CySecurity News - Latest Information Security and Hacking Incidents: Privacy

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Google Expands Chrome Autofill to IDs as Privacy Concerns Surface

Google is upgrading Chrome with a new autofill enhancement designed to make online forms far less time-consuming. The company announced that the update will allow Chrome to assist with more than just basic entries like passwords or addresses, positioning the browser as a smarter, more intuitive tool for everyday tasks. According to Google, the feature is part of a broader effort to streamline browsing while maintaining privacy and security protections for users.

The enhancement expands autofill to include official identification details such as passports, driver’s licenses, license plate numbers, and even vehicle identification numbers. Chrome will also improve its ability to interpret inconsistent or poorly structured web forms, reducing the need for users to repeatedly correct mismatched fields. Google says the feature will remain off until users enable it manually, and any data stored through the tool is encrypted, saved only with explicit consent, and always requires confirmation before autofill is applied. The update is rolling out worldwide across all languages, with additional supported data categories planned for future releases.

While the convenience factor is clear, the expansion raises new questions about how much personal information users should entrust to their browser. As Chrome takes on more sensitive data, the line between ease and exposure becomes harder to define. Google stresses that security safeguards are built into every layer of the feature, but recent incidents underscore how vulnerable personal data can still be once it moves beyond a user’s direct control.

A recent leak involving millions of Gmail-linked credentials illustrates this risk. Although the breach did not involve Chrome’s autofill system, it highlights how stolen data circulates once harvested and how credential reuse across platforms can amplify damage. Cybersecurity researchers, including Michael Tigges and Troy Hunt, have repeatedly warned that information extracted from malware-infected devices or reused across services often reappears in massive data dumps long after users assume it has disappeared. Their observations underline that even well-designed security features cannot fully protect data that is exposed elsewhere.

Chrome’s upgrade arrives as Google continues to release new features across its ecosystem. Over the past several weeks, the company has tested an ultra-minimal power-saving mode in Google Maps to support users during low-battery emergencies, introduced Gemini as a home assistant in the United States, and enhanced productivity tools across Workspace—from AI-generated presentations in Canvas to integrated meeting-scheduling within Gmail. Individually, these updates appear incremental, but together they reflect a coordinated expansion. Google is tightening the links between its products, creating systems that anticipate user needs and integrate seamlessly across devices.

This acceleration is occurring alongside major investments from other tech giants. Microsoft, for example, is expanding its footprint abroad through a wide-reaching strategy centered on the UAE. As these companies push deeper into automation and cross-platform integration, the competition increasingly revolves around who can deliver the smoothest, smartest digital experience without compromising user trust.

For now, Chrome’s improved autofill promises meaningful convenience, but its success will depend on whether users feel comfortable storing their most sensitive details within the browser—particularly in an era where data leaks and credential theft remain persistent threats.

Digital Security Threat Escalates with Exposure of 1.3 Billion Passwords

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Zero Trust

Credential Stuffing Cybersecurity Breach Data Leak Digital Risk Malware Logs Password Security Privacy Stolen Credentials Threat Intelligence Zero Trust

Digital Security Threat Escalates with Exposure of 1.3 Billion Passwords

One of the starkest reminders of just how easily and widely digital risks can spread is the discovery of an extensive cache of exposed credentials, underscoring the persistent dangers associated with password reuse and the many breaches that go unnoticed by the public. Having recently clarified the false claims of a large-scale Gmail compromise in the wake of Google’s recent clarification, the cybersecurity community is once again faced with vast, attention-grabbing figures which are likely to create another round of confusion.

Approximately 2 billion emails were included in the newly discovered dataset, along with 1.3 billion unique passwords that were found in the dataset, and 625 million of them were not previously reported to the public breach repository. It has been emphasised that Troy Hunt, the founder of Have I Been Pwned, should not use sensationalism when discussing this discovery, as he stresses the importance of the disclosure.

It is important to note that Hunt noted that he dislikes hyperbolic news headlines about data breaches, but he stressed that in this case, it does not require exaggeration since the data speaks for itself. Initially, the Synthient dataset was interpreted as a breach of Gmail before it was clarified to reveal that it was actually a comprehensive collection gathered from stealer logs and multiple past breaches spanning over 32 million unique email domains, and that it was a comprehensive collection.

There's no wonder why Gmail appears more often than other email providers, as it is the world's largest email service provider. The collection, rather than a single event, represents a very extensive collection of compromised email and password pairs, which is exactly the kind of material that is used to generate credential-stuffing attacks, where criminals use recycled passwords to automate attempts to access their banking, shopping, and other online accounts.

In addition to highlighting the dangers associated with unpublicized or smaller breaches, this new discovery also underscores the danger that even high-profile breaches can pose when billions of exposed credentials are quietly redirected to attackers. This newly discovered cache is not simply the result of a single hack, but is the result of a massive aggregation of credentials gathered from earlier attacks, as well as malware information thieves' logs, which makes credential-based attacks much more effective.

A threat actor who exploits reused passwords will have the ability to move laterally between personal and corporate services, often turning a compromised login into an entry point into an increasingly extensive network. A growing number organisations are still dependent on password-only authentication, which poses a high risk to businesses due to the fact that exposed credentials make it much easier for attackers to target business systems, cloud platforms, and administrative accounts more effectively.

The experts emphasised the importance of adopting stronger access controls as soon as possible, including the generation of unique passwords by trusted managers, the implementation of universal two-factor authentication, and internal checks to identify credentials which have been reused or have previously been compromised.

For attackers to be able to weaponise these massive datasets, enterprises must also enforce zero-trust principles, implement least-privilege access, and deploy automated defences against credential-stuffing attempts. When a single email account is compromised, it can easily cascade into financial, cloud or corporate security breaches as email serves as the central hub for recovering accounts and accessing linked services.

Since billions of credentials are being circulated, it is clear that both individuals and businesses need to take a proactive approach to authentication, modernise security architecture, and treat every login as if it were a potential entry point for attackers. This dataset is also notable for its sheer magnitude, representing the largest collection of data Have I Been Pwned has ever taken on, nearly triple the volume of its previous collection.

As compiled by Synthient, a cybercriminal threat intelligence initiative run by a college student, the collection is drawn from numerous sources where stolen credentials are frequently published by cybercriminals. There are two highly volatile types of compromised data in this program: stealer logs gathered from malware on infected computers and large credential-stuffing lists compiled from earlier breaches, which are then combined, repackaged and traded repeatedly over the underground networks.

In order to process the material, HIBP had to use its Azure SQL Hyperscale environment at full capacity for almost two weeks, running 80 processing cores at full capacity. The integration effort was extremely challenging, as Troy Hunt described it as requiring extensive database optimisation to integrate the new records into a repository containing more than 15 billion credentials while maintaining uninterrupted service for millions of people every day.

In the current era of billions of credential pairs being circulated freely between attackers, researchers are warning that passwords alone do not provide much protection any more than they once did. One of the most striking results of this study was that of HIBP’s 5.9 million subscribers, or those who actively monitor their exposure, nearly 2.9 million appeared in the latest compilation of HIBP credentials. This underscores the widespread impact of credential-stuffing troves. The consequences are especially severe for the healthcare industry.

As IBM's 2025 Cost of a Data Breach Report indicates, the average financial impact of a healthcare breach has increased to $7.42 million, and a successful credential attack on a medical employee may allow threat actors to access electronic health records, patient information, and systems containing protected health information with consequences that go far beyond financial loss and may have negative economic consequences as well.

