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Showing posts with label Cyber Security. Show all posts
Web Application Security
Access Control Failure customer data leak Cyber Security Cybersecurity Incident Data Exposure Data protection Privacy Risk URL Enumeration Web Application Security

Retailer Secures Website After Customer Data Leak Risk Identified


 

Express has quietly fixed a security flaw that permitted unauthorized access to customer order data following a significant lapse in web application security. This vulnerability exposed sensitive information ranging from customer names, emails, telephone numbers, shipping details, and partial payment data through search engine indexing, which resulted in an inadvertent public disclosure of order confirmation pages through search engine indexing.

There were at least a dozen such records appearing in search results, demonstrating that sequential order identifiers embedded within URLs may be exploited without sophisticated intrusion techniques. In a fraud investigation conducted by an independent security researcher, the issue was uncovered, which highlights how seemingly routine investigations can reveal deeper systemic weaknesses in data handling and access controls. The company was then able to take immediate and corrective measures.

A wide variety of personally identifiable information was disclosed in the exposed records, including customer name, phone number, email address, billing and delivery locations as well as masked payment card information, which was accessible via publicly accessible order confirmation pages. Initially, users could enumerate order records by altering parameters within the web address due to inadequate access controls and predictable URL patterns.

In investigating a suspicious transaction involving a family member, Rey Bango discovered that a simple search query could reveal unrelated customer orders that had previously been indexed by search engines when investigating a suspicious transaction. 

Upon the disclosure of this incident, Express, which is now owned by WHP Global, took steps to remediate the issue. However, the company has not yet clarified whether affected individuals will receive a formal notification. Despite reaffirming the organization's commitment to safeguarding consumer data and encouraging responsible reporting of vulnerabilities, Joe Berean did not outline a structured reporting process for vulnerabilities. 

A number of data exposure incidents have been linked to misconfigured web assets in the past year, reinforcing the persistent gaps in secure development practices as well as the challenges that enterprises must overcome when preventing unintended data leaks at large scales. 

The discovery emerged largely as an accident, resulting from Rey Bango's attempt to validate a potentially fraudulent transaction involving a family member's account after further investigation. In the absence of a clearly defined reporting channel, he escalated the issue by submitting a report in order to ensure prompt resolution. Based on his findings, search engines could surface unrelated records of customers by querying order numbers through indexed confirmation pages coupled with sequential order identifiers. 

As a result of independent verification, minor manipulations of URL parameters enabled the unauthorized access to other users' order histories and personal information, a vulnerability that could be amplified through automated enumeration. After the flaw was disclosed, Express addressed it, but the response evolved to clarify whether the affected customers would be notified and whether forensic logs could be used to determine the extent of unauthorized access. 

The company’s marketing head, Joe Berean, reinforced the company's commitment to data security, but offered limited transparency regarding incident response measures, such as the absence of information about a formal vulnerability disclosure framework or regulatory notification requirements. 

Despite persistent governance gaps, the lack of clarity regarding follow-up compliance, particularly concerning U.S. breach disclosure requirements, highlights these shortcomings. As seen in recent disclosures involving Home Depot and Petco, this episode aligns with a general pattern of exposure incidents that are related to misconfigurations. Because of overlooked security controls, sensitive customer data remains accessible, highlighting the ongoing challenges of enforcing robust web application security. 

The incident illustrates how relatively simple design oversights, such as predictable identifiers and improperly restricted web resources, can quickly morph into large-scale privacy risks, when combined with search engine indexing and absent disclosure mechanisms. 

The company has taken steps to resolve the immediate vulnerability, but the lack of clarity around notification to customers, audit logging, and formal vulnerability intake procedures raises concerns regarding incident readiness and accountability. 

Due to the expansion of digital commerce footprints, the case illustrates the necessity of incorporating secure-by-design principles, in addition to implementing robust access controls and maintaining transparent reporting mechanisms in order to address flaws before they become more serious. 

When these safeguards are not in place, even routine transactional systems can become unintentional points of vulnerability, reinforcing the necessity of continuous security validation throughout the lifecycle of an application.
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Vulnerability
Anthropic API Artificial Intelligence Cyber Security Vulnerability

Researchers Reproduce Anthropic-Style AI Vulnerability Findings Using Public Models at Low Cost

 


New research suggests that the ability to discover software vulnerabilities using artificial intelligence is becoming both inexpensive and widely accessible, raising concerns that advanced cyber capabilities may be spreading faster than anticipated.

A study by Vidoc Security demonstrates that vulnerability discovery techniques similar to those highlighted in Anthropic’s recent “Mythos” work can be reproduced using publicly available AI models. By leveraging GPT-5.4 and Claude Opus 4.6 within an open-source framework called opencode, researchers were able to replicate key findings for under $30 per scan, without access to Anthropic’s internal systems or restricted programs.

Anthropic had earlier positioned its Mythos research as highly sensitive, limiting access to a small group of major organizations and prompting concern across policy and financial circles. Reports indicated that senior figures, including Scott Bessent and Jerome Powell, discussed the implications alongside leading financial executives. The term “vulnpocalypse” resurfaced in cybersecurity discussions, reflecting fears of large-scale AI-driven exploitation.

The Vidoc team sought to test whether such capabilities were truly restricted. Using patched vulnerability examples referenced in Anthropic’s public materials, they examined issues affecting a file-sharing protocol, a security-focused operating system’s networking components, widely used video-processing software, and cryptographic libraries used for identity verification online.

Across three independent runs, both models successfully reproduced two of the documented vulnerability cases each time. Claude Opus 4.6 also independently rediscovered a flaw in OpenBSD in all three attempts, while GPT-5.4 failed to identify that specific issue. In other instances, including vulnerabilities tied to FFmpeg and wolfSSL, the systems correctly identified relevant code regions but did not fully determine the root cause.

The methodology closely mirrored workflows described by Anthropic. Instead of relying on a single prompt, the system first analyzed entire codebases, divided them into smaller segments, and ran parallel detection processes. These processes filtered meaningful signals from noise and cross-checked findings across files. Importantly, the selection of code segments was automated through earlier planning steps, rather than manually guided.

Despite these results, the study underlines a clear distinction. Anthropic’s system reportedly went beyond identifying vulnerabilities by constructing detailed exploit pathways, such as chaining code fragments across multiple network packets to achieve full remote control of a system. The public models, while capable of locating weaknesses, did not reach that level of execution.

According to researcher Dawid Moczadło, this indicates a new turn of events in cybersecurity economics. The most resource-intensive part of the process, identifying credible vulnerability signals, is becoming accessible to anyone with standard API access. However, validating those findings and converting them into reliable security insights or exploit strategies remains significantly more complex.

