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Web browser
Google Internet malware Microsoft RustStealer Web browser

Rust-Developed InfoStealer Extracts Sensitive Data from Chromium-Based Browsers

Rust-Developed InfoStealer Extracts Sensitive Data from Chromium-Based Browsers

Browsers at risk

The latest information-stealing malware, made in the Rust programming language, has surfaced as a major danger to users of Chromium-based browsers such as Microsoft Edge, Google Chrome, and others. 

Known as “RustStealer” by cybersecurity experts, this advanced malware is made to retrieve sensitive data, including login cookies, browsing history, and credentials, from infected systems. 

Evolution of Rust language

The growth in Rust language known for memory safety and performance indicates a transition toward more resilient and hard-to-find problems, as Rust binaries often escape traditional antivirus solutions due to their combined nature and lower order in malware environments. 

RustStealers works with high secrecy, using sophisticated obfuscation techniques to escape endpoint security tools. Initial infection vectors hint towards phishing campaigns, where dangerous attachments or links in evidently genuine emails trick users into downloading the payload. 

After execution, the malware makes persistence via registry modifications or scheduled tasks, to make sure it remains active even after the system reboots. 

Distribution Mechanisms

The main aim is on Chromium-based browsers, abusing the accessibility of unencrypted information stored in browser profiles to harvest session tokens, usernames, and passwords. 

Besides this, RustStealer has been found to extract data to remote C2 servers via encrypted communication channels, making detection by network surveillance tools such as Wireshark more challenging.

Experts have also observed its potential to attack cryptocurrency wallet extensions, exposing users to risks in managing digital assets via browser plugins. This multi-faceted approach highlights the malware’s goal to increase data robbery while reducing the chances of early detection, a technique similar to advanced persistent threats (APTs).

About RustStealer malware

What makes RustStealer different is its modular build, letting hackers rework its strengths remotely. This flexibility reveals that future ve

This adaptability suggests that future replications could integrate functionalities such as ransomware components or keylogging, intensifying threats in the longer run. 

The deployment of Rust also makes reverse-engineering efforts difficult, as the language’s output is less direct to decompile in comparison to scripts like Python or other languages deployed in outdated malware strains. 

Businesses are advised to remain cautious, using strong phishing securities, frequently updating browser software, and using endpoint detection and response (EDR) solutions to detect suspicious behavior. 

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threat
APT41 Attack Calendar Cybersecurity Detection Google Hacking malware phishing threat

APT41 Exploits Google Calendar in Stealthy Cyberattack; Google Shuts It Down

 

Chinese state-backed threat actor APT41 has been discovered leveraging Google Calendar as a command-and-control (C2) channel in a sophisticated cyber campaign, according to Google’s Threat Intelligence Group (TIG). The team has since dismantled the infrastructure and implemented defenses to block similar future exploits.

The campaign began with a previously breached government website — though TIG didn’t disclose how it was compromised — which hosted a ZIP archive. This file was distributed to targets via phishing emails.

Once downloaded, the archive revealed three components: an executable file and a dynamic-link library (DLL) disguised as image files, and a Windows shortcut (LNK) masquerading as a PDF. When users attempted to open the phony PDF, the shortcut activated the DLL, which then decrypted and launched a third file containing the actual malware, dubbed ToughProgress.

Upon execution, ToughProgress connected to Google Calendar to retrieve its instructions, embedded within event descriptions or hidden calendar events. The malware then exfiltrated stolen data by creating a zero-minute calendar event on May 30, embedding the encrypted information within the event's description field.

Google noted that the malware’s stealth — avoiding traditional file installation and using a legitimate Google service for communication — made it difficult for many security tools to detect.

To mitigate the threat, TIG crafted specific detection signatures, disabled the threat actor’s associated Workspace accounts and calendar entries, updated file recognition tools, and expanded its Safe Browsing blocklist to include malicious domains and URLs linked to the attack.

Several organizations were reportedly targeted. “In partnership with Mandiant Consulting, GTIG notified the compromised organizations,” Google stated. “We provided the notified organizations with a sample of TOUGHPROGRESS network traffic logs, and information about the threat actor, to aid with detection and incident response.”

Google did not disclose the exact number of impacted entities.
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Privacy
AI Systems AI technology AI tools customer data privacy Data Privacy Data Safety User Data data security Data Usage Google Google AI model Privacy

Google’s AI Virtual Try-On Tool Redefines Online Shopping Experience

 

At the latest Google I/O developers conference, the tech giant introduced an unexpected innovation in online shopping: an AI-powered virtual try-on tool. This new feature lets users upload a photo of themselves and see how clothing items would appear on their body. By merging the image of the user with that of the garment, Google’s custom-built image generation model creates a realistic simulation of the outfit on the individual. 

While the concept seems simple, the underlying AI technology is advanced. In a live demonstration, the tool appeared to function seamlessly. The feature is now available in the United States and is part of Google’s broader efforts to enhance the online shopping experience through AI integration. It’s particularly useful for people who often struggle to visualize how clothing will look on their body compared to how it appears on models.  

However, the rollout of this tool raised valid questions about user privacy. AI systems that involve personal images often come with concerns over data usage. Addressing these worries, a Google representative clarified that uploaded photos are used exclusively for the try-on experience. The images are not stored for AI training, are not shared with other services or third parties, and users can delete or update their photos at any time. This level of privacy protection is notable in an industry where user data is typically leveraged to improve algorithms. 

Given Google’s ongoing development of AI-driven tools, some expected the company to utilize this photo data for model training. Instead, the commitment to user privacy in this case suggests a more responsible approach. Virtual fitting technology isn’t entirely new. Retail and tech companies have been exploring similar ideas for years. Amazon, for instance, has experimented with AI tools in its fashion division. Google, however, claims its new tool offers a more in-depth understanding of diverse body types. 

During the presentation, Vidhya Srinivasan, Google’s VP of ads and commerce, emphasized the system’s goal of accommodating different shapes and sizes more effectively. Past AI image tools have faced criticism for lacking diversity and realism. It’s unclear whether Google’s new tool will be more reliable across the board. Nevertheless, their assurance that user images won’t be used to train models helps build trust. 

Although the virtual preview may not always perfectly reflect real-life appearances, this development points to a promising direction for AI in retail. If successful, it could improve customer satisfaction, reduce returns, and make online shopping a more personalized experience.
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Software
Advanced Technology Artificial Intelligence Cyber Security cybercriminals CyberThreat Google Google Ads Google Marketing Software

Google Unveils AI With Deep Reasoning and Creative Video Capabilities

 


This week, Google, as part of its annual Google Marketing Live 2025 event, unveiled a comprehensive suite of artificial intelligence-powered tools to help the company cement its position at the forefront of digital commerce and advertising on Wednesday, May 21, at a press conference.

Google's new tools are intended to revolutionise the way brands engage with consumers and drive measurable growth through artificial intelligence, and they are part of a strategic push that Google is making to redefine the future of advertising and online shopping. In her presentation, Vidhya Srinivasan, Vice President and General Manager of Google Ads and Commerce, stressed the importance of this change, saying, “The future of advertising is already here, fueled by artificial intelligence.” 