There is a growing concern about the threat of credential exposure outpacing traditional security measures, so this study serves as a decisive reminder to modernise digital defences before attackers exploit these growing vulnerabilities. Organisations should be pushing for passwordless authentication, continuous monitoring, and adaptive risk-based access, while individuals should take a proactive approach to maintaining their credentials as an essential rather than an optional task.

Ultimately, one thing is clear: in a world where billions of credentials circulate unchecked, the key to resilience is to anticipate breaches by strengthening the architecture, optimising the authentication process and maintaining security awareness instead of reacting to them after a breach takes place.

Microsoft Teams’ New Location-Based Status Sparks Major Privacy and Legal Concerns

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Privacy violation

Employee Security Location data location data breach location tracking Microsoft Microsoft Teams Privacy Privacy violation

Microsoft Teams’ New Location-Based Status Sparks Major Privacy and Legal Concerns

Microsoft Teams is preparing to roll out a new feature that could significantly change how employee presence is tracked in the workplace. By the end of the year, the platform will be able to automatically detect when an employee connects to the company’s office Wi-Fi and update their status to show they are working on-site. This information will be visible to both colleagues and supervisors, raising immediate questions about privacy and legality. Although Microsoft states that the feature will be switched off by default, IT administrators can enable it at the organizational level to improve “transparency and collaboration.”

The idea appears practical on the surface. Remote workers may want to know whether coworkers are physically present at the office to access documents or coordinate tasks that require on-site resources. However, the convenience quickly gives way to concerns about surveillance. Critics warn that this feature could easily be misused to monitor employee attendance or indirectly enforce return-to-office mandates—especially as Microsoft itself is requiring employees living within 50 miles of its offices to spend at least three days a week on-site starting next February.

To better understand the implications, TECHBOOK consulted Professor Christian Solmecke, a specialist in media and IT law. He argues that the feature rests on uncertain legal footing under European privacy regulations. According to Solmecke, automatically updating an employee’s location constitutes the processing of personal data, which is allowed under the GDPR only when supported by a valid legal basis. In this case, two possibilities exist: explicit employee consent or a legitimate interest on the part of the employer. But as Solmecke explains, an employer’s interest in transparency rarely outweighs an employee’s right to privacy, especially when tracking is not strictly necessary for job performance.

The expert compares the situation to covert video surveillance, which is only permitted when there is a concrete suspicion of wrongdoing. Location tracking, if used to verify whether workers are actually on-site, falls into a similar category. For routine operations, he stresses, such monitoring would likely be disproportionate. Solmecke adds that neither broad IT policies nor standard employment contracts provide sufficient grounds for processing this type of data. Consent must be truly voluntary, which is difficult to guarantee in an employer-employee relationship where workers may feel pressured to agree.

He states that if companies wish to enable this automatic location sharing, a dedicated written agreement would be required—one that employees can decline without negative repercussions. Additionally, in workplaces with a works council, co-determination rules apply. Under Germany’s Works Constitution Act, systems capable of monitoring performance or behavior must be approved by the works council before being implemented. Without such approval or a corresponding works agreement, enabling the feature would violate privacy law.

For employees, the upcoming rollout does not mean their on-site presence will immediately become visible. Microsoft cannot allow employers to activate such a feature without clear employee knowledge or consent. According to Solmecke, any attempt to automatically log and share employee location inside the company would be legally vulnerable and potentially challengeable. Workers retain the right to reject such data collection unless a lawful framework is in place.

As companies continue navigating hybrid and remote work models, Microsoft’s new location-based status illustrates the growing tension between workplace efficiency and digital privacy. Whether organizations adopt this feature will likely depend on how well they balance those priorities—and whether they can do so within the boundaries of data protection law.

User Privacy:Is WhatsApp Not Safe to Use?

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AI Cloud Data Encryption Privacy Signal WhatsApp X

User Privacy:Is WhatsApp Not Safe to Use?

WhatsApp allegedly collects data

The mega-messenger from Meta is allegedly collecting user data to generate ad money, according to recent attacks on WhatsApp. WhatsApp strongly opposes these fresh accusations, but it didn't help that a message of its own appeared to imply the same.

The allegations

There are two prominent origins of the recent attacks. Few experts are as well-known as Elon Musk, particularly when it occurs on X, the platform he owns. Musk asserted on the Joe Rogan Experience that "WhatsApp knows enough about what you're texting to know what ads to show you." "That is a serious security flaw."

These so-called "hooks for advertising" are typically thought to rely on metadata, which includes information on who messages whom, when, and how frequently, as well as other information from other sources that is included in a user's profile.

End-to-end encryption

The message content itself is shielded by end-to-end encryption, which is the default setting for all 3 billion WhatsApp users. Signal's open-source encryption protocol, which the Meta platform adopted and modified for its own use, is the foundation of WhatsApp's security. So, in light of these new attacks, do you suddenly need to stop using WhatsApp?

In reality, WhatsApp's content is completely encrypted. There has never been any proof that Meta, WhatsApp, or anybody else can read the content itself. However, the platform you are utilizing is controlled by Meta, and it is aware of your identity. It does gather information on how you use the platform.

How user data is used

Additionally, it shares information with Meta so that it can "show relevant offers/ads." Signal has a small portion of WhatsApp's user base, but it does not gather metadata in the same manner. Think about using Signal instead for sensitive content. Steer clear of Telegram since it is not end-to-end encrypted and RCS because it is not yet cross-platform encrypted.

Remember that end-to-end encryption only safeguards your data while it is in transit. It has no effect on the security of your content on the device. I can read all of your messages, whether or not they are end-to-end encrypted, if I have control over your iPhone or Android.

Zero STT Med Sets New Benchmark in Clinical Speech Recognition Efficiency

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Voice AI Innovation

AI In Healthcare Clinical Speech Recognition Healthcare Technology HIPAA Secure ASR Medical Transcription AI Privacy Real-Time Documentation Shunyalabs Zero STT Med Voice AI Innovation

Zero STT Med Sets New Benchmark in Clinical Speech Recognition Efficiency

Shunyalabs.ai has taken a decisive step into transforming medical transcription and clinical documentation by introducing Zero STT Med, a powerful automatic speech recognition (ASR) system developed especially for the medical and clinical fields. Shunyalabs.ai is a pioneer in enterprise-grade Voice AI infrastructure.

A new integrated healthcare system, designed for seamless integration into hospitals as well as platforms for telemedicine, ambient scribe systems, and other healthcare environments with regulated regulations, represents a major leap forward in the evolution of healthcare technology.

Shunyalabs' Zero STT Med is a highly accurate, real-time, and flexible solution that is proven to provide exceptional accuracy, real-time responsiveness, and deployment flexibility across a broad spectrum of cloud and on-premises environments through a combination of domain-optimised speech models with Shunyalabs' proprietary training technology.

With its effective reduction of training overheads typically required for ASR solutions, the platform enables healthcare professionals to spend more time on patient care and less on documenting it, which makes it a new benchmark for clinical speech recognition as it improves precision and efficiency.

The Zero STT Med solution is the result of Shunyalabs' proprietary training framework that stands out for its exceptional precision, responsiveness, and adaptability -- qualities which make it an ideal fit for applications in hospitals, telemedicine, ambient scribe systems, and other healthcare settings regulated by regulatory bodies.

In addition to its outstanding performance metrics, Zero STT Med has set a new benchmark for speech-to-text accuracy, with a Word Error Rate of 11.1% and a Character Error Rate of 5.1%, which puts it well in front of existing medical ASR technologies.

A further distinguishing feature of Zero STT Med is the remarkable efficiency with which it trains itself; the model is fully converged within three days on dual A100 GPUs, and only a limited quantity of real clinical audio is needed. In addition to drastically reducing the amount of data collection and computing demands, this efficiency also enables more frequent updates, which will reflect the most recent medical advancements, terminologies and drug names.