Anthropic itself has acknowledged that traditional benchmarks like Cybench are no longer sufficient to measure modern AI cyber capabilities, noting that its Mythos system exceeded those standards. The company estimated that comparable capabilities could become widespread within six to eighteen months.

The Vidoc findings suggest that, at least for vulnerability discovery, this transition may already be underway. By publishing their methodology, prompts, and results, the researchers highlight how open tools and commercially available models can replicate parts of workflows once considered highly restricted.

For organizations, the implications are instrumental. As AI reduces the cost and effort required to uncover software flaws, defenders may need to adopt continuous monitoring, faster remediation cycles, and deeper behavioral analysis. The challenge is no longer just identifying vulnerabilities, but managing the scale and speed at which they can now be discovered.

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Fake Calls
AI Phishing Threats bank scams Consumer Protection Cyber Scams Cyber Security Fake Calls

Fake Court Summons And Survey Scams Surge As Regions Bank Warns Of Rising Consumer Fraud Risks

 


Fear remains one of the most powerful tools scammers use, and today’s fraud tactics are evolving to exploit it more effectively than ever. Fake court summons and deceptive online survey scams are now being widely used to trick individuals into revealing sensitive information or making payments. Regions Bank has raised awareness around these threats, emphasizing that such schemes are designed to steal passwords, drain bank accounts, or silently install malware on personal devices. 

One of the more alarming trends involves fraudulent legal notices. Victims may receive messages claiming they missed a court date, failed to pay a toll, or owe a penalty. These alerts often create a sense of urgency, warning of arrest or severe consequences if immediate action is not taken. The goal is to push individuals into reacting quickly without verifying the information. Instead of legitimate resolution channels, these messages direct users to click suspicious links, scan QR codes, or call phone numbers that connect them directly to scammers.  

Although these communications can appear convincing, they often contain clear warning signs. Aggressive or threatening language, demands for immediate payment, and instructions to use unconventional methods such as gift cards or wire transfers are strong indicators of fraud. Genuine legal authorities follow formal processes and provide verifiable documentation, allowing individuals to confirm claims through official sources. Ignoring these red flags can lead to serious financial and data security consequences. Another emerging tactic involves fake CAPTCHA prompts. 

These scams exploit the familiarity of “I’m not a robot” verification tools but introduce unusual instructions, such as pressing specific keyboard shortcuts. What seems like a routine step can actually trigger hidden malicious code, potentially installing malware on the user’s device. Legitimate CAPTCHA systems are simple and never require complex or unexpected actions, making any deviation a likely sign of a scam. Survey scams represent another widespread threat. These schemes lure victims with promises of rewards such as cash, gift cards, or free products. After completing a series of questions, users are told they have “won” and are asked to provide payment details for a small fee. 

In reality, the reward never materializes, and the scammers gain access to valuable financial information. Organizations like the Better Business Bureau have noted a rise in such scams, highlighting unrealistic offers, vague company information, suspicious links, and poor grammar as common warning signs. If individuals encounter these scams, experts recommend deleting the message immediately, avoiding any engagement, and reporting the incident through official platforms such as the Internet Crime Complaint Center. Acting quickly is critical, especially if personal or financial information has already been shared. 

Ultimately, staying vigilant is the most effective defense. Avoid clicking on unknown links, verify information through trusted sources, enable multi-factor authentication, and regularly monitor financial accounts for unusual activity. These scams rely on urgency, fear, and enticing rewards to bypass rational thinking. While tactics continue to evolve, a cautious and informed approach remains the strongest way to protect against fraud in an increasingly digital environment.
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Fake Accounts
AI technology Cyber Security Deepfake deepfake scams Digital identification Digital Identity Verification Fake Accounts

Tinder And Zoom Introduce World ID Iris Scanning To Verify Humans Amid Rising AI Fake Profiles

 

Now comes eye-scan tech on Tinder and Zoom, rolling out to confirm real people behind profiles amid rising fears about AI mimics and bots. This move leans on identity checks from World ID - backed by Tools for Humanity - to tell actual humans apart. Verification lights up through unique iris patterns, quietly working when someone logs in. Not every user sees it yet; testing shapes how widely it spreads. Behind the scenes, privacy safeguards aim to shield biometric data tightly. Shifts like these respond to digital trust gaps widening across social apps lately. Scanning begins at the iris, that ring of color in the eye, using either an app or a round gadget made for this purpose. After confirmation comes through, a distinct digital ID lands on the person's smartphone. 

This key travels with them, opening access wherever systems accept it to prove someone is human, not automated software. Rising floods of fake online personas built by artificial intelligence fuel efforts like this one. Impersonations crafted by deepfakes grow more common, pushing such verification into sharper focus. Backed by Sam Altman - also at the helm of OpenAI - the project made its debut in San Francisco. At the event, he suggested the web may soon be flooded with machine-made content more than human output. Truth online might hinge on tools able to tell actual humans apart from artificial ones. 

Such systems, according to him, are likely to grow unavoidable. Fake accounts plague both Tinder and Zoom, complicating trust on these platforms. Driven by artificial intelligence, counterfeit profiles on Tinder deploy synthetic photos alongside prewritten messages. These setups often unfold into romantic deception aimed at seizing cash or sensitive details. Reports indicate massive monetary damage worldwide due to similar frauds lately. Losses tally in the billions across nations within just a few years. 

Surprisingly, Zoom faces a distinct yet connected challenge - deepfake-driven impersonation at work. A well-documented incident saw fraudsters deploy synthetic audio and video to mimic corporate leaders, tricking staff into sending large sums. Here, World ID steps in, adding stronger verification when stakes run high. Later came iris scans, after Match Group already introduced video selfies to fight fake profiles on Tinder. Though not required, this newer check offers a tougher way to prove who you really are. People at the company say it helps users feel more certain about others’ real identities. 

What matters most is trust during interactions. Because irises differ so much between people, World ID uses them as a key part of its method. This setup aims to protect user privacy by creating an individual code instead of keeping sensitive data like home locations or full names. Even though it does not collect traditional identity markers, the technology still confirms real individuals. Growth has been steady, with expanding adoption seen on various digital services. 