This declaration was followed by Google's announcement of advanced solutions that will enable businesses to use smarter bidding, dynamic creative creation, and intelligent, agent-based assistants in real-time, which can adjust to user behaviour and market conditions, as well as adapt to changing market conditions. Google has launched this major product at a critical time in its history, as generative AI platforms and conversational search tools are putting unprecedented pressure on traditional search and shopping channels, diverting users away from these methods. 

By leveraging technological disruptions as an opportunity for brands and marketers around the world, Google underscores its commitment to staying ahead of the curve by creating innovation-driven opportunities for brands and marketers. A long time ago, Google began to explore artificial intelligence, and since its inception in 1998, it has evolved steadily. Google’s journey into artificial intelligence dates back much earlier than many people think. 

While Google has always been known for its groundbreaking PageRank algorithm, its formal commitment to artificial intelligence accelerated throughout the mid-2000s when key milestones like the acquisition of Pyra Labs in 2003 and the launch of Google Translate in 2006 were key milestones. It is these early efforts that laid the foundation for analysing content and translating it using AI. It was not long before Google Instant was introduced in 2010 as an example of how predictive algorithms were enhancing user experience by providing real-time search query suggestions. 

In the years that followed, artificial intelligence research and innovation became increasingly important, as evidenced by Google X's establishment in 2011 and DeepMind's strategic acquisition in 2014, pioneers in reinforcement learning that created the historic algorithm AlphaGo. A new wave of artificial intelligence has been sweeping across the globe since 2016 with Google Assistant and advanced tools like TensorFlow, which have democratized machine learning development. 

Breakthroughs such as Duplex have highlighted AI's increasing conversational sophistication, but most recently, Google's AI has embraced multimodal capabilities, which is why models like BERT, LaMDA, and PaLM are revolutionising language understanding and dialogue in a way previously unknown to the world. AI has a rich legacy that underscores its crucial role in driving Google’s transformation across search, creativity, and business solutions, underpinned by this legacy. 

As part of its annual developer conference in 2025, Google I/O reaffirmed its leadership in the rapidly developing field of artificial intelligence by unveiling an impressive lineup of innovations that promise to revolutionize the way people interact with technology, reaffirming its leadership in this field. In addition to putting a heavy emphasis on artificial intelligence-driven transformation, this year's event showcased next-generation models and tools that are far superior to the ones displayed in previous years. 

Among the announcements made by AI are the addition of AI assistants with deeper contextual intelligence, to the creation of entire videos with dialogue, which highlights a monumental leap forward in both the creative and cognitive capabilities of AI in general. It was this technological display that was most highlighted by the unveiling of Gemini 2.5, Google's most advanced artificial intelligence model. This model is positioned as the flagship model of the Gemini series, setting new industry standards for outstanding performance across key dimensions, such as reasoning, speed, and contextual awareness, which is among the most important elements of the model. 

The Gemini 2.5 model has outperformed its predecessors and rivals, including Google's own Gemini Flash, which has redefined expectations for what artificial intelligence can do. Among the model's most significant advantages is its enhanced problem-solving ability, which makes it far more than just a tool for retrieving information; it is also a true cognitive assistant because it provides precise, contextually-aware responses to complex and layered queries. 

 It has significantly enhanced capabilities, but it operates at a faster pace and with better efficiency, which makes it easier to integrate into real-time applications, from customer support to high-level planning tools, seamlessly. Additionally, the model's advanced understanding of contextual cues allows it to conduct intelligent, more coherent conversations, allowing it to feel more like a human being collaborating rather than interacting with a machine. This development marks a paradigm shift in artificial intelligence in addition to incremental improvements. 

It is a sign that artificial intelligence is moving toward a point where systems are capable of reasoning, adapting, and contributing in meaningful ways across the creative, technical, and commercial spheres. Google I/O 2025 serves as a preview of a future where AI will become an integral part of productivity, innovation, and experience design for digital creators, businesses, and developers alike. 

Google has announced that it is adding major improvements to its Gemini large language model lineup, which marks another major step forward in Google's quest to develop more powerful, adaptive artificial intelligence systems, building on the momentum of its breakthroughs in artificial intelligence. The new iterations, Gemini 2.5 Flash and Gemini 2.5 Pro, feature significant architectural improvements that aim to optimise performance across a wide range of uses. 

It will be available in early June 2025 in general availability as Gemini 2.5 Flash, a fast and lightweight processor designed for high-speed and lightweight use, and the more advanced Pro version will appear shortly afterwards as well. Among the most notable features of the Pro model is the introduction of “Deep Think” which provides advanced reasoning techniques to handle complex tasks using parallel processing techniques to handle complex issues. 

As a result of its inspiration from AlphaGo's strategic modelling, Deep Think gives AI the ability to simultaneously explore various solution paths, producing faster and more accurate results. With this capability, the model is well-positioned to offer a cutting-edge solution for reasoning at the highest level, mathematical analysis, and programming that meets the demands of competition. When Demiss Hassabis, CEO of Google DeepMind, held a press briefing to highlight the model's breakthrough performance, he highlighted its impressive performance on the USAMO 2025, a challenging math challenge that is a challenging one in the world, and LiveCodeBench, another benchmark that is a popular one in advanced coding.

A statement by Hassabis said, “Deep Think pushed the performance of models to the limit, resulting in groundbreaking results.” Google is adopting a cautious release strategy to comply with its commitment to ethical AI deployment. In order to ensure safety, reliability, and transparency, Deep Think will initially be accessible only to a limited number of trusted testers who will be able to provide feedback. 

In addition to demonstrating Google's intent to responsibly scale frontier AI capabilities, this deliberate rollout emphasises the importance of maintaining trust and control while showcasing the company's commitment to it. In addition to its creative AI capabilities, Google announced two powerful models for generative media during its latest announcements: Veo 3 for video generation and Imagen 4. These models represent significant breakthroughs in generative media technology. 

There has been a shift in artificial intelligence-assisted content creation in recent years, and these innovations provide creators with a much deeper, more immersive toolkit that allows them to tell visual and audio stories in a way that is truly remarkable in terms of realism and precision. Veo 3 represents a transformative leap in video generation technology, and for the first time, artificial intelligence-generated videos do not only comprise silent, motion-only clips anymore, but also provide a wide range of visual effects and effects. 

As a result of the integration of fully synchronised audio with Veo 3, the experience felt more like a real cinematic production than a simple algorithmic output, with ambient sounds, sound effects, and even real-time dialogue between characters, as it was in the original film. "For the first time in history, we are entering into a new era of video creation," said Demis Hassabis, CEO of Google DeepMind, highlighting how both the visual fidelity and the auditory depth of the new model were highlighted. As a result of these breakthroughs, Google has developed Flow, a new AI-powered filmmaking platform exclusively for creative professionals, which integrates these breakthroughs into Flow. 