Zero STT Med has been specifically designed to support the real-world medical workflows, providing seamless documentation during consultations, charting, and dictation processes. Its privacy-sensitive architecture allows it to be installed even on CPU-only on-premises servers, ensuring strict compliance with data protection regulations, such as HIPAA and GDPR, while allowing institutions to have complete control over their data.

Clinical speech recognition is a challenging field that often overwhelms conventional ASR systems because of rapid dialogues, overlapping speakers, specialised terminology, and critical accuracy demands. But this new technology offers healthcare professionals a reliable, secure, high-fidelity transcription tool that enables them to transcribe easily, effortlessly, and in an accurate manner.

Among Shunyalabs.ai’s many defining strengths, Shunyalabs.ai prides itself on its Unparalleled Accuracy, along with its Efficiency and Flexible Deployment, two of the most important features that set Zero STT Med apart from the increasingly competitive field of medical speech recognition that is rapidly advancing.

A high-performance ASR system for healthcare can be fully trained in just three days by using an inexpensive setup consisting of two A100 GPUs, which is a substantial improvement over the traditional barriers of data collection, computation, and cost that have hindered the development of high-performance ASR systems in the past.

Using this accelerated training capability, they are not only able to cater to the most specific of learners but also ensure the model remains up-to-date with the ever-evolving language of medicine, such as new drug names, emerging procedures, and evolving clinical terms.

It is an innovative application that is designed to ensure data privacy and compliance, and Zero STT Med is fully integrated with CPU-only servers that allow full on-premises deployments without any cloud dependency. This ensures complete control over patient information, according to global standards such as HIPAA and GDPR, and eliminates the need for cloud dependency.

During the presentation, Ritu Mehrotra, the Founder and CEO of Shunyalabs.ai, stated that medical transcription is a process that requires perfect accuracy since each word plays an important role in clinical care. It is noted that Zero STT Med bridges this gap by providing healthcare organisations with an effective, cost-effective, and time-efficient solution that allows them to utilise their resources effectively.

There is no doubt that the significance of this technological development goes far beyond the technical realm — it addresses the biggest problem in modern medicine, which is physician burnout as a result of excessive documentation. Artificial intelligence (AI) assisted transcription has consistently been demonstrated to reduce documentation time by up to 70%, leading to better clinical performance, less cognitive strain, and more time for practitioners to devote to their patients.

This innovative new product, Zero STT Med, combines real-time processing capabilities with an intuitive user interface so that it seamlessly supports the recording of live clinical consultations, dictations, and archival recordings. Moreover, features such as speaker diarisation allow clinicians to differentiate between multiple speakers within a conversation in real-time.

Additionally, Sourav Banerjee, the Chief Technology Officer of Shunyalabs.ai, stated that the new system is more than just a marginal upgrade — he called it a "redefining of medical speech recognition", which includes fewer corrections, lower latency, and secure data. As a result of these advancements, Zero STT Med is positioned to become an indispensable part of healthcare documentation, bridging the gap between the technological advancements of AI and the precision required by clinical care.

Zero STT Med has been designed with the highest level of privacy and regulatory compliance, and is specifically intended for sensitive healthcare environments where data protection is of utmost importance. The system can run on CPU-only servers on premises, ensuring that healthcare providers maintain complete control over their data while adhering to HIPAA and GDPR regulations.

The model was designed to fulfil the clinical workflows relevant to real-world clinical practices. It can be used for live dictations and transcriptions (especially for live consultations), as well as batch processing of historical recordings, providing flexibility across issues such as immediate or retrospective recording requirements.

The software offers many unique features, including medical terminology optimisation, speaker diarisation that differentiates clinicians from patients with precision, and accent recognition that has been improved through extensive training on a variety of speech datasets in order to achieve the highest level of accuracy. This allows the system to deliver exceptional accuracy, no matter what linguistic or acoustic conditions may be encountered in a clinical setting.

Furthermore, Shunyalabs.ai has developed a rapid retraining capability that allows it to be able to continually update the model with emerging drug names, evolving surgical procedures, and the most recent medical terminology without having to spend excessive amounts of time and resources retraining.

It is worth noting that the system is more than an incremental upgrade to medical speech recognition; it redefines it in a way that requires fewer corrections, lower latency, and complete data privacy. That is the description of the impact Zero STT Med brings to the healthcare and healthtech industries. As a strategic step towards broader adoption, the company has begun extending early access to select healthcare and healthtech organisations for pilot integration and evaluation.

While the model is currently available in English, Shunyalabs plans to extend its linguistic reach in the near future by adding support for Indian and other international languages, illustrating the company's vision of providing high-fidelity, privacy-centred voice AI to the global healthcare community within the next few years.

During the course of the healthcare sector's digital transformation, innovations like Zero STT Med underscore a pivotal shift toward intelligent, privacy-conscious, and domain-specific computer-assisted systems that enhance both accuracy and accessibility through improved accuracy rates and faster response times.

A technology like this not only streamlines documentation but also redefines the clinician's experience by bridging the gap between human expertise and machine accuracy, reducing fatigue, elevating decision-making, and helping patients become more engaged with treatment.

In the future, Zero STT Med has the potential to establish new global standards for clinical speech recognition that are trustworthy, adaptive, and efficient, thereby paving the way for excellence in healthcare based on technology.

WhatsApp’s “We See You” Post Sparks Privacy Panic Among Users

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Privacy Issues

customer data privacy customer privacy Digital Privacy internet privacy Meta Online Privacy Privacy Privacy Issues

WhatsApp’s “We See You” Post Sparks Privacy Panic Among Users

WhatsApp found itself in an unexpected storm this week after a lighthearted social media post went terribly wrong. The Meta-owned messaging platform, known for emphasizing privacy and end-to-end encryption, sparked alarm when it posted a playful message on X that read, “people who end messages with ‘lol’ we see you, we honor you.” What was meant as a fun cultural nod quickly became a PR misstep, as users were unsettled by the phrase “we see you,” which seemed to contradict WhatsApp’s most fundamental promise—that it can’t see users’ messages at all.

Within minutes, the post went viral, amassing over five million views and an avalanche of concerned replies. “What about end-to-end encryption?” several users asked, worried that WhatsApp was implying it had access to private conversations. The company quickly attempted to clarify the misunderstanding, replying, “We meant ‘we see you’ figuratively lol (see what we did there?). Your personal messages are protected by end-to-end encryption and no one, not even WhatsApp, can see them.”

Despite the clarification, the irony wasn’t lost on users—or critics. A platform that has spent years assuring its three billion users that their messages are private had just posted a statement that could easily be read as the opposite. The timing and phrasing of the post made it a perfect recipe for confusion, especially given the long-running public skepticism around Meta’s privacy practices. WhatsApp continued to explain that the message was simply a humorous way to connect with users who frequently end their chats with “lol.”

The company reiterated that nothing about its encryption or privacy commitments had changed, emphasizing that personal messages remain visible only to senders and recipients. “We see you,” they clarified, was intended as a metaphor for understanding user habits—not an admission of surveillance. The situation became even more ironic considering it unfolded on X, Elon Musk’s platform, where he has previously clashed with WhatsApp over privacy concerns.

Musk has repeatedly criticized Meta’s handling of user data, and many expect him to seize on this incident as yet another opportunity to highlight his stance on digital privacy. Ultimately, the backlash served as a reminder of how easily tone can be misinterpreted when privacy is the core of your brand. A simple social media joke, meant to be endearing, became a viral lesson in communication strategy.