A large number of people - already in the millions - have gone through the sign-up process. Now shaping how we confirm who's behind a screen, artificial intelligence pushes biometrics deeper into everyday applications. Though concerns linger about data safety and user acceptance, this trend mirrors wider attempts across tech sectors to tackle rising confusion between real people and sophisticated automated fakes. Despite hesitation in some areas, systems that verify physical traits gain ground as tools for clearer online identities.
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Zero Trust Security
Backup Protection Cyber Recovery cyber resilience Cyber Security Data integrity Data Recovery Ransomware Defense Threat Detection Zero Trust Security

The Shift from Cyber Defense to Recovery-Driven Security


 

There has been a structural recalibration of cybersecurity strategies as organizations recognize that breaches impact operations, finances, and reputation in ways that extend far beyond the moment of intrusion. 

Incidents that once remained within the domain of IT are now affecting the entire organization, with containment cycles lasting up to months and remediation costs reaching tens of millions for large-scale breaches. 

Leaders in response are shifting their focus from absolute prevention to sustained operational continuity, recognizing that resilience is not defined by the absence of attacks, but rather by the capability of recovering quickly and precisely. 

The shift is driving a renewed focus on creating integrated cyber resilience frameworks that align business continuity objectives with security controls, ensuring critical systems remain recoverable even after active compromises. There is also a disconnect between security enforcement and operational accessibility resulting from this evolution. 

The cybersecurity function has historically prioritized perimeter hardening and strict authentication, whereas business operations demand uninterrupted data availability with minimal friction to operate. With increasing threat landscapes and competing priorities, these priorities are convergent, often revealing inefficiencies, in which layered authentication mechanisms, while indispensable, inadvertently delay recovery workflows and extend downtime during critical incidents.

By integrating adaptive intelligence and automation into Zero Trust architectures, this divide is beginning to be reconciled. The approach organizations are taking is to design environments where continuous verification is co-existing with streamlined restoration capabilities rather than treating security and recovery as opposing forces. 

Zero Trust, at its core, is a strategic model rather than a single technology that requires rigorous, context-aware authentication utilizing multiple data points prior to granting access. In combination with intelligent recovery systems, this approach is redefining resilience by enabling secure access without compromising recovery agility, resulting in high-assurance environments that are able to maintain operations even under persistent threat circumstances. 

With the increased sophistication of ransomware campaigns, conventional backup-centric strategies are revealing their limitations, as adversaries increasingly design attacks that extend beyond the initial system compromises. Threat actors execute long reconnaissance phases during many incidents, mapping enterprise environments, identifying high-value assets, and, critically, locating backups and undermining them before encrypting or destroying data.

By intentionally targeting a variety of entities, cybercrime has evolved into a coordinated and enterprise-like environment where operational disruption is designed to maximize leverage. Attackers effectively eliminate an organization's ability to restore from trusted states when they compromise recovery pathways, amplifying downtime and causing an increase in financial and regulatory risk. 

Due to this inevitability, forward-looking organizations are repositioning their security postures to reflect this inevitability, incorporating defensive controls into a more holistic security model that includes assured recoverability. As part of this approach, cyber resilience and cyber recovery are integrated, where the objective is to not only withstand intrusion attempts but to maintain data integrity, availability, and rapid restoration under adversarial circumstances. 

The modern cyber recovery architectures are reflecting these evolving threat dynamics by incorporating resilience as an integral part of their development, repositioning data protection from a passive safeguard to an active line of defense. Hardened recovery frameworks are becoming increasingly popular among organizations, which include air-gapped vaulting and immutable storage, in order to ensure backup data is not susceptible to adversarial manipulation while enabling integrity validation before restoration through advanced malware scanning. 

A controlled virtual environment is used to test recovery processes isolated from one another, along with point-in-time restoration capabilities that are capable of restoring systems back to a known, uncompromised state with minimal operational disruptions as a complement to this. 

Separate recovery enclaves are also crucial to preventing lateral movement and credential-based compromise, as backup infrastructure is decoupled from production networks, thus eliminating lateral movement pathways. This architecture ensures that security and compliance requirements are not treated as an afterthought but are integrally integrated, supported by comprehensive audit trails, tagging of data, and a verifiable chain of custody. These capabilities together provide organizations with a structured, audit-ready recovery posture that maintains business continuity, even under sustained cyber pressure, a transition from reactive incident response.

In an effort to maintain continuous visibility into backup repository integrity and behavior, organizations are extending the focus beyond safeguarding backup repositories in their resilience frameworks. There is an increasing trend among threat actors to employ persistence-driven techniques that alter backup configurations or introduce incremental data corruption to erode reliable recovery points over time—often without triggering immediate alerts. 

Unless granular monitoring is employed, manipulations of this kind can be undetected until the recovery process has been initiated, at which point recovery pathways may already be compromised. It is for this reason that enterprises are integrating advanced telemetry, behavioral analytics, and anomaly detection in backup ecosystems, enabling early detection of irregular access patterns, unauthorized configuration changes, and deviations in data consistency. 

By enhancing proactive visibility, enterprises can not only respond more quickly to incidents but also prevent adversaries from dismantling recovery capabilities silently. Rapid recovery is of little value if latent threats are reintroduced into production environments. 

Furthermore, it is important to ensure that recovered data is intact and uncompromised. In this regard, organizations are integrating validation layers, such as isolated forensic sandboxes and automated recovery testing, to verify backup integrity well in advance of a loss. 

By implementing a comprehensive architectural shift in which recovery is engineered as a fundamental capability instead of a reactive measure, enterprises are positioned to sustain operations with minimal disruption by embedding immutability, isolation, continuous monitoring, and trusted validation into data protection strategies from conception. 

Consequently, resilience is no longer based on the ability to evade every attack, but rather on the ability to restore systems as quickly and precisely as possible, especially when defenses have been breached inevitably. Cybersecurity effectiveness is no longer defined by absolute prevention, but rather by the assurance that controlled, reliable recovery can be achieved under adverse circumstances. 

A growing number of adversaries continue to develop techniques that bypass traditional defenses and target recovery mechanisms themselves, forcing organizations to adopt a design philosophy based on the expectation of compromise rather than treating compromise as an exception. 

In order to maintain operational continuity, it is imperative that security postures, continuous monitoring, and resilient recovery architectures are integrated cohesively. In order to mitigate the cascading impact of cyber incidents, enterprises should align detection capabilities with verified restoration processes and embed trust throughout the recovery lifecycle. 