Flow is Google's latest generative modelling tool that combines the most advanced models into an intuitive interface, so storytellers can design cinematic sequences with greater ease and fluidity than ever before. In Flow, the company claims it will recreate the intuitive, inspired creative process, where iteration feels effortless and ideas evolve in a way that is effortless and effortless. Flow has already been used by several filmmakers to create short films that illustrate the creative potential of the technology, combining Flow's capabilities with traditional methods to create the films.

Additionally, Imagen 4 is the latest update to Google's image generation model, offering extraordinary improvements in visual clarity, fine detail, and especially in typography and text rendering, as well as providing unparalleled advancements in visual clarity and fine detail. With these improvements, it has become a powerful tool for marketers, designers, and content creators who need to create beautiful visuals combining high-quality imagery with precise, readable text. 

The Imagen 4 platform is a significant step forward in advancing the quality of visual storytelling based on artificial intelligence, whether for branding, digital campaigns, or presentations. Despite fierce competition from leading technology companies, Google has made significant advancements in autonomous artificial intelligence agents at a time when the landscape of intelligent automation is rapidly evolving.

It is no secret that Microsoft's GitHub Copilot has already demonstrated how powerful AI-driven development assistants can be, but OpenAI's CodeX platform continues to push the boundaries of what AI has to offer. It is in this context that Google introduced innovative tools like Stitch and Jules that could generate a complete website, a codebase, and a user interface automatically without any human input. These tools signal a revolution in how software developers develop and create digital content. A convergence of autonomous artificial intelligence technologies from a variety of industry giants underscores a trend towards automating increasingly complex knowledge tasks. 

Through the use of these AI systemorganisationsons can respond quickly to changing market demands and evolving consumer preferences by providing real-time recommendations and dynamic adjustments. Through such responsiveness, an organisation is able to optimise operational efficiency, maximise resource utilisation, and create sustainable growth by ensuring that the company remains tightly aligned with its strategic goals. AI provides businesses with actionable insights that enable them to compete more effectively in an increasingly complex and fast-paced market place by providing actionable insights. 

Aside from software and business applications, Google's AI innovations also have great potential to have a dramatic impact on the healthcare sector, where advancements in diagnostic accuracy and personalised treatment planning have the potential to greatly improve the outcomes for patients. Furthermore, improvements in the field of natural language processing and multimodal interaction models will help provide more intuitive, accessible and useful user interfaces for users from diverse backgrounds, thus reducing barriers to adoption and enabling them to make the most of technology. 

In the future, when artificial intelligence becomes an integral part of today's everyday lives, its influence will be transformative, affecting industries, redefining workflows, and generating profound social effects. The fact that Google leads the way in this space not only implies a future where artificial intelligence will augment human capabilities, but it also signals the arrival of a new era of progress in science, economics, and culture as a whole.
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Hackers
Cactus ransomware Cyber crimes elastic Google Hackers

Cybercriminals Are Dividing Tasks — Why That’s a Big Problem for Cybersecurity Teams

 



Cyberattacks aren’t what they used to be. Instead of one group planning and carrying out an entire attack, today’s hackers are breaking the process into parts and handing each step to different teams. This method, often seen in cybercrime now, is making it more difficult for security experts to understand and stop attacks.

In the past, cybersecurity analysts looked at threats by studying them as single operations done by one group with one goal. But that method is no longer enough. These days, many attackers specialize in just one part of an attack—like finding a way into a system, creating malware, or demanding money—and then pass on the next stage to someone else.

To better handle this shift, researchers from Cisco Talos, a cybersecurity team, have proposed updating an older method called the Diamond Model. This model originally focused on four parts of a cyberattack: the attacker, the target, the tools used, and the systems involved. The new idea is to add a fifth layer that shows how different hacker groups are connected and work together, even if they don’t share the same goals.

By tracking relationships between groups, security teams can better understand who is doing what, avoid mistakes when identifying attackers, and spot patterns across different incidents. This helps them respond more accurately and efficiently.

The idea of cybercriminals selling services isn’t new. For years, online forums have allowed criminals to buy and sell services—like renting out access to hacked systems or offering ransomware as a package. Some of these relationships are short-term, while others involve long-term partnerships where attackers work closely over time.

In one recent case, a group called ToyMaker focused only on breaking into systems. They then passed that access to another group known as Cactus, which launched a ransomware attack. This type of teamwork shows how attackers are now outsourcing parts of their operations, which makes it harder for investigators to pin down who’s responsible.

Other companies, like Elastic and Google’s cyber threat teams, have also started adapting their systems to deal with this trend. Google, for example, now uses separate labels to track what each group does and what motivates them—whether it's financial gain, political beliefs, or personal reasons. This helps avoid confusion when different groups work together for different reasons.

As cybercriminals continue to specialize, defenders will need smarter tools and better models to keep up. Understanding how hackers divide tasks and form networks may be the key to staying one step ahead in this ever-changing digital battlefield.

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update
AFU Android auto-restart BFU Data Encryption Google Pin Privacy reboot Security Smartphone update

Google’s New Android Security Update Might Auto-Reboot Your Phone After 3 Days

 

In a recent update to Google Play Services, the tech giant revealed a new security feature that could soon reboot your Android smartphone automatically — and this move could actually boost your device’s safety.

According to the update, Android phones left unused for three consecutive days will automatically restart. While this might sound intrusive at first, the reboot comes with key security benefits.

There are two primary reasons why this feature is important:

First, after a reboot, the only way to unlock a phone is by entering the PIN — biometric options like fingerprint or facial recognition won’t work until the PIN is input manually. This ensures added protection, especially for users who haven’t set up any screen lock. A forced PIN entry makes it much harder for unauthorized individuals to access your device or the data on it.

Second, the update enhances encryption security. Android devices operate in two states: Before First Unlock (BFU) and After First Unlock (AFU). In the BFU state, your phone’s contents are completely encrypted, meaning that even advanced tools can’t extract the data.

This security measure also affects how law enforcement and investigative agencies handle seized phones. Since the BFU state kicks in automatically after a reboot, authorities have a limited window to access a device before it locks down data access completely.

“A BFU phone remains connected to Wi-Fi or mobile data, meaning that if you lose your phone and it reboots, you'll still be able to use location-finding services.”

The feature is listed in Google’s April 2025 System release notes, and while it appears to extend to Android tablets, it won’t apply to wearables like the Pixel Watch, Android Auto, or Android TVs.

As of now, Google hasn’t clarified whether users will have the option to turn off this feature or customize the three-day timer.

Because it’s tied to Google Play Services, users will receive the feature passively — there’s no need for a full system update to access it.
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User Privacy
Data Breach Google Privacy Lawsuit Texas User Privacy

Google to Pay Texas $1.4 Billion For Collecting Personal Data

 

The state of Texas has declared victory after reaching a $1 billion-plus settlement from Google parent firm Alphabet over charges that it illegally tracked user activity and collected private data. 

Texas Attorney General Ken Paxton announced the state's highest sanctions to date against the tech behemoth for how it manages the data that people generate when they use Google and other Alphabet services. 

“For years, Google secretly tracked people’s movements, private searches, and even their voiceprints and facial geometry through their products and services. I fought back and won,” Paxton noted in a May 9 statement announcing the settlement.