For WhatsApp, the encryption remains intact, the messages still unreadable—but the marketing team has learned an important rule: never joke about “seeing” your users when your entire platform is built on not seeing them at all.

Unsecured Corporate Data Found Freely Accessible Through Simple Searches

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Privacy

AI governance AI Security Corporate Data Breach Cybersecurity Data protection Digital Risk ethical AI Information Security Privacy

Unsecured Corporate Data Found Freely Accessible Through Simple Searches

An era when artificial intelligence (AI) is rapidly becoming the backbone of modern business innovation is presenting a striking gap between awareness and action in a way that has been largely overlooked. In a recent study conducted by Sapio Research, it has been reported that while most organisations in Europe acknowledge the growing risks associated with AI adoption, only a small number have taken concrete steps towards reducing them.

Based on insights from 800 consumers and 375 finance decision-makers across the UK, Germany, France, and the Netherlands, the Finance Pulse 2024 report highlights a surprising paradox: 93 per cent of companies are aware that artificial intelligence poses a risk, yet only half have developed formal policies to regulate its responsible use.

There was a significant number of respondents who expressed concern about data security (43%), followed closely by a concern about accountability, transparency, and the lack specialised skills to ensure a safe implementation (both of which reached 29%). In spite of this increased awareness, only 46% of companies currently maintain formal guidelines for the use of artificial intelligence in the workplace, and even fewer—48%—impose restrictions on the type of data that employees are permitted to feed into the systems.

It has also been noted that just 38% of companies have implemented strict access controls to safeguard sensitive information. Speaking on the findings of this study, Andrew White, CEO and Co-Founder of Sapio Research, commented that even though artificial intelligence remains a high priority for investment across Europe, its rapid integration has left many employers confused about the use of this technology internally and ill-equipped to put in place the necessary governance frameworks.

It was found, in a recent investigation by cybersecurity consulting firm PromptArmor, that there had been a troubling lapse in digital security practices linked to the use of artificial intelligence-powered platforms. According to the firm's researchers, 22 widely used artificial intelligence applications—including Claude, Perplexity, and Vercel V0-had been examined by the firm's researchers, and highly confidential corporate information had been exposed on the internet by way of chatbot interfaces.

There was an interesting collection of data found in the report, including access tokens for Amazon Web Services (AWS), internal court documents, Oracle salary reports that were explicitly marked as confidential, as well as a memo describing a venture capital firm's investment objectives. As detailed by PCMag, these researchers confirmed that anyone could easily access such sensitive material by entering a simple search query - "site:claude.ai + internal use only" - into any standard search engine, underscoring the fact that the use of unprotected AI integrations in the workplace is becoming a dangerous and unpredictable source of corporate data theft.

A number of security researchers have long been investigating the vulnerabilities in popular AI chatbots. Recent findings have further strengthened the fragility of the technology's security posture. A vulnerability in ChatGPT has been resolved by OpenAI since August, which could have allowed threat actors to exploit a weakness in ChatGPT that could have allowed them to extract the users' email addresses through manipulation.

In the same vein, experts at the Black Hat cybersecurity conference demonstrated how hackers could create malicious prompts within Google Calendar invitations by leveraging Google Gemini. Although Google resolved the issue before the conference, similar weaknesses were later found to exist in other AI platforms, such as Microsoft’s Copilot and Salesforce’s Einstein, even though they had been fixed by Google before the conference began.

Microsoft and Salesforce both issued patches in the middle of September, months after researchers reported the flaws in June. It is particularly noteworthy that these discoveries were made by ethical researchers rather than malicious hackers, which underscores the importance of responsible disclosure in safeguarding the integrity of artificial intelligence ecosystems.

It is evident that, in addition to the security flaws of artificial intelligence, its operational shortcomings have begun to negatively impact organisations financially and reputationally. "AI hallucinations," or the phenomenon in which generative systems produce false or fabricated information with convincing accuracy, is one of the most concerning aspects of artificial intelligence. This type of incident has already had significant consequences for the lawyer involved, who was penalised for submitting a legal brief that was filled with over 20 fictitious court references produced by an artificial intelligence program.

Deloitte also had to refund the Australian government six figures after submitting an artificial intelligence-assisted report that contained fabricated sources and inaccurate data. This highlighted the dangers of unchecked reliance on artificial intelligence for content generation and highlighted the risk associated with that. As a result of these issues, Stanford University’s Social Media Lab has coined the term “workslop” to describe AI-generated content that appears polished yet is lacking in substance.

In the United States, 40% of full-time office employees reported that they encountered such material regularly, according to a study conducted. In my opinion, this trend demonstrates a growing disconnect between the supposed benefits of automation and the real efficiency can bring. When employees are spending hours correcting, rewriting, and verifying AI-generated material, the alleged benefits quickly fade away.

Although what may begin as a convenience may turn out to be a liability, it can reduce production quality, drain resources, and in severe cases, expose companies to compliance violations and regulatory scrutiny. It is a fact that, as artificial intelligence continues to grow and integrate deeply into the digital and corporate ecosystems, it is bringing along with it a multitude of ethical and privacy challenges.

In the wake of increasing reliance on AI-driven systems, long-standing concerns about unauthorised data collection, opaque processing practices, and algorithmic bias have been magnified, which has contributed to eroding public trust in technology. There is still the threat of unauthorised data usage on the part of many AI platforms, as they quietly collect and analyse user information without explicit consent or full transparency. Consequently, the threat of unauthorised data usage remains a serious concern.

It is very common for individuals to be manipulated, profiled, and, in severe cases, to become the victims of identity theft as a result of this covert information extraction. Experts emphasise organisations must strengthen regulatory compliance by creating clear opt-in mechanisms, comprehensive deletion protocols, and transparent privacy disclosures that enable users to regain control of their personal information.

In addition to these alarming concerns, biometric data has also been identified as a very important component of personal security, as it is the most intimate and immutable form of information a person has. Once compromised, biometric identifiers are unable to be replaced, making them prime targets for cybercriminals to exploit once they have been compromised.

If such information is misused, whether through unauthorised surveillance or large-scale breaches, then it not only poses a greater risk of identity fraud but also raises profound questions regarding ethical and human rights issues. As a consequence of biometric leaks from public databases, citizens have been left vulnerable to long-term consequences that go beyond financial damage, because these systems remain fragile.

There is also the issue of covert data collection methods embedded in AI systems, which allow them to harvest user information quietly without adequate disclosure, such as browser fingerprinting, behaviour tracking, and hidden cookies. utilising silent surveillance, companies risk losing user trust and being subject to potential regulatory penalties if they fail to comply with tightening data protection laws, such as GDPR. Microsoft and Salesforce both issued patches in the middle of September, months after researchers reported the flaws in June.

It is particularly noteworthy that these discoveries were made by ethical researchers rather than malicious hackers, which underscores the importance of responsible disclosure in safeguarding the integrity of artificial intelligence ecosystems. It is evident that, in addition to the security flaws of artificial intelligence, its operational shortcomings have begun to negatively impact organisations financially and reputationally.

"AI hallucinations," or the phenomenon in which generative systems produce false or fabricated information with convincing accuracy, is one of the most concerning aspects of artificial intelligence. This type of incident has already had significant consequences for the lawyer involved, who was penalised for submitting a legal brief that was filled with over 20 fictitious court references produced by an artificial intelligence program.

Deloitte also had to refund the Australian government six figures after submitting an artificial intelligence-assisted report that contained fabricated sources and inaccurate data. This highlighted the dangers of unchecked reliance on artificial intelligence for content generation, highlighted the risk associated with that. As a result of these issues, Stanford University’s Social Media Lab has coined the term “workslop” to describe AI-generated content that appears polished yet is lacking in substance.