The key to establishing resilience is not eliminating risk, but rather abiding by its ability to absorb disruption, restore critical systems with integrity, and sustain business operations without interruption in a world where cyber incidents have become an operational certainty rather than simply a possibility.
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Cyber Security
advanced technologies AI Advancements AI in robotics AI Robots AI technology Cyber Security

Physical AI Talent War Drives Salaries Surge Across Robotics And Autonomous Vehicle Industry

 

Salaries climb fast as demand surges for experts who blend AI know-how with hands-on hardware skills. Firms in robotics, military tech, and self-operating machines now pay between three hundred thousand and five hundred thousand dollars just to attract top people. That surge comes on the heels of earlier fights for workers during the driverless car push, when even big names had trouble pulling in talent. Waymo once set the bar high - now others chase it harder than before. Pressure builds not because of trends, but due to how few can actually bridge software brains with real-world devices. 

Competition doesn’t slow - it spreads, fueled by what very few offer. What drives this wave of hiring is the need for people able to connect classic robotics with current AI tools. Such individuals must build and roll out smart systems that work in many areas - humanoid machines, factory automation, self-driving lift trucks, plus equipment found in farming, mining, and building sites. Because these jobs involve high-level challenges, skilled workers have become highly sought after; rivalry now stretches beyond new tech firms to include long-standing car makers too. 

Now stepping into a sharper spotlight, defense tech companies attract skilled professionals more aggressively than many peers - backed by steady financial support from organizations including the U.S. Department of Defense. Because these firms propose better pay, workers once aimed at self-driving car ventures shift direction, nudging auto industry players and new entrants alike toward rethinking how they hire and reward staff. Positions like AI enablement engineers and applied AI researchers see intense demand; such roles feed straight into building advanced smart technologies. While quiet on the surface, movement beneath reshapes where expertise flows. 

A shift in talent demand could reshape parts of the auto industry. Those focusing on driverless systems might lose key staff, possibly stalling progress. Firms new to the field may have to find more money or use what they have more carefully just to keep up. Some investors are moving fast - one backer gathered well over a billion dollars to support emerging hardware-driven AI ventures. Growth in this space seems tied closely to who can attract and hold technical experts. Money flows follow where specialists choose to work. 

What lies ahead isn’t just about filling roles - industries are shifting as firms move past self-driving cars toward what some call physical AI. These efforts stretch into areas like military tech, factory robots, and new kinds of transport machinery. Firms like Hermeus, having secured major capital lately, show where money is going: complex builds that tie artificial intelligence to real-world hardware. Growth now hinges less on software alone, more on machines that act in space. Quiet progress reshapes entire sectors without loud announcements. Capital follows builders who merge circuits with movement. 

Now that the field has grown older, fighting for skilled workers plays a central role in where it heads next. Winning trust and keeping sharp minds depends on which organizations manage operations at scale using actual AI systems today. Because need keeps climbing while available experts stay few, hardware-linked AI skill shortages persist - pointing toward lasting changes in how firms assess and pursue tech talent. Though time passes, pressure does not ease.
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Winona County cyberattack
Cyber Security local government cybersecurity Minnesota National Guard response ransomware attack 2026 Winona County cyberattack

Winona County Cyberattack Disrupts Key Services, Minnesota Deploys National Guard for Emergency Response

 

A cyberattack on Winona County has disrupted critical systems, leading Minnesota authorities to step in with emergency assistance.

The attack began on April 6 and continued into April 7, impacting core digital infrastructure used for emergency response and municipal operations. Officials said the incident significantly affected their ability to manage essential services, including administrative and public-facing functions.

Governor Tim Walz responded by signing an executive order authorizing the Minnesota National Guard to support recovery efforts.

"Cyberattacks are an evolving threat that can strike anywhere, at any time," said Governor Walz. "Swift coordination between state and local experts matters in these moments. That's why I am authorizing the National Guard to support Winona County as they work to protect critical systems and maintain essential services."

County officials confirmed that teams have been working continuously since detecting the breach. The response involves coordination with Minnesota Information Technology Services, the Minnesota Bureau of Criminal Apprehension, the League of Minnesota Cities, the Federal Bureau of Investigation, and external cybersecurity experts.

Despite these efforts, authorities acknowledged that the scale and complexity of the attack exceeded both internal capabilities and commercial support, prompting a formal request for assistance from the National Guard.

Under the executive order, the Adjutant General is authorized to deploy personnel, equipment, and additional resources to assist with the response. The state can also procure necessary services, with costs covered through Minnesota’s general fund.

The order is currently active and will remain in place until the situation stabilizes or is officially lifted. The immediate focus is on containing the threat, preventing further damage, and restoring affected systems.

Officials emphasized that emergency services remain operational. Systems supporting 911 calls, fire response, and other urgent services are functioning, ensuring public safety is not compromised.

However, disruptions have slowed other county operations, and residents may experience delays while systems are restored.

Authorities have not yet disclosed the exact nature of the cyberattack or confirmed whether ransomware is involved.

The FBI, along with state agencies and cybersecurity experts, is investigating the incident. The probe aims to determine how the breach occurred, identify affected systems, and assess whether sensitive data was accessed.

This event follows a ransomware incident reported by Winona County in January 2026.

At that time, officials stated, "We recently identified and responded to a ransomware incident affecting our computer network. Upon discovery, we immediately initiated an investigation to assess the scope and impact of the incident."

During the earlier attack, a local emergency was declared to maintain service continuity. While emergency operations remained active, other services faced temporary disruptions.

The recurrence of cyber incidents within a short period has raised concerns about ongoing vulnerabilities and the growing cyber threat landscape for local governments. The incident highlights a broader trend: smaller government bodies are increasingly targeted by sophisticated cyberattacks but often lack the resources to respond effectively.

As systems go offline, public services are immediately affected, and recovery can take time. While state support is helping stabilize operations in Winona County, the situation underscores the need for stronger cybersecurity defenses at the local level.

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financial systems
AI Risks AI technology Anthropic Anthropic AI Cyber Security Financial Cybersecurity financial systems

Wall Street Banks Test Anthropic Mythos AI as Regulators Warn of Rising Cybersecurity Threats

 

Now showing up in high-security finance circles: early tests of cutting-edge AI aimed at boosting cyber resilience, driven by rising regulator unease over smart-tech dangers. Leading the charge - an emerging system called Mythos, developed by Anthropic, notable not just for spotting code flaws but also for actively probing them under controlled conditions. 

Hidden flaws in financial networks now draw attention through Mythos, offering banks an early look ahead of potential breaches. Rather than waiting, some begin using artificial intelligence to mimic live hacking attempts across vast operations. What was once passive observation shifts toward active testing - driven by machines that learn attacker behavior. Instead of just alarms after intrusion, systems predict paths criminals might follow. Tools evolve beyond fixed rules into adaptive models shaped by constant simulation. Security transforms quietly - not with fanfare - but through repeated digital trials beneath the surface. 