“This $1.375 billion settlement is a major win for Texans’ privacy and tells companies that they will pay for abusing our trust. I will always protect Texans by stopping Big Tech’s attempts to make a profit by selling away our rights and freedoms.”

The dispute dates back to 2022, when the Texas Attorney General's Office filed a complaint against Google and Alphabet, saying that the firm was illegally tracking activities, including Incognito searches and geolocation. The state also claimed that Google and Alphabet acquired biometric information from consumers without their knowledge or consent. 

According to Paxton's office, the Texas settlement is by far the highest individual penalty imposed on Google for alleged user privacy violations and data collecting, with the previous high being a $341 million settlement with a coalition of 41 states in a collective action. 

The AG's office declined to explain how the funds will be used. However, the state maintains a transparency webpage that details the programs it funds through penalties. The settlement is not the first time Google has encountered regulatory issues in the Lone Star State. 

The company previously agreed to pay two separate penalties of $8 million and $700 million in response to claims that it used deceptive marketing techniques and violated anti-competitive laws. 

Texas also went after other tech behemoths, securing a $1.4 billion settlement from Facebook parent firm Meta over allegations that it misused data and misled its customers about its data gathering and retention practices. 

The punitive restrictions are not uncommon in Texas, which has a long history of favouring and protecting major firms through legislation and legal policy. Larger states, such as Texas, can also have an impact on national policy and company decisions due to their population size.
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Scams
Data Breach express VPN Google Online Personal Information Scams

This Free Tool Helps You Find Out if Your Personal Information Is Exposed Online

 


Many people don't realize how much of their personal data is floating around the internet. Even if you're careful and don’t use the internet much, your information like name, address, phone number, or email could still be listed on various websites. This can lead to annoying spam or, in serious cases, scams and fraud.

To help people become aware of this, ExpressVPN has created a free tool that lets you check where your personal information might be available online.


How the Tool Works

Using the tool is easy. You just enter your first and last name, age, city, and state. Once done, the tool scans 68 websites that collect and sell user data. These are called data broker sites.

It then shows whether your details, such as phone number, email address, location, or names of your relatives, appear on those sites. For example, one person searched their legal name and only one result came up. But when they searched the name they usually use online, many results appeared. This shows that the more you interact online, the more your data might be exposed.


Ways to Remove Your Data

The scan is free, but if you want the tool to remove your data, it offers a paid option. However, there are free ways to remove your information by yourself.

Most data broker sites have a page where you can ask them to delete your data. These pages are not always easy to find and often have names like “Opt-Out” or “Do Not Sell My Info.” But they are available and do work if you take the time to fill them out.

You can also use a feature from Google that allows you to request the removal of your personal data from its search results. This won’t delete the information from the original site, but it will make it harder for others to find it through a search engine. You can search for your name along with the site’s name and then ask Google to remove the result.


Other Tools That Can Help

If you don’t want to do this manually, there are paid services that handle the removal for you. These tools usually cost around $8 per month and can send deletion requests to hundreds of data broker sites.

It’s important to know what personal information of yours is available online. With this free tool from ExpressVPN, you can quickly check and take steps to protect your privacy. Whether you choose to handle removals yourself or use a service, taking action is a smart step toward keeping your data safe.

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Screenshots
Cybersecurity geographic Google Google Maps Google Security Tools location data breach Maps Privacy Scan Threat Screenshots

Google Now Scans Screenshots to Identify Geographic Locations

 


With the introduction of a new feature within Google Maps that is already getting mixed reviews from users, this update is already making headlines around the world. Currently available on iPhones, this update allows users to scan screenshots and photographs to identify and suggest places in real time. 

However, even though the technology has the potential to make life easier, such as helping users remember places they have visited or discovering new destinations, it raises valid privacy concerns as well. Even though it is a feature powered by artificial intelligence, there is not much clarity about its exact mechanism. However, it is known that the system analyses the content of images, which is a process involving the transmission of user data across multiple servers, including personal photos. 

Currently, the feature is exclusive to iOS devices, with Android support coming shortly afterwards -- an interesting delaybecauset Android is Google's native operating system. In fact, iPhone users have already been able to test it out by uploading older images to Google Maps and comparing them with locations that they know. 

As the update gains traction, it is likely to generate a lot of discussion regarding its usefulness and ethical implications. It has been reported that Google Maps has launched a new feature to streamline the user experience by making it easier for users to search for locations. Its functionality is currently available only for iPhones, but will soon be available for other devices as well. It allows the app to automatically detect and extract location information from screenshots taken from the device, such as the name of the place or address. 

As the location is identified, it is added to a personalised list, which allows users to return to those locations without having to type in the details manually. There is a particular benefit to using this enhancement for users who frequently take screenshots of places they intend to visit in the future, either from messages they receive from their friends and family, or from social media. As a result of this update, users no longer have to switch between their phone’s gallery and the Maps app manually to search for these places. This makes the process more seamless and intuitive since this friction has been eliminated. 

It is worth mentioning that Google's approach reflects a larger push toward automated convenience, but it also comes with several concerns about data usage and user consent in regards to this approach. In Google's opinion, the motivation behind this feature stems from a problem that many travellers face when researching destinations: keeping track of screenshots they have taken from travel blogs, social media posts, or news articles.

In most cases, these valuable bits of information get lost in the camera roll, which makes it difficult to recall or retrieve them when they are needed. This is an issue that Google is looking to address by improving the efficiency and stress of trip planning. Added to Google Maps' seamless way of surface-saving spots, users will never miss out on a must-visit location simply because it was buried among other images. 

When users authorize the app to access their photo library, it scans screenshots for recognizable place names and addresses and instantly lets them know if they do. If a location is able to be recognized successfully, the app will prompt the user, telling them that the place can now be reviewed and saved if the user wants to. With the advent of this functionality, what once existed only as a passive image archive will soon become an interactive tool for travel planning, providing both convenience and personal navigation. 

Firstly, users must ensure that on their iPhone or iPad device that Google Maps is updated to its latest version if they intend to take full advantage of this innovative feature. Once the app is up to date, the transition from screenshot to saved destination becomes almost effortless. By simply capturing screenshots of websites mentioning travel destinations, whether they come from blogs, articles, or curated recommendations lists, the app can recognize and retrieve valuable location information by simply taking screenshots. 

At the bottom of the screen, there is a new "Screenshots" tab, which appears prominently under the "You" section within the updated interface. The first time a user accesses this section for the first time, they are given a short overview of the functionality, and then they are prompted to grant the app access to the photo gallery of the device. Allowing the app to access this photo gallery allows it to use intelligence to scan for place names and landmarks in the images. 

Once Google Maps has been able to recognise a location within a screenshot, it will begin analysing the images to identify relevant geographical information embedded within them. By simply clicking on the “Scan screenshots” button, Google Maps immediately begins analysing your stored screenshots. Recognised locations are neatly organised into a list, allowing for selective curation. Once confirmed, these places are added to a custom list within the app once confirmed. 