When employees are spending hours correcting, rewriting, and verifying AI-generated material, the alleged benefits quickly fade away. Although what may begin as a convenience may turn out to be a liability, it can reduce production quality, drain resources, and in severe cases, expose companies to compliance violations and regulatory scrutiny.

It is a fact that, as artificial intelligence continues to grow and integrate deeply into the digital and corporate ecosystems, it is bringing along with it a multitude of ethical and privacy challenges. In the wake of increasing reliance on AI-driven systems, long-standing concerns about unauthorised data collection, opaque processing practices, and algorithmic bias have been magnified, which has contributed to eroding public trust in technology.

There is still the threat of unauthorised data usage on the part of many AI platforms, as they quietly collect and analyse user information without explicit consent or full transparency. Consequently, the threat of unauthorised data usage remains a serious concern. It is very common for individuals to be manipulated, profiled, and, in severe cases, to become the victims of identity theft as a result of this covert information extraction.

Experts emphasise that thatorganisationss must strengthen regulatory compliance by creating clear opt-in mechanisms, comprehensive deletion protocols, and transparent privacy disclosures that enable users to regain control of their personal information. In addition to these alarming concerns, biometric data has also been identified as a very important component of personal security, as it is the most intimate and immutable form of information a person has.

Once compromised, biometric identifiers are unable to be replaced, making them prime targets for cybercriminals to exploit once they have been compromised. If such information is misused, whether through unauthorised surveillance or large-scale breaches, then it not oonly posesa greater risk of identity fraud but also raises profound questions regarding ethical and human rights issues.

As a consequence of biometric leaks from public databases, citizens have been left vulnerable to long-term consequences that go beyond financial damage, because these systems remain fragile. There is also the issue of covert data collection methods embedded in AI systems, which allow them to harvest user information quietly without adequate disclosure, such as browser fingerprinting behaviourr tracking, and hidden cookies.

utilising silent surveillance, companies risk losing user trust and being subject to potential regulatory penalties if they fail to comply with tightening data protection laws, such as GDPR. Furthermore, the challenges extend further than privacy, further exposing the vulnerability of AI itself to ethical abuse. Algorithmic bias is becoming one of the most significant obstacles to fairness and accountability, with numerous examples having been shown to, be in f ,act contributing to discrimination, no matter how skewed the dataset.

There are many examples of these biases in the real world - from hiring tools that unintentionally favour certain demographics to predictive policing systems which target marginalised communities disproportionately. In order to address these issues, we must maintain an ethical approach to AI development that is anchored in transparency, accountability, and inclusive governance to ensure technology enhances human progress while not compromising fundamental freedoms.

In the age of artificial intelligence, it is imperative tthat hatorganisationss strike a balance between innovation and responsibility, as AI redefines the digital frontier. As we move forward, not only will we need to strengthen technical infrastructure, but we will also need to shift the culture toward ethics, transparency, and continual oversight to achieve this.

Investing in a secure AI infrastructure, educating employees about responsible usage, and adopting frameworks that emphasise privacy and accountability are all important for businesses to succeed in today's market. As an enterprise, if security and ethics are incorporated into the foundation of AI strategies rather than treated as a side note, today's vulnerabilities can be turned into tomorrow's competitive advantage – driving intelligent and trustworthy advancement.

Connected Car Privacy Risks: How Modern Vehicles Secretly Track and Sell Driver Data

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Privacy Risks

Car Data Data collection Data Privacy Data protection Data Safety User Data data security Data Surveillance Mozilla Foundation Privacy Privacy Risks

Connected Car Privacy Risks: How Modern Vehicles Secretly Track and Sell Driver Data

The thrill of a smooth drive—the roar of the engine, the grip of the tires, and the comfort of a high-end cabin—often hides a quieter, more unsettling reality. Modern cars are no longer just machines; they’re data-collecting devices on wheels. While you enjoy the luxury and performance, your vehicle’s sensors silently record your weight, listen through cabin microphones, track your every route, and log detailed driving behavior. This constant surveillance has turned cars into one of the most privacy-invasive consumer products ever made.

The Mozilla Foundation recently reviewed 25 major car brands and declared that modern vehicles are “the worst product category we have ever reviewed for privacy.” Not a single automaker met even basic standards for protecting user data. The organization found that cars collect massive amounts of information—from location and driving patterns to biometric data—often without explicit user consent or transparency about where that data ends up.

The Federal Trade Commission (FTC) has already taken notice. The agency recently pursued General Motors (GM) and its subsidiary OnStar for collecting and selling drivers’ precise location and behavioral data without obtaining clear consent. Investigations revealed that data from vehicles could be gathered as frequently as every three seconds, offering an extraordinarily detailed picture of a driver’s habits, destinations, and lifestyle.

That information doesn’t stay within the automaker’s servers. Instead, it’s often shared or sold to data brokers, insurers, and marketing agencies. Driver behavior, acceleration patterns, late-night trips, or frequent stops at specific locations could be used to adjust insurance premiums, evaluate credit risk, or profile consumers in ways few drivers fully understand.

Inside the car, the illusion of comfort and control masks a network of tracking systems. Voice assistants that adjust your seat or temperature remember your commands. Smartphone apps that unlock the vehicle transmit telemetry data back to corporate servers. Even infotainment systems and microphones quietly collect information that could identify you and your routines. The same technology that powers convenience features also enables invasive data collection at an unprecedented scale.

For consumers, awareness is the first defense. Before buying a new vehicle, it’s worth asking the dealer what kind of data the car collects and how it’s used. If they cannot answer directly, it’s a strong indication of a lack of transparency. After purchase, disabling unnecessary connectivity or data-sharing features can help protect privacy. Declining participation in “driver score” programs or telematics-based insurance offerings is another step toward reclaiming control.

As automakers continue to blend luxury with technology, the line between innovation and intrusion grows thinner. Every drive leaves behind a digital footprint that tells a story—where you live, work, shop, and even who rides with you. The true cost of modern convenience isn’t just monetary—it’s the surrender of privacy. The quiet hum of the engine as you pull into your driveway should represent freedom, not another connection to a data-hungry network.

AI Browsers Spark Debate Over Privacy and Cybersecurity Risks

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prompt injection attacks

AI Browser Security AI vulnerabilities Atlas Browser Comet Browser Cybersecurity Threats Digital Privacy Risks Online Safety Privacy prompt injection attacks

AI Browsers Spark Debate Over Privacy and Cybersecurity Risks

With the rapid development of artificial intelligence, the digital landscape continues to undergo a reshaping process, and the internet browser itself seems to be the latest frontier in this revolution. After the phenomenal success of AI chatbots such as ChatGPT, Google Gemini, and Perplexity, tech companies are now racing to integrate the same kind of intelligence into the very tool that people use every day to navigate the world online.

A recent development by Google has been the integration of Gemini into its search engine, while both OpenAI and Perplexity have released their own AI-powered browsers, Atlas and Perplexity, all promising a more personalised and intuitive way to browse online content. In addition to offering unprecedented convenience and conversational search capabilities for users, this innovation marks the beginning of a new era in information access.

In spite of the excitement, cybersecurity professionals remain increasingly concerned. There is a growing concern among experts that intelligent systems are inadvertently exposing users to sophisticated cyber risks in spite of enhancing their user experience.

A context-aware interaction or dynamic data retrieval feature that allows users to interact with their environment can be exploited through indirect prompt injection and other manipulation methods, which may allow attackers to exploit the features.