What's pushing these tests forward? Part of it comes from alerts issued by American regulatory bodies, highlighting rising risks tied to artificial intelligence in cyber threats. As AI systems grow sharper, officials warn they might empower attackers to run breaches automatically, uncover system weaknesses faster, then strike vital operations - banks included - with greater precision. Though subtle, the shift marks a turning point in how digital dangers evolve. 

One reason Mythos stands out is its ability to analyze enormous amounts of code quickly. Because it detects hidden bugs others miss, security teams gain deeper insight into weak spots. What makes the model unusual is how it links separate issues to map multi-step exploits. Although some worry such power could be misapplied, financial institutions find value in testing systems against lifelike threats. Most cyber specialists point out the banking world faces extra risk because everything links together, holding valuable information. 

A small flaw might spread widely, disrupting transactions, markets, sometimes personal records. Tools powered by artificial intelligence - Mythos, for example - might detect weaknesses sooner than traditional methods. Meanwhile, regulatory bodies urge stricter supervision along with more defined guidelines governing AI applications in finance. What worries them extends beyond outside dangers - to include internal weaknesses that might emerge if AI tools lack proper governance inside organizations. 

While safety is a priority, so too is preventing system failures caused by weak oversight structures. Restricting entry to Mythos, Anthropic allows just certain groups to test the system under tight conditions. While some push fast progress, others slow down - this move leans toward care over speed. Responsibility shapes how strong tools spread, not just what they can do. 

Though Wall Street banks assess artificial intelligence for cyber protection, one fact stands out - threats shift faster than ever. Those who blend AI into security efforts might stay ahead; however, success depends on steady monitoring, strong protective layers, and constant updates when new dangers appear.
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Social Media Regulation
AI Bill Cyber Security Deepfake Controls digital safety karnataka Social Media Regulation

Karnataka Unveils AI-Driven Bill to Enforce Swift Social Media Safety

 

Karnataka is set to revolutionize social media regulation with the draft Karnataka Responsible Social Media & Digital Safety Bill, 2026, submitted to Chief Minister Siddaramaiah. Prepared by the Karnataka State Policy and Planning Commission (KSPPC), this legislation emphasizes artificial intelligence (AI), rapid content moderation, and robust user protections, marking India's first state-level, AI-compliant, citizen-centric digital safety framework. S Mohanadass Hegde, a KSPPC member, highlighted its potential to foster responsible digital citizenship amid rising AI-driven threats. 

The primary focus is  on tackling AI-generated content and deepfakes through mandatory labelling, precise legal definitions, and strict penalties for misuse. Platforms face enforceable timelines, required to remove harmful content within 24 to 48 hours, shifting from advisory central guidelines to binding state actions. This departs from national laws like the Information Technology Act, 2000, and IT Rules, 2021, which prioritize due diligence without such tight deadlines.

The bill establishes the Karnataka Digital Safety & Social Media Regulatory Authority to monitor compliance and address region-specific digital risks swiftly. Users gain rights to report harmful content, access time-bound grievance redressal, and protections against harassment and misinformation. Hegde noted that localized oversight enables faster responses than central bodies, enhancing enforcement through tech tools like fake news detection, deepfake tracking, and real-time dashboards. 

Prevention takes center stage with a digital awareness and media literacy program promoting fact-checking, critical thinking, and responsible online behavior. This educational push targets mental well-being, particularly for youth vulnerable to harmful trends and addiction risks, balancing punishment with proactive measures. A team member emphasized education as key to curbing violations before they escalate. Implementation unfolds in phases: initial awareness and institutional setup, followed by technology integration and full enforcement. Slated for legal vetting and monsoon session introduction in June-July 2026, the draft positions Karnataka as a leader in decentralized digital governance, offering a blueprint for other states amid evolving AI challenges.
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Security Risk
CISO Burnout Cyber Security Executive Stress Cyber Resilience Security Risk

CISO Burnout Is Costing Businesses More Than Money

 

Businesses are increasingly feeling the financial and operational impact of CISO burnout, as overstretched security leaders make slower decisions, miss critical signals, and eventually leave their roles. The pressure of rising cyber threats, regulatory demands, and limited resources is turning the CISO position into a high‑turnover, high‑cost liability rather than a strategic asset. 

Why CISOs are burning out 

CISOs today face an “always‑on” workload, with AI‑driven attacks, expanding digital estates, and constant audits leaving little room for rest. Many report chronic stress, decision fatigue, and missed family events, while still working well beyond contracted hours to keep up. Boards often understand the pressure in theory, but fail to translate this into better staffing, budgets, or clearer priorities.

When a burned‑out CISO resigns or takes extended leave, firms pay not only recruitment and onboarding costs, but also the hidden price of lost productivity and disrupted projects. One expert estimates total CISO replacement costs can exceed 200% of salary when incident‑related losses, staff turnover, and delayed IT initiatives are factored in. Incidents that might have been caught earlier are more likely to slip through, raising breach‑related expenses and reputational damage. 

Impact on security and board confidence 

Burnout erodes cyber resilience by weakening threat detection, slowing crisis‑time decisions, and degrading communication of risk to the board. As CISOs disengage, security can become an afterthought, initiatives stall, and internal morale in security teams drops. This visibly undermines confidence at the top, making it harder to secure long‑term investment in modern security programs.

To break the cycle, companies must invest in prevention: realistic job design, adequate headcount, clear mandates, and mental‑health support. Some firms are shifting toward fractional or portfolio‑style CISOs, spreading responsibility and reducing single‑point pressure. Firms that treat CISO well‑being as a core part of risk management will likely see better retention, stronger security posture, and lower overall breach‑related costs.
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Secure AI Systems
AI Compliance AI Deployment AI governance AI Infrastructure Cyber Risk Management Cyber Security Data Governance enterprise AI Secure AI Systems

From Demo to Deployment Why AI Projects Struggle to Scale


 

In many cases, the enthusiasm surrounding artificial intelligence peaks during demonstrations, when controlled environments create an overwhelming vision of seamless capability. However, one of the most challenging aspects of enterprise technology adoption remains the transition from that initial promise to sustained operational value. 

The apparent simplicity of embedding such systems into real-world operations, where consistency, resilience, and accountability are non-negotiable, often masks the complexity involved. It is generally not the intelligence of the model that causes difficulties in practice, rather the organization's ability to operationalise it within existing production ecosystems within the organization. 

In the early stages of the pilot program, technical feasibility is established successfully, demonstrating that AI can perform defined tasks under ideal conditions. In order to scale that capability, it is necessary to demonstrate a thorough understanding of model accuracy. A clear integration of systems, alignment with legacy and modern infrastructure, clearly defined ownership across teams, disciplined cost management, and compliance with evolving regulatory frameworks are necessary. 