Each additional location becomes a central hub, offering visuals, descriptions, navigation options, and the possibility of organising them into favourites or themed lists, allowing for easy organisation. The static images that once resided in the camera roll are now transformed into a dynamic planning tool that can be accessed from anywhere. The clever combination of AI and user behavior illustrates how technology can elevate everyday habits into smarter, more intuitive experiences by incorporating AI into everyday experiences.

As a further step toward making Google Maps a hands-off experience, you can also set it up so that it will automatically scan any future screenshots you take. With access to the entire photo library, the app continuously monitors and detects new screenshots that contain location information. It then places them directly into the “Screenshots” section without having to do any manual work at all. 

Users have the option of switching this feature on or off at any time, thus giving them complete control over how much of their photo content is being analyzed at any given time. Additionally, if you would rather take a more selective approach, the feature allows you to choose specific images to scan manually, which allows you to make the most of the available features.

In this way, users can take advantage of the convenience of the tool while maintaining their level of privacy and control as artificial intelligence continues to shape our everyday digital experiences, and the new Google Maps feature stands out as one of the best examples of how to combine automation with the ability to control it. 

A smarter, more intuitive way of planning and exploring is created by turning passive screenshots into actionable insights – allowing you to discover, save, and revisit locations in a more intuitive way. This latest update marks a significant milestone in Google Maps' evolution toward smarter, more intuitive navigation tools. By bridging visual content with location intelligence, it creates an enhanced user experience that aligns with the rising demand for efficiency and automation in the industry. 

The rise of artificial intelligence continues to shape the way digital platforms function. Features like screenshot scanning emphasize the necessity to maintain user control while enhancing convenience as a result of thoughtful innovation. As a result of this upgrade, both users and industry professionals will be able to enjoy seamless, context-aware travel planning, which is a reflection of the future.
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Technology
AI AI Chatbot Chatbot Gemini Google Technology

Google to Launch Gemini AI for Children Under 13

Google to Launch Gemini AI for Children Under 13

Google plans to roll out its Gemini artificial intelligence chatbot next week for children younger than 13 with parent-managed Google accounts, as tech companies vie to attract young users with AI products.

Google will launch its Gemini AI chatbot soon for children below the age of 13 with parent-managed Google accounts. The move comes as tech companies try to attract young users with AI tools. According to a mail sent to a parent of an 8-year-old, Google apps will soon be available to a child. It means your child can use Gemini to ask questions, get homework help, and also create stories. 

That chatbot will be available to children whose guardians have Family Link, a Google feature that allows families to make Gmail and opt-in services like YouTube for their children. To register a child account, the parent gives the tech company the child’s personal information such as name and date of birth. 

According to Google spokesperson Karl Ryan, Gemini has concrete measures for younger users to restrict the chatbot from creating unsafe or harmful content. If a child with a Family Link account uses Gemini, the company can not use the data for training its AI model. 

Gemini for children can drive the use of chatbots among vulnerable populations as companies, colleges, schools, and others struggle with the effects of popular gen AI tech. The systems are trained on massive amounts of data sets to create human-like text and realistic images and videos. Google and other AI chatbot developers are battling fierce competition to get young users’ attention. 

Recently, President Donald Trump requested schools to embrace tools for teaching and learning. Millions of teens are already using chatbots for study help, virtual companions, and writing coaches. Experts have warned that chatbots could pose serious threats to child safety. 

The bots are known to sometimes make things up. UNICEF and other children's advocacy groups have found that AI systems can misinform, manipulate, and confuse young children who may face difficulties understanding that the chatbots are not humans. 

According to UNICEF’s global research office, “Generative AI has produced dangerous content,” posing risks for children. Google has acknowledged some risks, cautioning parents that “Gemini can make mistakes” and suggesting they “help your child think critically” about the chatbot. 

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USB Charging
Apple Google Juice Jacking Samsung Technology USB Charging

Do Not Charge Your Phone at Public Stations, Experts Warn

Do Not Charge Your Phone at Public Stations, Experts Warn

For a long time, smartphones have had a built-in feature that saves us against unauthorized access through USB. In Android and iOS, pop-ups ask us to confirm access before a data USB connection is established to transfer our data. 

But this defense is not enough to protect against “juice-jacking” — a hacking technique that manipulates charging stations to install malicious code, steal data, or enable access to the device while plugged in. Experts have found a severe flaw in this system that hackers can exploit easily. 

Cybersecurity researchers have discovered a serious loophole in this system that can be easily exploited. 

Hackers using new technique to hack smartphones via USB

According to experts, hackers can now use a new method called “choice jacking” to make sure that access to smartphones is easily verified without the user realizing it. 

First, the hackers deploy a feature on a charging station so that it looks like a USB keyboard when connected. After that, through USB Power Delivery, it runs a “USB PD Data Role Swap” to make a Bluetooth connection, activating the file transfer consent pop-up, and approving permission while acting as a Bluetooth keyboard. 

The hackers leverage the charging station to evade the protection mechanism on the device, which is aimed at protecting users against hacking attacks with USB peripherals. This can become a serious issue if the hacker gets access to all files and personal data stored on our smartphones to hack accounts. 

Experts at Graz University of Technology tried this technique on devices from a lot of manufacturers such as Samsung, which sells the second most smartphones besides Apple. All tested smartphones allowed the researchers to transfer data during the duration the screen was unlocked. 

No solution to this problem

Despite smartphone manufacturers being aware of the problem, there are not enough safety measures against juice-jacking, Only Google and Apply have implemented a solution, which requires users first to provide their PIN or password before they can use a device as authorized start and begin the data transfer. But, other manufacturers have not come up with efficient solutions to address this issue and offer protection.

If your smartphone has USB debugging enabled, it can be dangerous as USB debugging allows hackers to get access to the device via the Android Debug Bridge and deploy their own apps, run files, and generally use a higher access mode. 

How to be safe?

The easiest way users can protect themselves from juice-jacking attacks through USB charging stations is to never use a public charging station. Users should always avoid charging stations in busy areas such as airports and malls, they are the most dangerous. 

Users are advised to carry their power banks when traveling and always keep their smartphones updated.

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Mandiant
Campaigns Cloud Cyber Security Data Google Mandiant

New Report Reveals Hackers Now Aim for Money, Not Chaos

New Report Reveals Hackers Now Aim for Money, Not Chaos

Recent research from Mandiant revealed that financially motivated hackers are the new trend, with more than (55%) of criminal gangs active in 2024 aiming to steal or extort money from their targets, a sharp rise compared to previous years. 

About the report

The main highlight of the M-Trends report is that hackers are using every opportunity to advance their goals, such as using infostealer malware to steal credentials. Another trend is attacking unsecured data repositories due to poor security hygiene. 

Hackers are also exploiting fractures and risks that surface when an organization takes its data to the cloud. “In 2024, Mandiant initiated 83 campaigns and five global events and continued to track activity identified in previous years. These campaigns affected every industry vertical and 73 countries across six continents,” the report said. 

Ransomware-related attacks accounted for 21% of all invasions in 2024 and comprised almost two-thirds of cases related to monetization tactics. This comes in addition to data theft, email hacks, cryptocurrency scams, and North Korean fake job campaigns, all attempting to get money from targets. 