It is possible that these vulnerabilities may allow malicious actors to access sensitive data such as personal files, login credentials, and financial information, which raises the risk of data breaches and cybercriminals. In these new eras of artificial intelligence, where the boundaries between browsing and AI are blurring, there has become an increasing urgency in ensuring that trust, transparency, and safety are maintained on the Internet.

AI browsers continue to divide experts when it comes to whether they are truly safe to use, and the issue becomes increasingly complicated as the debate continues. In addition to providing unprecedented ease of use and personalisation, ChatGPT's Atlas and Perplexity's Comet represent the next generation of intelligent browsers. However, they also introduce new levels of vulnerability that are largely unimaginable in traditional web browsers.

It is important to understand that, unlike conventional browsers, which are just gateways to online content, these artificial intelligence-driven platforms function more like a digital assistant on their own. Aside from learning from user interactions, monitoring browsing behaviours, and even performing tasks independently across multiple sites, humans and machines are becoming increasingly blurred in this evolution, which has fundamentally changed the way we collect and process data today.

A browser based on Artificial Intelligence watches and interprets each user's digital moves continuously, from clicks to scrolls to search queries and conversations, creating extensive behavioural profiles that outline users' interests, health concerns, consumer patterns, and emotional tendencies based on their data.

Privacy advocates have argued for years that this level of surveillance is more comprehensive than any cookie or analytics tool on the market today, and represents a turning point in digital tracking. During a recent study by the Electronic Frontier Foundation, organisation discovered that Atlas retained search data related to sensitive medical inquiries, including names of healthcare providers, which raised serious ethical and legal concerns in regions that restricted certain medical procedures.

Due to the persistent memory architecture of these systems, they are even more contentious. While ordinary browsing histories can be erased by the user, AI memories, on the other hand, are stored on remote servers, which are frequently retained indefinitely. By doing so, the browser maintains long-term context. The system can use this to access vast amounts of sensitive data - ranging from financial activities to professional communications to personal messages - even long after the session has ended.

These browsers are more vulnerable than ever because they require extensive access permissions to function effectively, which includes the ability to access emails, calendars, contact lists, and banking information. Experts have warned that such centralisation of personal data creates a single point of catastrophic failure—one breach could expose an individual's entire digital life.

OpenAI released ChatGPT Atlas earlier this week, a new browser powered by artificial intelligence that will become a major player in the rapidly expanding marketplace of browsers powered by artificial intelligence. The Atlas browser, marketed as a browser that integrates ChatGPT into your everyday online experience, represents an important step forward in the company’s effort to integrate generative AI into everyday living.

Despite being initially launched for Mac users, OpenAI promises to continue to refine its features and expand compatibility across a range of platforms in the coming months. As Atlas competes against competitors such as Perplexity's Comet, Dia, and Google's Gemini-enabled Chrome, the platform aims to redefine the way users interact with the internet—allowing ChatGPT to follow them seamlessly as they browse through the web.

As described by OpenAI, ChatGPT's browser is equipped to interpret open tabs, analyse data on the page, and help users in real time, without requiring users to switch between applications or copy content manually. There have been a number of demonstrations that have highlighted the versatility of the tool, demonstrating its capability of completing a broad range of tasks, from ordering groceries and writing emails to summarising conversations, analysing GitHub repositories and providing research assistance. OpenAI has mentioned that Atlas utilises ChatGPT’s built-in memory in order to be able to remember past interactions and apply context to future queries based on those interactions.

There is a statement from the company about the company's new approach to creating a more intuitive, continuous user experience, in which the browser will function more as a collaborative tool and less as a passive tool. In spite of Atlas' promise, just as with its AI-driven competitors, it has stirred up serious issues around security, data protection and privacy.

One of the most pressing concerns regarding prompt injection attacks is whether malicious actors are manipulating large language models to order them to perform unintended or harmful actions, which may expose customer information. Experts warn that such "agentic" systems may come at a significant security cost.

An attack like this can either occur directly through the user's prompts or indirectly by hiding hidden payloads within seemingly harmless web pages. A recent study by Brave researchers indicates that many AI browsers, including Comet and Fellou, are vulnerable to exploits like this. The attacker is thus able to bypass browser security frameworks and gain unauthorized access to sensitive domains such as banks, healthcare facilities, or corporate systems by bypassing browser security frameworks.

It has also been noted that many prominent technologists have voiced their reservations. Simon Willison, a well-known developer and co-creator of the Django Web Framework, has urged that giving browsers the freedom to act autonomously on their users' behalf would pose grave risks. Even seemingly harmless requests, like summarising a Reddit post, could, if exploited via an injection vulnerability, be used to reveal personal or confidential information.

With the advancement of artificial intelligence browsers, the tension between innovation and security becomes more and more intense, prompting the call for stronger safeguards before these tools become mainstream digital companions. There has been an increase in the number of vulnerabilities discovered by security researchers that make AI browsers a lot more dangerous than was initially thought, with prompt injection emerging as the most critical vulnerability.

A malicious website can use this technique to manipulate AI-driven browser agents secretly, effectively turning them against a user. Researchers at Brave found that attackers are able to hide invisible instructions within webpage code, often rendered as white text on white backgrounds. These instructions are unnoticeable by humans but are easily interpreted by artificial intelligence systems.

A user may be directed to perform unauthorised actions when they visit a web page containing embedded commands. For example, they may be directed to retrieve private e-mails, access financial data, or transfer money without their consent. Due to the inherent lack of contextual understanding that artificial intelligence systems possess, they can unwittingly execute these harmful instructions, with full user privileges, when they do not have the ability to differentiate between legitimate inputs from deceptive prompts.

These attacks have caused a lot of attention among the cybersecurity community due to their scale and simplicity. Researchers from LayerX demonstrated the use of a technique called CometJacking, which was demonstrated as a way of hijacking Perplexity’s Comet browser into a sophisticated data exfiltration tool by a single malicious link.

A simple encoding method known as Base64 encoding was used by attackers to bypass traditional browser security measures and sandboxes, allowing them to bypass the browser's protections. It is therefore important to know that the launch point for a data theft campaign could be a seemingly harmless comment on Reddit, a social media post, or even an email newsletter, which could expose sensitive personal or company information in an innocuous manner.

The findings of this study illustrate the inherent fragility of artificial intelligence browsers, where independence and convenience often come at the expense of safety. It is important to note that cybersecurity experts have outlined essential defence measures for users who wish to experiment with AI browsers in light of these increasing concerns.

Individuals should restrict permissions strictly, giving access only to non-sensitive accounts and avoiding involving financial institutions or healthcare institutions until the technology becomes more mature. By reviewing activity logs regularly, you can be sure that you have been alerted to unusual patterns or unauthorised actions in advance. A multi-factor authentication system can greatly enhance security across all linked accounts, while prompt software updates allow users to take advantage of the latest security patches.

A key safeguard is to maintain manual vigilance-verifying URLs and avoiding automated interactions with unfamiliar or untrusted websites. Some prominent technologists have expressed doubts about these systems as well. A respected developer and co-creator of the Django Web Framework, Simon Willison, has warned that giving browsers the ability to act autonomously on behalf of users comes with profound risks.

It is noted that even benign requests, such as summarising a Reddit post, could inadvertently expose sensitive information if exploited by an injection vulnerability, and this could result in personal information being released into the public domain. With the advancement of artificial intelligence browsers, the tension between innovation and security becomes more and more intense, prompting the call for stronger safeguards before these tools become mainstream digital companions.

There has been an increase in the number of vulnerabilities discovered by security researchers that make AI browsers a lot more dangerous than was initially thought, with prompt injection emerging as the most critical vulnerability. Using this technique, malicious websites have the ability to manipulate the AI-driven browsers, effectively turning them against their users.

