has Nature Already Figured Out?

Take, for example, transportation networks.

Slime mold is a single-celled organism with no brain or central nervous system. Yet as it searches for food, it creates a network that balances efficiency with resilience. In a well-known experiment, researchers arranged food sources to approximate cities around Tokyo. The slime mold developed a network comparable to the Tokyo rail system in cost, efficiency, and fault tolerance.

The point isn’t that transit authorities should surrender network planning to slime mold. Municipal governments have enough problems without giving procurement authority to an amoeba. The more interesting lesson is that evolution has spent enormous amounts of time working against many of the same underlying constraints humans face.

Living systems must move resources, regulate temperature, store information, respond to disruption, make use of imperfect inputs, and accomplish all of this under severe energy constraints. Once those problems are framed at that level, biology becomes relevant to fields that do not look remotely like biotechnology.

Data centers provide a good example. Cooling is one of their fundamental engineering challenges, while organisms across the natural world have developed an extraordinary variety of ways to manage heat. The opportunity is not necessarily to copy one particular animal or plant, but to examine biological strategies for thermal regulation and ask whether any of their underlying principles can be useful elsewhere.

The same applies to information storage. DNA packs enormous amounts of information into very little physical space. Instead of merely treating that as a curiosity of life, researchers are investigating whether DNA itself could eventually become a medium for storing digital information.

Mining provides another, stranger example. Certain plants known as hyperaccumulators naturally take up unusually high concentrations of metals from soil. Researchers have explored phytomining, in which plants could help recover valuable metals from places where conventional mining might be difficult or uneconomical. The Living Tech report goes a step further, considering how genetic tools might eventually enhance capabilities biology already possesses.

From Learning From Biology to Building With It

There is another difference between traditional biomimicry and what is happening now.

Historically, learning from nature generally meant studying a biological solution and recreating some version of it using human-made materials and machines. Observe flight, build an aircraft. Study adhesion, develop an adhesive. Examine the structure of a shell, design a stronger material.

Synthetic biology expands the possibilities because the biological system itself can become part of the technology.

Humans have manipulated living systems for thousands of years through agriculture, domestication, selective breeding, and fermentation. What has changed is the precision with which we can increasingly read, alter, and design biological processes.

Molecular biologist and Singularity expert Tiffany Vora describes synthetic biology in Living Tech as applying engineering and computer-science principles to the building blocks of life. Once genetic information has been digitized, biology begins to look less like something that must merely be observed and more like a medium that can also be manipulated.

That opens a different class of possibilities. A metal-accumulating plant might not merely inspire a new mining technology; the plant could become part of the mining process. Microorganisms can act as manufacturing systems, converting one substance into another. DNA may not simply inspire dense storage technologies; DNA itself could become the storage medium.

The boundary between biology and technology starts to get fuzzy at that point, which is one of the central ideas behind Living Tech. Biology can inspire technologies, digital technologies can help us understand biology, and synthetic biology can combine the two into systems that do not fit neatly on either side.

Four Billion Years Is a Considerable Head Start

There is a temptation, particularly when AI enters the conversation, to assume that making biology computable means we are close to understanding it. The evidence points in a less tidy direction.

PigeonBot II is a useful reminder.

Researchers from Stanford University and the University of Groningen developed the bird-inspired robot to study how birds achieve stable flight without the vertical stabilizers used by conventional airplanes. The robot could adjust its wings and tail in ways modeled on pigeons and successfully demonstrated stable rudderless flight.

But the researchers ran into a problem when trying to reproduce the performance of feathers. Synthetic alternatives did not match some of the useful mechanical properties of the real thing, so PigeonBot II incorporated actual pigeon feathers.

There is something appropriately humbling about building an advanced robotic bird and discovering that evolution has already manufactured one of the components better than you can.

Examples like this are important because they temper the idea of biology as a dataset. Digitization gives us unprecedented access to living systems, but a digital representation is not the system itself. The more closely researchers examine cells, brains, ecosystems, and organisms, the more often they discover additional layers of interaction that earlier models ignored.

The ebook offers several examples of this pattern. Brain cells once considered largely structural have turned out to play active signaling roles. Parts of the genome once dismissed as “junk” appear to contain additional functions. Researchers continue to discover biological entities that do not fit comfortably into existing categories. Better tools are increasing our knowledge, but they are also increasing the number of things we know we don’t understand.

Four billion years of evolutionary experimentation is a considerable head start.

Biology as a Platform for Innovation

This is why biotechnology may be too narrow a label for what is happening.

Most people still associate biotech primarily with pharmaceuticals, healthcare, genetics, and perhaps agriculture. Those applications are important, but they can obscure the broader possibility that biology is becoming a platform for innovation across industries.

A data-center engineer might look to thermal regulation in living systems. A materials scientist might examine how organisms produce strong materials without the heat, pressure, and chemical treatments common in industrial manufacturing. A mining company might find itself hiring plant scientists. Infrastructure designers might discover useful network principles in fungi or slime mold.

Computing followed a comparable trajectory. It began as an identifiable technology sector and eventually became part of almost every other sector. Artificial intelligence is now going through much the same process. The Living Tech thesis is that biology could increasingly do the same, affecting manufacturing, computing, architecture, transportation, agriculture, and other fields that do not traditionally think of themselves as biotech.

Humans have always looked to nature for ideas. That part is ancient. What is changing is our ability to see biological systems in much greater detail, search for patterns across enormous amounts of information, and increasingly move from observing biological solutions to adapting or directly using them.

Nature has been running experiments for four billion years. We’re getting much better at figuring out what it learned.

This article draws on Living Tech: The Convergence of Biology and Innovation, a Singularity report exploring how biology and technology are converging across fields ranging from manufacturing and computing to agriculture, architecture, neuroscience, and organizational design. Read the full report here.

The post We’ve Always Copied Nature. Now We Can Search It. appeared first on SingularityHub.

Upravená Cessna přeletěla celé Spojené státy bez jediného zásahu pilota • Letadlo zvládlo samo odstartovat, obletět bouřky i bezpečně samostatně přistát • Na celý let dohlíželi vzdálení operátoři pomocí klávesnice, myši a také mikrofonu