Exploits were amid the most popular primary infection vector at 33%, stolen credentials at 16%, phishing at 14%, web compromises at 9%, and earlier compromises at 8%. 

Finance in danger

Finance topped in the targeted industry, with more than 17% of attacks targeting the sector, followed closely by professional services and business (11%), critical industries such as high tech (10%), governments (10%), and healthcare (9%). 

Experts have highlighted a broader target of various industries, suggesting that anyone can be targeted by state-sponsored attacks, either politically or financially motivated.  

Stuart McKenzie, Managing Director, Mandiant Consulting EMEA. said “Financially motivated attacks are still the leading category. “While ransomware, data theft, and multifaceted extortion are and will continue to be significant global cybercrime concerns, we are also tracking the rise in the adoption of infostealer malware and the developing exploitation of Web3 technologies, including cryptocurrencies.” 

He also stressed that the “increasing sophistication and automation offered by artificial intelligence are further exacerbating these threats by enabling more targeted, evasive, and widespread attacks. Organizations need to proactively gather insights to stay ahead of these trends and implement processes and tools to continuously collect and analyze threat intelligence from diverse sources.”

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Sandboxing
Cookies data security Google Google Chrome Google Chrome browser Google Chrome security Privacy Privacy Sandbox Sandboxing

Google Ends Privacy Sandbox, Keeps Third-Party Cookies in Chrome

 

Google has officially halted its years-long effort to eliminate third-party cookies from Chrome, marking the end of its once-ambitious Privacy Sandbox project. In a recent announcement, Anthony Chavez, VP of Privacy Sandbox, confirmed that the browser will continue offering users the choice to allow or block third-party cookies—abandoning its previous commitment to remove them entirely. 

Launched in 2020, Privacy Sandbox aimed to overhaul the way user data is collected and used for digital advertising. Instead of tracking individuals through cookies, Google proposed tools like the Topics API, which categorized users based on web behavior while promising stronger privacy protections. Despite this, critics claimed the project would ultimately serve Google’s interests more than users’ privacy or industry fairness. Privacy groups like the Electronic Frontier Foundation (EFF) warned users that the Sandbox still enabled behavioral tracking, and urged them to opt out. Meanwhile, regulators on both sides of the Atlantic scrutinized the initiative. 

In the UK, the Competition and Markets Authority (CMA) investigated the plan over concerns it would restrict competition by limiting how advertisers access user data. In the US, a federal judge recently ruled that Google engaged in deliberate anticompetitive conduct in the ad tech space—adding further pressure on the company. Originally intended to bring Chrome in line with browsers like Safari and Firefox, which block third-party cookies by default, the Sandbox effort repeatedly missed deadlines. In 2023, Google shifted its approach, saying users would be given the option to opt in rather than being automatically transitioned to the new system. Now, it appears the initiative has quietly folded. 

In his statement, Chavez acknowledged ongoing disagreements among advertisers, developers, regulators, and publishers about how to balance privacy with web functionality. As a result, Google will no longer introduce a standalone prompt to disable cookies and will instead continue with its current model of user control. The Movement for an Open Web (MOW), a vocal opponent of the Privacy Sandbox, described Google’s reversal as a victory. “This marks the end of their attempt to monopolize digital advertising by removing shared standards,” said MOW co-founder James Rosewell. “They’ve recognized the regulatory roadblocks are too great to continue.” 

With Privacy Sandbox effectively shelved, Chrome users will retain the ability to manage cookie preferences—but the web tracking status quo remains firmly in place.
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WhatsApp
AI tools Gmail Google Privacy WhatsApp

Gmail Users Face a New Dilemma Between AI Features and Data Privacy

 



Google’s Gmail is now offering two new upgrades, but here’s the catch— they don’t work well together. This means Gmail’s billions of users are being asked to pick a side: better privacy or smarter features. And this decision could affect how their emails are handled in the future.

Let’s break it down. One upgrade focuses on stronger protection of your emails, which works like advanced encryption. This keeps your emails private, even Google won’t be able to read them. The second upgrade brings in artificial intelligence tools to improve how you search and use Gmail, promising quicker, more helpful results.

But there’s a problem. If your emails are fully protected, Gmail’s AI tools can’t read them to include in its search results. So, if you choose privacy, you might lose out on the benefits of smarter searches. On the other hand, if you want AI help, you’ll need to let Google access more of your email content.

This challenge isn’t unique to Gmail. Many tech companies are trying to combine stronger security with AI-powered features, but the two don’t always work together. Apple tried solving this with a system that processes data securely on your device. However, delays in rolling out their new AI tools have made their solution uncertain for now.

Some reports explain the choice like this: if you turn on AI features, Google will use your data to power smart tools. If you turn it off, you’ll have better privacy, but lose some useful options. The real issue is that opting out isn’t always easy. Some settings may remain active unless you manually turn them off, and fully securing your emails still isn’t simple.

Even when extra security is enabled, email systems have limitations. For example, Apple’s iCloud Mail doesn’t use full end-to-end encryption because it must work with global email networks. So even private emails may not be completely safe.

This issue goes beyond Gmail. Other platforms are facing similar challenges. WhatsApp, for example, added a privacy mode that blocks saving chats and media, but also limits AI-related features. OpenAI’s ChatGPT can now remember what you told it in past conversations, which may feel helpful but also raises questions about how your personal data is being stored.

In the end, users need to think carefully. AI tools can make email more useful, but they come with trade-offs. Email has never been a perfectly secure space, and with smarter AI, new threats like scams and data misuse may grow. That’s why it’s important to weigh both sides before making a choice.



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Salt Typhoon
Android Cyber Security Google messages RCS Salt Typhoon

Google Plans Big Messaging Update for Android Users

 



Google is preparing a major upgrade to its Messages app that will make texting between Android and iPhone users much smoother and more secure. For a long time, Android and Apple phones haven’t worked well together when it comes to messaging. But this upcoming change is expected to improve the experience and add strong privacy protections.


New Messaging Technology Called RCS

The improvement is based on a system called RCS, short for Rich Communication Services. It’s a modern replacement for traditional SMS texting. This system adds features like read receipts, typing indicators, and high-quality image sharing—all without needing third-party apps. Most importantly, RCS supports encryption, which means messages can be protected and private.

Recently, the organization that decides how mobile networks work— the GSMA announced support for RCS as the new standard. Both Google and Apple have agreed to upgrade their messaging apps to match this system, allowing Android and iPhone users to send safer, encrypted messages to each other for the first time.


Why Is This Important Now?

The push for stronger messaging security comes after several cyberattacks, including a major hacking campaign by Chinese groups known as "Salt Typhoon." These hackers broke into American networks and accessed sensitive data. Events like this have raised concerns about weak security in regular text messaging. Even the FBI advised people not to use SMS for sharing personal or financial details.


What’s Changing in Google Messages?

As part of this shift, Google is updating its Messages app to make it easier for users to see which contacts are using RCS. In a test version of the app, spotted by Android Authority, Google is adding new features that label contacts based on whether they support RCS. The contact list may also show different colors to make RCS users stand out.