An important distinction between experimentation and operationalisation becomes the decisive factor for the failure of most AI initiatives beyond the pilot phase. This gap becomes particularly evident when controlled demonstrations are encountered with unpredictability in live environments. In order to minimize friction during demonstrations, structured datasets, stable inputs, and narrowly focused application scenarios are used.

Production systems, on the other hand, are subject to fragmented data pipelines, inconsistent input patterns, incomplete contextual signals, and stringent latency requirements. Edge cases, on the other hand, are not exceptions, but the norm, and systems need to maintain stability under varying loads and constraints. As a result, organizations typically lose the initial momentum generated by a successful demo when attempting wider deployment, revealing previously concealed limitations.

Consequently, the challenge is not to design an artificial intelligence system that performs well in isolation, but to design one that can sustain performance under continuous operational pressure. In addition to model development, AI systems that are considered production-grade have to be designed in a distributed system environment that addresses fault tolerance, observability, scalability, and cost efficiency in a systematic manner. 

In order to be effective, they must integrate seamlessly with existing services, provide monitoring and feedback loops, and evolve without introducing instability. In the transition from prototype to production phase, the majority of AI initiatives fail, highlighting the importance of architectural discipline and operational maturity. In addition to the visible challenges associated with deployment, there is another fundamental constraint silently determining the fate of most artificial intelligence initiatives, namely the data ecosystem in which it is embedded. 

While organizations frequently focus on model selection and tooling, the real determinant of success lies in the structure, governance, and reliability of the data environment, which supports continuous learning and decision-making at an appropriate scale. Despite this prerequisite, many enterprise settings remain unmet. 

According to industry assessments, a significant portion of organizations are lacking confidence in the capability to manage data efficiently for artificial intelligence (AI), suggesting deeper structural gaps in the collection, organization, and maintenance of data. Despite substantial data volumes, they are often distributed among disconnected systems, including enterprise resource planning platforms, customer relationship management tools, legacy on-premises databases, spreadsheets, and a growing number of third-party services. 

Inconsistencies in schema design are caused by fragmentation, and weak or missing metadata layers contribute to limited visibility into the data lineage as well as inadequate governance controls. A system such as this will be forced to produce stable and reproducible outcomes when it has incomplete or unreliable inputs. The consequences of this misalignment are evident during production deployment. Models trained on fragmented or poorly governed data environments will exhibit unpredictable behavior over time and will not generalize across applications. 

Inconsistencies in data source dependencies start compromising operational workflows, eroding stakeholder trust. When confidence is declining, leadership often responds by stifling or suspending the rollout of broader artificial intelligence initiatives, not because of technological deficiencies, but rather because of a lack of supporting data infrastructure to support the rollout. Moreover, this reinforces the broader pattern observed across enterprises that the transition from experimentation to operational scale is governed as much by data maturity as it is by system architecture. 

The discussion around artificial intelligence has begun to shift from capability to control as organizations move beyond isolated deployments. The scale of technology initially appears to be a concern, but gradually turns out to be a matter of designing accountability systems, in which speed, governance, and operational clarity should coexist without friction. 

Having reached this stage, success is no longer determined by isolated breakthroughs but by an organization's ability to integrate artificial intelligence into the operating fabric of its organization. Many enterprises instinctively adopt centralised oversight structures, such as review boards and governance councils, as a way of standardizing decision-making in response to increased complexity and risk exposure. However, these mechanisms are insufficient to ensure AI adoption occurs across a wide range of business units as AI adoption accelerates across multiple business units. 

Scale-achieving organizations integrate governance directly into execution pathways rather than relying solely on episodic review processes. In place of evaluating each initiative individually, they define enterprise-wide standards and reusable solutions that align with varying levels of risk to enable lower-risk use cases through streamlined deployment paths, while higher-risk applications are systematically evaluated through structured frameworks with clearly assigned ownership, ensuring that their use is secure. 

Through this approach, ambiguity is reduced, approval cycles are shortened, and teams are able to operate confidently within predefined boundaries. However, another constraint emerges in the form of data usage hesitancy, which has quietly limited AI initiatives. Because of concerns regarding security, compliance, and control, organizations often delay or restrict the use of real operational data. 

It is imperative to implement tangible operational safeguards to overcome this barrier in addition to policy assurances. Providing the assurance that data remains within controlled network environments, establishing clear lifecycle management protocols, and providing real-time visibility into system usage and cost dynamics are all necessary to create the confidence necessary to expand adoption to a wider audience.

With the maturation of these mechanisms, decision makers are given the assurance needed to extend the capabilities of AI into critical workflows without introducing unmanaged risks. Scaling AI is no longer a matter of increasing the number of models but rather a matter of aligning organizational structures in support of these models.

The ability of companies to expand AI initiatives with significantly reduced friction is facilitated by the establishment of clear ownership models, harmonising processes across departments, establishing unified data foundations, and integrating governance into daily operations. On the other hand, organizations whose AI is maintained as a standalone technology function may experience fragmented adoption, inconsistent results, and a decline in stakeholder trust. 

In this shift, leadership is expected to meet new challenges. Long-term success is determined not by the sophistication of individual models, but by how disciplined AI operations are implemented across organizations. Every deployment must be able to withstand scrutiny under real-world conditions, where outputs need to be explainable, defendable, and reliable. 

In response, forward-looking leaders are refocusing on the central question how confidently can AI be scaled - rather than how rapidly it can be deployed. As governance is integrated into development and operational workflows, the perceived tradeoff between speed and control begins to dissolve, allowing the two to strengthen each other. 

A recurring challenge across AI initiatives from stalled pilots to fragmentation of data and governance bottlenecks indicates the absence of a coherent operating model. An effective organization addresses this by developing a framework that connects business value to execution. 

AI will be required to deliver a set of outcomes, integration pathways are established into existing systems and decision processes, roles and workflows have to be redesigned to accommodate AI-driven operations, and mechanisms are embedded to ensure trust, safety, and continuous oversight are implemented. 

Upon alignment of these elements, artificial intelligence becomes a repeatable, scalable capability that is integrated into an organization's core operations instead of an experimentation process. For organizations that wish to make AI ambitions a reality, disciplined execution rather than rapid experimentation is the path forward. 

The development of enforceable standards, the investment in resilient data and systems foundations, and the alignment of accountability between business and technical functions are essential to success. Leading organizations that prioritize operational readiness, measurable outcomes, and controlled scalability are better prepared to transform artificial intelligence from isolated success stories into dependable enterprise capabilities. 