Brave researchers discovered that attackers are capable of hiding invisible instructions within the code of the webpages, often rendered as white text on a white background. The instructions are invisible to the naked eye, but are easily interpreted by artificial intelligence systems. The embedded commands on such pages can direct the browser to perform unauthorised actions, such as retrieving private emails, accessing financial information, and transferring funds, as a result of a user visiting such a page.

Since AI systems are inherently incapable of distinguishing between legitimate and deceptive user inputs, they can unknowingly execute harmful instructions with full user privileges without realising it. This attack has sparked the interest of the cybersecurity community due to its scale and simplicity.

Researchers from LayerX have demonstrated a method of hijacking Perplexity's Comet browser by merely clicking on a malicious link, and using this technique, transforming the browser into an advanced data exfiltration tool. Attackers were able to bypass traditional browser security measures and security sandboxes by using simple methods like Base64 encoding.

It means that a seemingly harmless comment on Reddit, a post on social media, or an email newsletter can serve as a launch point for a data theft campaign, thereby potentially exposing sensitive personal and corporate information to a third party. There is no doubt that AI browsers are intrinsically fragile, where autonomy and convenience sometimes come at the expense of safety. The findings suggest that AI browsers are inherently vulnerable.

It has become clear that security experts have identified essential defence measures to protect users who wish to experiment with AI browsers in the face of increasing concerns. It is suggested that individuals restrict their permissions as strictly as possible, granting access only to non-sensitive accounts and avoiding connecting to financial or healthcare services until the technology is well developed.

In order to detect unusual patterns or unauthorised actions in time, it is important to regularly review activity logs. Multi-factor authentication is a vital component of protecting linked accounts, as it adds a new layer of security, while prompt software updates ensure that users receive the latest security patches on their systems.

Furthermore, experts emphasise manual vigilance — verifying URLs and avoiding automated interactions with unfamiliar or untrusted websites remains crucial to protecting their data. There is, however, a growing consensus among professionals that artificial intelligence browsers, despite impressive demonstrations of innovation, remain unreliable for everyday use.

Analysts at Proton concluded that AI browsers are no longer reliable for everyday use. This argument argues that the issue is not only technical, but is structural as well; privacy risks are a part of the very design of these systems themselves. AI browser developers, who prioritise functionality and personalisation over all else, have inherently created extensive surveillance architectures that rely heavily on user data in order to function as intended.

It has been pointed out by OpenAI's own security leadership that prompt injection remains an unresolved frontier issue, thus emphasising that this emerging technology is still a very experimental and unsettled one. The consensus among cybersecurity researchers, at the moment, is that the risks associated with artificial intelligence browsers far outweigh their convenience, especially for users dealing with sensitive personal and professional information.

With the acceleration of the AI browser revolution, it is now crucial to strike a balance between innovation and accountability. Despite the promise of seamless digital assistance and a hyper-personalised browsing experience through tools such as Atlas and Comet, they must be accompanied by robust ethical frameworks, transparent data governance, and stronger security standards to make progress.

A lot of experts stress that the real progress will depend on the way this technology evolves responsibly - prioritising user consent, privacy, and control over convenience for the end user. In the meantime, users and developers alike should not approach AI browsers with fear, but with informed caution and an insistence that trust is built into the browser as a default state.

Stop Using Public Wi-Fi: Critical Security Risks Explained

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Security

Cybersecurity Hacking Privacy Public Wifi Security

Stop Using Public Wi-Fi: Critical Security Risks Explained

Public Wi-Fi networks, commonly found in coffee shops and public spaces, are increasingly used by remote workers and mobile device users seeking internet access outside the home or office. While convenient, these networks pose significant security risks that are often misunderstood.

This article explains why tech experts caution against the casual use of public Wi-Fi, emphasizing that such networks can be notably unsafe, especially when unsecured. The distinction between secure and unsecured networks is critical: secure networks require authentication steps like passwords, account creation, or agreeing to terms of service.

These measures typically offer additional layers of protection for users. In contrast, unsecured networks allow anyone to connect without authorization, lacking essential cybersecurity safeguards. According to experts from Executech, unsecured networks do not incorporate protective measures to prevent unauthorized access and malicious activities, leaving users vulnerable to cyberattacks.

When connecting to unsecured public Wi-Fi, data transmitted between a device and the network can be intercepted by attackers who may exploit weaknesses in the infrastructure. Cybercriminals often target these networks to access sensitive information stored or shared on connected devices. Individuals should be wary about what activities they perform on such connections, as the risk of unauthorized access and data theft is high.

Security experts advise users to avoid performing sensitive tasks, such as accessing bank accounts, entering financial details for online shopping, or opening confidential emails, when on public Wi-Fi. Personal and family information, especially involving children, should also be kept off devices used on public networks to mitigate the risk of exposure.

For those who absolutely must use public Wi-Fi—for emergencies or workplace requirements—layering protections is recommended. Downloading a reputable VPN can help encrypt data traffic, establishing a secure tunnel between the user’s device and the internet and reducing some risk.

Ultimately, the safest approach is to avoid public Wi-Fi altogether when possible, relying on personal routers or trusted connections instead. All public Wi-Fi networks are susceptible to hacking attempts, regardless of perceived safety. By following the suggested precautions and maintaining awareness of potential risks, users can better protect their sensitive information and minimize security threats when forced to use public Wi-Fi networks.

ChatGPT Atlas Surfaces Privacy Debate: How OpenAI’s New Browser Handles Your Data

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User Data

AI Browsers atlas Browser ChatGPT OpenAI Privacy User Data

ChatGPT Atlas Surfaces Privacy Debate: How OpenAI’s New Browser Handles Your Data

OpenAI has officially entered the web-browsing market with ChatGPT Atlas, a new browser built on Chromium: the same open-source base that powers Google Chrome. At first glance, Atlas looks and feels almost identical to Chrome or Safari. The key difference is its built-in ChatGPT assistant, which allows users to interact with web pages directly. For example, you can ask ChatGPT to summarize a site, book tickets, or perform online actions automatically, all from within the browser interface.

While this innovation promises faster and more efficient browsing, privacy experts are increasingly worried about how much personal data the browser collects and retains.

How ChatGPT Atlas Uses “Memories”

Atlas introduces a feature called “memories”, which allows the system to remember users’ activity and preferences over time. This builds on ChatGPT’s existing memory function, which stores details about users’ interests, writing styles, and previous interactions to personalize future responses.

In Atlas, these memories could include which websites you visit, what products you search for, or what tasks you complete online. This helps the browser predict what you might need next, such as recalling the airline you often book with or your preferred online stores. OpenAI claims that this data collection aims to enhance user experience, not exploit it.

However, this personalization comes with serious privacy implications. Once stored, these memories can gradually form a comprehensive digital profile of an individual’s habits, preferences, and online behavior.

OpenAI’s Stance on Early Privacy Concerns

OpenAI has stated that Atlas will not retain critical information such as government-issued IDs, banking credentials, medical or financial records, or any activity related to adult content. Users can also manage their data manually: deleting, archiving, or disabling memories entirely, and can browse in incognito mode to prevent the saving of activity.

Despite these safeguards, recent findings suggest that some sensitive data may still slip through. According to The Washington Post, an investigation by a technologist at the Electronic Frontier Foundation (EFF) revealed that Atlas had unintentionally stored private information, including references to sexual and reproductive health services and even a doctor’s real name. These findings raise questions about the reliability of OpenAI’s data filters and whether user privacy is being adequately protected.