At the moment, there’s no clear way to know whether a chat will use secure RCS or fallback SMS. This update will fix that. It will even help users identify if someone using an iPhone has enabled RCS messaging.


A More Secure Future for Messaging

Once this update is live, Android users will have a messaging app that better matches Apple’s iMessage in both features and security. It also means people can communicate across platforms without needing apps like WhatsApp or Signal. With both Google and Apple on board, RCS could soon become the standard way we all send safe and reliable text messages.


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Technology
AI AI Training Artificial Intelligence ChatGPT Cybersecurity Google IT OpenAI Technology

Building Smarter AI Through Targeted Training


 

In recent years, artificial intelligence and machine learning have been in high demand across a broad range of industries. As a consequence, the cost and complexity of constructing and maintaining these models have increased significantly. Artificial intelligence and machine learning systems are resource-intensive, as they require substantial computation resources and large datasets, and are also difficult to manage effectively due to their complexity. 

As a result of this trend, professionals such as data engineers, machine learning engineers, and data scientists are increasingly being tasked with identifying ways to streamline models without compromising performance or accuracy, which in turn will lead to improved outcomes. Among the key aspects of this process involves determining which data inputs or features can be reduced or eliminated, thereby making the model operate more efficiently. 

In AI model optimization, a systematic effort is made to improve a model's performance, accuracy, and efficiency to achieve superior results in real-world applications. The purpose of this process is to improve a model's operational and predictive capabilities through a combination of technical strategies. It is the engineering team's responsibility to improve computational efficiency—reducing processing time, reducing resource consumption, and reducing infrastructure costs—while also enhancing the model's predictive precision and adaptability to changing datasets by enhancing the model's computational efficiency. 

An important optimization task might involve fine-tuning hyperparameters, selecting the most relevant features, pruning redundant elements, and making advanced algorithmic adjustments to the model. Ultimately, the goal of modeling is not only to provide accurate and responsive data, but also to provide scalable, cost-effective, and efficient data. As long as these optimization techniques are applied effectively, they ensure the model will perform reliably in production environments as well as remain aligned with the overall objectives of the organization. 

It is designed to retain important details and user preferences as well as contextually accurate responses when ChatGPT's memory feature is enabled, which is typically set to active by default so that the system can provide more personalized responses over time. If the user desires to access this functionality, he or she can navigate to the Settings menu and select Personalization, where they can check whether memory is active and then remove specific saved interactions if needed. 

As a result of this, it is recommended that users periodically review the data that has been stored within the memory feature to ensure its accuracy. In some cases, incorrect information may be retained, including inaccurate personal information or assumptions made during a previous conversation. As an example, in certain circumstances, the system might incorrectly log information about a user’s family, or other aspects of their profile, based on the context in which it is being used. 

In addition, the memory feature may inadvertently store sensitive data when used for practical purposes, such as financial institutions, account details, or health-related queries, especially if users are attempting to solve personal problems or experiment with the model. It is important to remember that while the memory function contributes to improved response quality and continuity, it also requires careful oversight from the user. There is a strong recommendation that users audit their saved data points routinely and delete the information that they find inaccurate or overly sensitive. This practice helps maintain the accuracy of data, as well as ensure better, more secure interactions. 

It is similar to clearing the cache of your browser periodically to maintain your privacy and performance optimally. "Training" ChatGPT in terms of customized usage means providing specific contextual information to the AI so that its responses will be relevant and accurate in a way that is more relevant to the individual. ITGuides the AI to behave and speak in a way that is consistent with the needs of the users, users can upload documents such as PDFs, company policies, or customer service transcripts. 

When people and organizations can make customized interactions for business-related content and customer engagement workflows, this type of customization provides them with more customized interactions. It is, however, often unnecessary for users to build a custom GPT for personal use in the majority of cases. Instead, they can share relevant context directly within their prompts or attach files to their messages, thereby achieving effective personalization. 

As an example, a user can upload their resume along with a job description when crafting a job application, allowing artificial intelligence to create a cover letter based on the resume and the job description, ensuring that the cover letter accurately represents the user's qualifications and aligns with the position's requirements. As it stands, this type of user-level customization is significantly different from the traditional model training process, which requires large quantities of data to be processed and is mainly performed by OpenAI's engineering teams. 

Additionally, ChatGPT users can increase the extent of its memory-driven personalization by explicitly telling it what details they wish to be remembered, such as their recent move to a new city or specific lifestyle preferences, like dietary choices. This type of information, once stored, allows the artificial intelligence to keep a consistent conversation going in the future. Even though these interactions enhance usability, they also require thoughtful data sharing to ensure privacy and accuracy, especially as ChatGPT's memory is slowly swelled over time. 

It is essential to optimize an AI model to improve performance as well as resource efficiency. It involves refining a variety of model elements to maximize prediction accuracy and minimize computational demand while doing so. It is crucial that we remove unused parameters from networks to streamline them, that we apply quantization to reduce data precision and speed up processing, and that we implement knowledge distillation, which translates insights from complex models to simpler, faster models. 

A significant amount of efficiency can be achieved by optimizing data pipelines, deploying high-performance algorithms, utilizing hardware accelerations such as GPUs and TPUs, and employing compression techniques such as weight sharing, low-rank approximation, and optimization of the data pipelines. Also, balancing batch sizes ensures the optimal use of resources and the stability of training. 

A great way to improve accuracy is to curate clean, balanced datasets, fine-tune hyperparameters using advanced search methods, increase model complexity with caution and combine techniques like cross-validation and feature engineering with the models. Keeping long-term performance high requires not only the ability to learn from pre-trained models but also regular retraining as a means of combating model drift. To enhance the scalability, cost-effectiveness, and reliability of AI systems across diverse applications, these techniques are strategically applied. 

Using tailored optimization solutions from Oyelabs, organizations can unlock the full potential of their AI investments. In an age when artificial intelligence is continuing to evolve rapidly, it becomes increasingly important to train and optimize models strategically through data-driven optimization. There are advanced techniques that can be implemented by organizations to improve performance while controlling resource expenditures, from selecting features and optimizing algorithms to efficiently handling data. 

As professionals and teams that place a high priority on these improvements, they will put themselves in a much better position to create AI systems that are not only faster and smarter but are also more adaptable to the daily demands of the world. Businesses are able to broaden their understanding of AI and improve their scalability and long-term sustainability by partnering with experts and focusing on how AI achieves value-driven outcomes.
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Technology
Amazon Artificial Intelligence ChatGPT Cybersecurity CyberThreat Google GTI Microsoft New Sec Gemini OpenAI Technology

New Sec-Gemini v1 from Google Outperforms Cybersecurity Rivals

 


A cutting-edge artificial intelligence model developed by Google called Sec-Gemini v1, a version of Sec-Gemini that integrates advanced language processing, real-time threat intelligence, and enhanced cybersecurity operations, has just been released. With the help of Google's proprietary Gemini large language model and dynamic security data and tools, this innovative solution utilizes its capabilities seamlessly to enhance security operations. 