Those organizations that approach AI as an operational investment rather than a technological initiative will gain a competitive advantage in a market that is increasingly focused on trust, transparency, and performance.
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malicious PDF files
Adobe Adobe Reader Cyber Security Cyberattacks cybersecurity vulnerabilities data security Hacker attack Malicious Files Malicious PDF Attachment malicious PDF files

Adobe Reader Zero-Day PDF Exploit Actively Used in Attacks to Steal Data

 

A fresh security flaw in Adobe Reader - unknown until now - is under attack by hackers wielding manipulated PDFs, sparking alarm across global user bases. Since December, activity has persisted without pause; findings come from analyst Haifei Li, who traced repeated intrusions back months. 

What stands out is the method: an intricate exploit resembling digital fingerprinting, effective despite up-to-date installations. Even patched systems fall vulnerable to this quietly spreading technique. Open a single infected PDF, then the damage begins - little else matters after that. This method spreads quietly because it leans on normal software behaviors instead of obvious malware tricks. 

Instead of complex setups, it taps into built-in functions like util.readFileIntoStream and RSS.addFeed, tools meant for routine tasks. Because these actions look ordinary, alarms rarely sound. Information slips out before anyone notices anything wrong. What makes this flaw especially risky isn’t just stolen information. As Li points out, it might allow further intrusions - such as running unauthorized code from afar or breaking out of restricted environments. Control over the affected device could then shift entirely into an attacker’s hands, turning a minor leak into something far worse. 

Examining deeper, threat analyst Gi7w0rm noticed fake PDFs in these operations frequently include bait written in Russian. With topics tied to current oil and gas industry shifts, the material appears shaped deliberately - aimed at certain professionals to seem believable. Though subtle, the choice of subject matter reflects an effort to mirror real-world events closely. 

Still waiting, Li notified Adobe about the flaw earlier - yet when details emerged, a fix wasn’t available. Without an update out yet, anyone opening PDFs from outside channels stays at risk. For now, while waiting for a solution, specialists urge care with PDFs - especially ones arriving by email or unknown sources. 

Watch network activity closely; odd patterns like strange HTTP or HTTPS calls may point to the vulnerability being used. Unusual user-agent labels in web requests could mean trouble already started. One more zero-day surfaces, revealing how hackers now lean on familiar file types and common programs to slip past security walls. 

While the flaw stays open, sharp attention and careful handling of digital files become necessary tools for staying protected. Though fixes lag behind, cautious behavior offers some shield against unseen threats waiting in plain sight. 
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Cyber Security
advance payment scams and money laundering Apple Apple device security Apple Pay call scams Cyber Fraud Cyber Security

Apple Pay Scam Surge Targets iPhone Users With Fake Fraud Alerts and Urgent Calls

 

A fresh surge in digital deception now sweeps through global iPhone communities - fraudsters twist anxiety into action using counterfeit Apple Pay warnings. Moments of panic open doors; criminals slip in, siphoning cash before victims react. Across continents - from city hubs in America to quiet towns in Europe - the pattern repeats quietly, yet widely. These traps snap shut fast: funds vanish while confusion lingers behind. 

A fake alert arrives by text, pretending to be from Apple, saying there is odd behavior on someone’s Apple Pay. Usually, it holds a contact line, pushing people to dial right away if they want to block what seems like theft. Pressure builds fast - this rush matters, because confusion helps trick targets into moving before checking facts. Right away, after the call connects, the person speaking is actually a fraudster pretending to be from Apple support, a financial institution employee, or sometimes even someone claiming police authority. 

Often beginning mid-sentence, these criminals rely on rehearsed dialogue - sometimes knowing bits of private facts - to appear legitimate. Driven by deception, their aim involves getting individuals to disclose confidential credentials like login codes, temporary access numbers, or credit account specifics. Instead of helping, they push for immediate fund transfers using false claims about protecting digital profiles. What makes these attacks effective isn’t code - it’s mimicry paired with pressure. Fake sites appear almost identical, pulling people in through urgency instead of malware. 

Access unfolds when someone hands over a verification number, thinking it's routine. Sometimes, approval prompts arrive disguised as normal alerts - clicking confirms access for thieves. Control shifts without force; consent does the work, quietly. Alerts pretending to come from Apple might seem convincing. Still, the firm emphasizes it never reaches out first to ask for login details or access codes. Messages showing up without warning, particularly ones demanding quick replies, deserve careful attention. 

Instead of responding, consider them suspicious by default. Official communications will not pressure anyone into instant decisions. Should you spot something off, snap a picture of the message and send it straight to Apple’s dedicated fraud inbox. Above all else, stay clear of phone numbers or links tucked inside those alerts - get in touch only via trusted paths marked out by Apple itself. Scammers cast a wider net than just Apple. 

Pretending to be support agents from well-known tech giants - Microsoft, say, or Google - is common practice among cyber actors aiming at regular people, showing how manipulation methods keep evolving across digital spaces. Surprisingly, fake Apple Pay messages show how clever online thieves have gotten lately. Because such tricks now happen so often, staying alert and acting carefully matters more than ever. 

Unexpected notifications should always spark doubt - never hand out private details without verifying first. Real businesses do not demand quick decisions by email or text message, a fact worth repeating quietly to oneself when pressured.
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Sanctioned Exchange Breach
Africa under cyber threats Blockchain Forensics Investigation Cross Chain Transaction Tracking Cryptocurrency Security Risks Cyber Security Darknet Financial Networks Sanctioned Exchange Breach

$13.74M Exploit Leads to Closure of Sanctioned Grinex Exchange Amid Intelligence Concerns


 

As a consequence of a reported security breach valued at approximately $13.74 million, Grinex, a cryptocurrency exchange registered in Kyrgyzstan, has been suspended from operations as a consequence of sanctions imposed by both the United States and the UK in the previous year. 

Based on the platform's description of the incident, it alleges the involvement of Western intelligence-linked actors in a highly coordinated cyber intrusion. Consequently, unauthorized access to user assets exceeding 1 billion rubles resulted, prompting a temporary suspension of operations while internal containment and assessment procedures were implemented. 

The company further asserted in its official disclosure that the compromise was of a level of sophistication that matches state-grade cyber capabilities. This suggests that advanced tools and infrastructure have been used beyond typical cybercriminal activity. According to Grinex, preliminary forensic analysis indicates a targeted operation that is likely to undermine perceptions of financial stability within sanctioned ecosystems in order to undermine perceived financial stability. 