Broader Implications for AI Browsers

OpenAI is not alone in this race. Other companies, including Perplexity with its upcoming browser Comet, have also faced criticism for extensive data collection practices. Perplexity’s CEO openly admitted that collecting browser-level data helps the company understand user behavior beyond the AI app itself, particularly for tailoring ads and content.

The rise of AI-integrated browsers marks a turning point in internet use, combining automation and personalization at an unprecedented scale. However, cybersecurity experts warn that AI agents operating within browsers hold immense control — they can take actions, make purchases, and interact with websites autonomously. This power introduces substantial risks if systems malfunction, are exploited, or process data inaccurately.

What Users Can Do

For those concerned about privacy, experts recommend taking proactive steps:

• Opt out of the memory feature or regularly delete saved data.

• Use incognito mode for sensitive browsing.

• Review data-sharing and model-training permissions before enabling them.

AI browsers like ChatGPT Atlas may redefine digital interaction, but they also test the boundaries of data ethics and security. As this technology evolves, maintaining user trust will depend on transparency, accountability, and strict privacy protection.

Proxy Servers: How They Work and What They Actually Do

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VPN

https Internet of Things IP Address Privacy Proxy Server VPN

Proxy Servers: How They Work and What They Actually Do

When browsing online, your device usually connects directly to a website’s server. However, in certain cases, especially for privacy, security, or access control — a proxy server acts as a go-between. It stands between your device and the internet, forwarding your web requests and returning responses while showing its own public IP address instead of yours.

According to the U.S. National Institute of Standards and Technology (NIST), a proxy server is essentially a system that handles requests from clients and forwards them to other servers. In simple terms, it’s a digital middleman that manages the communication between you and the websites you visit.

How a Proxy Server Operates

Here’s how the process works:

1. Your computer or device sends a request to the proxy server instead of directly contacting a website.

2. The proxy then forwards that request to the destination site.

3. The site responds to the proxy.

4. The proxy returns the data to your device.

From your perspective, it looks like a normal browsing session, but from the website’s end, the request appears to come from the proxy’s IP address. Proxies can exist as physical network devices or as cloud-based services that users configure through system or browser settings.

Companies often use “reverse proxies” to manage and filter incoming traffic to their web servers. These reverse proxies can block malicious activity, balance heavy traffic loads, and improve performance by caching frequently accessed pages.

Why People Use Proxy Servers

Proxy servers are used for several reasons. They provide a basic layer of privacy by hiding your actual IP address and limiting what websites can track about you. They can also make it appear that you’re browsing from another location, allowing access to region-locked content or websites blocked in your area.

In workplaces and educational institutions, proxies help administrators restrict certain sites, monitor browsing activity, and reduce bandwidth consumption by storing copies of commonly visited web pages. Large organizations also rely on proxies to safeguard internal systems and regulate how employees connect to external networks.

The Limitations and Risks

Despite their advantages, proxy servers have notable limits. They do not encrypt your internet traffic, which means that if your connection is not secured through HTTPS, the information passing through can still be intercepted. Free or public proxy services pose particular risks, they often slow down browsing, log user activity, inject advertisements, or even harvest data for profit.

For users seeking genuine privacy or security, experts recommend using paid, reputable proxy services or opting for a Virtual Private Network (VPN). VPNs extend the idea of a proxy by adding encryption, ensuring that all traffic between the user and the internet is protected.

Proxy vs. VPN vs. NAT

Although proxies, VPNs, and Network Address Translation (NAT) all sit between your device and the wider web, they function differently.

• Proxy: Masks your IP address and filters traffic but does not encrypt your connection.

• VPN: Encrypts all online activity and provides a stronger layer of privacy and security.

• NAT: Operates within routers, allowing multiple devices in a household or office to share one public IP address. It’s a background process, not a privacy tool.

Proxy servers are practical tools for managing internet access, optimizing traffic, and adding basic privacy. However, they should not be mistaken for comprehensive security solutions. Users should view proxies as one layer of digital protection, effective when used properly, but insufficient on their own. For strong privacy, encryption, and security, a VPN remains the more reliable choice.

AWS Outage Exposes the Fragility of Centralized Messaging Platforms

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Signal

AWS communication Data Decentralised Platform Matrix Outage Privacy Signal

AWS Outage Exposes the Fragility of Centralized Messaging Platforms

A recently recorded outage at Amazon Web Services (AWS) disrupted several major online services worldwide, including privacy-focused communication apps such as Signal. The event has sparked renewed discussion about the risks of depending on centralized systems for critical digital communication.

Signal is known globally for its strong encryption and commitment to privacy. However, its centralized structure means that all its operations rely on servers located within a single jurisdiction and primarily managed by one cloud provider. When that infrastructure fails, the app’s global availability is affected at once. This incident has demonstrated that even highly secure applications can experience disruption if they depend on a single service provider.

According to experts working on decentralized communication technology, this kind of breakdown reveals a fundamental flaw in the way most modern communication apps are built. They argue that centralization makes systems easier to control but also easier to compromise. If the central infrastructure goes offline, every user connected to it is impacted simultaneously.

Developers behind the Matrix protocol, an open-source network for decentralized communication, have long emphasized the need for more resilient systems. They explain that Matrix allows users to communicate without relying entirely on the internet or on a single server. Instead, the protocol enables anyone to host their own server or connect through smaller, distributed networks. This decentralization offers users more control over their data and ensures communication can continue even if a major provider like AWS faces an outage.

The first platform built on Matrix, Element, was launched in 2016 by a UK-based team with the aim of offering encrypted communication for both individuals and institutions. For years, Element’s primary focus was to help governments and organizations secure their communication systems. This focus allowed the project to achieve financial stability while developing sustainable, privacy-preserving technologies.

Now, with growing support and new investments, the developers behind Matrix are working toward expanding the technology for broader public use. Recent funding from European institutions has been directed toward developing peer-to-peer and mesh network communication, which could allow users to exchange messages without relying on centralized servers or continuous internet connectivity. These networks create direct device-to-device links, potentially keeping users connected during internet blackouts or technical failures.

Mesh-based communication is not a new idea. Previous applications like FireChat allowed people to send messages through Bluetooth or Wi-Fi Direct during times when the internet was restricted. The concept gained popularity during civil movements where traditional communication channels were limited. More recently, other developers have experimented with similar models, exploring ways to make decentralized communication more user-friendly and accessible.

While decentralized systems bring clear advantages in terms of resilience and independence, they also face challenges. Running individual servers or maintaining peer-to-peer networks can be complex, requiring technical knowledge that many everyday users might not have. Developers acknowledge that reaching mainstream adoption will depend on simplifying these systems so they work as seamlessly as centralized apps.

Other privacy-focused technology leaders have also noted the implications of the AWS outage. They argue that relying on infrastructure concentrated within a few major U.S. providers poses strategic and privacy risks, especially for regions like Europe that aim to maintain digital autonomy. Building independent, regionally controlled cloud and communication systems is increasingly being seen as a necessary step toward safeguarding user privacy and operational security.

The recent AWS disruption serves as a clear warning. Centralized systems, no matter how secure, remain vulnerable to large-scale failures. As the digital world continues to depend heavily on cloud-based infrastructure, developing decentralized and distributed alternatives may be key to ensuring communication remains secure, private, and resilient in the face of future outages.

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WhatsApp allegedly collects data

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AI Browsers Spark Debate Over Privacy and Cybersecurity Risks

Stop Using Public Wi-Fi: Critical Security Risks Explained

ChatGPT Atlas Surfaces Privacy Debate: How OpenAI’s New Browser Handles Your Data

Proxy Servers: How They Work and What They Actually Do

AWS Outage Exposes the Fragility of Centralized Messaging Platforms

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WhatsApp allegedly collects data

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