A new AI model, Sec-Gemini v1 that combines sophisticated reasoning with real-time cybersecurity insights and tools has been released by Google. This integration makes the model extremely capable of performing essential security functions like threat detection, vulnerability assessment, and incident analysis. A key part of Google's effort to support progress across the broader security landscape is its initiative to provide free access to Sec-Gemini v1 to select institutions, professionals, non-profit organizations, and academic institutions to promote a collaborative approach to security research. 

Due to its integration with Google Threat Intelligence (GTI), the Open Source Vulnerabilities (OSV) database, and other key data sources, Sec-Gemini v1 stands out as a unique solution. On the CTI-MCQ threat intelligence benchmark and the CTI-Root Cause Mapping benchmark, it outperforms peer models by at least 11%, respectively. Using the CWE taxonomy, this benchmark assesses the model's ability to analyze and classify vulnerabilities.

One of its strongest features is accurately identifying and describing the threat actors it encounters. Because of its connection to Mandiant Threat Intelligence, it can recognize Salt Typhoon as a known adversary, which is a powerful feature. There is no doubt that the model performs better than its competitors based on independent benchmarks. According to a report from Security Gemini v1, compared to comparable AI systems, Sec-Gemini v1 scored at least 11 per cent higher on CTI-MCQ, a key metric used to assess threat intelligence capabilities. 

Additionally, it achieved a 10.5 per cent edge over its competitors in the CTI-Root Cause Mapping benchmark, a test that assesses the effectiveness of an AI model in interpreting vulnerability descriptions and classifying them by the Common Weakness Enumeration framework, an industry standard. It is through this advancement that Google is extending its leadership position in artificial intelligence-powered cybersecurity, by providing organizations with a powerful tool to detect, interpret, and respond to evolving threats more quickly and accurately. 

It is believed that Sec-Gemini v1 has the strength to be able to perform complex cybersecurity tasks efficiently, according to Google. Aside from conducting in-depth investigations, analyzing emerging threats, and assessing the impact of known vulnerabilities, you are also responsible for performing comprehensive incident investigations. In addition to accelerating decision-making processes and strengthening organization security postures, the model utilizes contextual knowledge in conjunction with technical insights to accomplish the objective. 

Though several technology giants are actively developing AI-powered cybersecurity solutions—such as Microsoft's Security Copilot, developed with OpenAI, and Amazon's GuardDuty, which utilizes machine learning to monitor cloud environments—Google appears to have carved out an advantage in this field through its Sec-Gemini v1 technology. 

A key reason for this edge is the fact that it is deeply integrated with proprietary threat intelligence sources like Google Threat Intelligence and Mandiant, as well as its remarkable performance on industry benchmarks. In an increasingly competitive field, these technical strengths place it at the top of the list as a standout solution. Despite the scepticism surrounding the practical value of artificial intelligence in cybersecurity - often dismissed as little more than enhanced assistants that still require a lot of human interaction - Google insists that Sec-Gemini v1 is fundamentally different from other artificial intelligence models out there. 

The model is geared towards delivering highly contextual, actionable intelligence rather than simply summarizing alerts or making basic recommendations. Moreover, this technology not only facilitates faster decision-making but also reduces the cognitive load of security analysts. As a result, teams can respond more quickly to emerging threats in a more efficient way. At present, Sec-Gemini v1 is being made available exclusively as a research tool, with access being granted only to a select set of professionals, academic institutions, and non-profit organizations that are willing to share their findings. 

There have been early signs that the model will make a significant contribution to the evolution of AI-driven threat defence, as evidenced by the model's use-case demonstrations and early results. It will introduce a new era of proactive cyber risk identification, contextualization, and mitigation by enabling the use of advanced language models. 

In real-world evaluations, the Google security team demonstrated Sec-Gemini v1's advanced analytical capabilities by correctly identifying Salt Typhoon, a recognized threat actor, with its accurate analytical capabilities. As well as providing in-depth contextual insights, the model provided in-depth contextual information, including vulnerability details, potential exploitation techniques, and associated risk levels. This level of nuanced understanding is possible because Mandiant's threat intelligence provides a rich repository of real-time threat data as well as adversary profiles that can be accessed in real time. 

The integration of Sec-Gemini v1 into other systems allows Sec-Gemini v1 to go beyond conventional pattern recognition, allowing it to provide more timely threat analysis and faster, evidence-based decision-making. To foster collaboration and accelerate model refinement, Google has offered limited access to Sec-Gemini v1 to a carefully selected group of cybersecurity practitioners, academics, and non-profit organizations to foster collaboration. 

To avoid a broader commercial rollout, Google wishes to gather feedback from trusted users. This will not only ensure that the model is more reliable and capable of scaling across different use cases but also ensure that it is developed in a responsible and community-led manner. During practical demonstrations, Google's security team demonstrated Sec-Gemini v1's ability to identify Salt Typhoon, an internationally recognized threat actor, with high accuracy, as well as to provide rich contextual information, such as vulnerabilities, attack patterns and potential risk exposures associated with this threat actor. 

Through its integration with Mandiant's threat intelligence, which enhances the model's ability to understand evolving threat landscapes, this level of precision and depth can be achieved. The Sec-Gemini v1 software, which is being made available for free to a select group of cybersecurity professionals, academic institutions, and nonprofit organizations, for research, is part of Google's commitment to responsible innovation and industry collaboration. 

Before a broader deployment of this model occurs, this initiative will be designed to gather feedback, validate use cases, and ensure that it is effective across diverse environments. Sec-Gemini v1 represents an important step forward in integrating artificial intelligence into cybersecurity. Google's enthusiasm for advancing this technology while ensuring its responsible development underscores the company's role as a pioneer in the field. 

Providing early, research-focused access to Sec-Gemini v1 not only fosters collaboration within the cybersecurity community but also ensures that Sec-Gemini v1 will evolve in response to collective expertise and real-world feedback, as Google offers this model to the community at the same time. Sec-Gemini v1 has demonstrated remarkable performance across industry benchmarks as well as its ability to detect and mitigate complex threats, so it may be able to change the face of threat defense strategies in the future. 

The advanced reasoning capabilities of Sec-Gemini v1 are coupled with cutting-edge threat intelligence, which can accelerate decision-making, cut response times, and improve organizational security. However, while Sec-Gemini v1 shows great promise, it is still in the research phase and awaiting wider commercial deployment. Using such a phased approach, it is possible to refine the model carefully, ensuring that it adheres to the high standards that are required by various environments. 

For this reason, it is very important that stakeholders, such as cybersecurity experts, researchers, and industry professionals, provide valuable feedback during the first phase of the model development process, to ensure that the model's capabilities are aligned with real-world scenarios and needs. This proactive stance by Google in engaging the community emphasizes the importance of integrating AI responsibly into cybersecurity. 

This is not solely about advancing the technology, but also about establishing a collaborative framework that can make it easier to detect and respond to emerging cyber threats more effectively, more quickly, and more securely. The real issue is the evolution of Sec-Gemini version 1, which may turn out to be one of the most important tools for safeguarding critical systems and infrastructure around the globe in the future.
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