Additionally, the exchange outlined that its systems had been subjected to persistent probing and hostile activity since inception, and framed the latest incident as an important escalation in an ongoing pattern of attacks that have attempted to weaken the exchange's financial stability and operational environment. It has become increasingly difficult to assess Grinex’s potential continuity with previously sanctioned infrastructure following further investigations into its operational lineage and transactional footprint, particularly since multiple blockchain intelligence assessments have linked it to the defunct Garantex ecosystem. 

The United States Treasury first designated Garantex in April 2022 on allegations that it assisted ransomware-related laundering activities through darknet markets such as Conti and Hydra. When authorities cited more than $100 million in illicit transaction processing and sustained exposure to money laundering networks, the company was subjected to renewed restrictions in August 2025. 

As a result of enforcement actions, analysts from Elliptic and TRM Labs have concluded that Grinex may have effectively absorbed Garantex's user base. During this process, Grinex deployed a ruble-pegged stablecoin mechanism identified as A7A5, which maintained liquidity flows and maintained transactional continuity despite regulatory pressure.

On-chain intelligence has also mapped a wider ecosystem of interconnected exchanges, according to Elliptic. Rapira, an exchange incorporated in Georgia with a presence in Moscow, has executed cryptoasset transfers to and from Grinex worth more than $72 million, reinforcing concerns regarding persistent sanctions circumvention channels linked to Russian financial institutions. 

Elliptic has independently corroborated the timeline of the $13.74 million asset compromise, indicating that the breach occurred at approximately 12:00 UTC on April 15, 2026 and then the assets were rapidly dispersed across both TRON and Ethereum networks. An attacker is believed to have systematically converted USDT holdings into liquid and less traceable assets such as TRX and ETH to mitigate the risk associated with issuer-level freezing mechanisms. 

The TRM Labs team has since identified approximately 70 blockchain addresses associated with this incident, as well as highlighting a concurrent disruption at TokenSpot, a Kyrgyzstan-based exchange suspected of operating in conjunction with Grinex. TokenSpot initially attributed service interruption to routine maintenance through its Telegram communication system, however subsequent activity indicated partial fund movements associated with the same consolidation wallet structure as the Grinex breach, although on a much smaller scale. 

A chain-analysis assessment further indicated the rapid conversion strategy employed during the incident, which was characterised as a well-established method of laundering assets that outpaced enforcement response by rapidly rotating assets from stablecoins into decentralized tokens. As well as raising the possibility of strategic deception within the incident narrative, the firm argued that given Grinex’s sanctioned status and historically opaque organizational structure, the breach may have been the result of either opportunistic cyberexploitation or a deliberately created false flag.

Although various theories have been advanced as to whether or not the event is to be attributed to any particular person, analysts agree that the event has materially disrupted a financial architecture long associated with sanctions evasion mechanisms and cross-border illicit liquidity flows. 

The Grinex incident highlights the evolution of the risk landscape, as cybersecurity analysts suggest that continuous monitoring of cross-chain fund movements is critical, stricter compliance alignment is necessary among exchanges operating in high-risk jurisdictions, and enhanced due diligence needs to be conducted regarding stablecoin liquidity routes. 

In light of this case, it is even more important that blockchain analytics firms, regulators, and financial platforms coordinate intelligence sharing to detect and disrupt laundering activities at a very early stage. Increasing the effectiveness of on-chain tracing capabilities, enforcing robust asset freezing protocols, and improving the transparency of exchange ownership structures will all help reduce systemic exposure to similar incidents in the future.
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LinkedIn privacy policy
browser extension scanning Cyber Security Data Privacy Concerns Fairlinked report LinkedIn lawsuit LinkedIn privacy policy

LinkedIn Faces Lawsuits Over Alleged Browser Extension Surveillance, Denies Privacy Violations

 

Two class-action lawsuits have been initiated against LinkedIn, accusing the platform of secretly monitoring users through browser extension scanning. The company, however, has strongly rejected the claims, stating that its practices are transparent and already outlined in its privacy policy.

"This is a house of cards built entirely upon a fabrication. We do disclose that we scan for browser extensions in our Privacy Policy, in order to detect abuse and provide defense for site stability," LinkedIn tells PCMag.

The lawsuits were filed on Monday in a U.S. District Court in California, following a report by German organization Fairlinked e.V.. The report alleges that LinkedIn uses a JavaScript file on its website to scan users’ Chrome browser extensions, checking for as many as 6,222 extensions. It further claims that this data could potentially be used to profile users or identify whether they are using competing tools.

LinkedIn disputes these allegations, explaining that the scanning is designed to combat web scraping activities. “We do not use this data to infer sensitive information about members,” the company tells PCMag. Its privacy policy also mentions that it may collect device and network-related data, including details about browsers and add-ons.

According to LinkedIn, the scanning mechanism serves as a protective measure to prevent unauthorized scraping of member profiles. Despite this explanation, the lawsuits argue that the company’s actions exceed reasonable expectations of user privacy and are seeking damages, along with a halt to the scanning practice.

"No reasonable user would read generalized references to URLs, browser data, add-ons, device features, cookies, automated systems, security, anti-abuse, fraud prevention, or similar matters and understand that LinkedIn would covertly interrogate the user’s browser, enumerate or infer installed extensions," one of the complaints says.

One of the lawsuits, filed by California resident Jeff Ganan, claims the practice violates the Electronic Communications Privacy Act and the California Comprehensive Computer Data Access and Fraud Act, among other statutes. A second lawsuit, filed by Nicholas Farrell, raises similar concerns with a stronger focus on alleged violations of California-specific laws.

Fairlinked, which represents commercial LinkedIn users, is also connected to the controversy through one of its board members, believed to be Steven Morell, founder of Teamfluence. LinkedIn claims it previously restricted accounts linked to Teamfluence over concerns about misuse of member data.

Commenting on the dispute, LinkedIn’s Vice President for Legal, Sarah Wight, said: “So we acted to restrict the accounts associated with Teamfluence. In retaliation for their accounts being suspended, in January, the creator of Teamfluence sought an injunction against LinkedIn in Germany,” adding, “I’m happy to report that the court thoroughly rejected Teamfluence’s claims, reaffirming LinkedIn’s ability to act swiftly and decisively against bad actors who access member data inappropriately."

In a separate statement to PCMag, LinkedIn added, “Unfortunately, this is a case of an individual who lost in the court of law, but is seeking to re-litigate in the court of public opinion without regard for accuracy,” referring to the ongoing controversy.

Fairlinked, however, disputes LinkedIn’s narrative, stating: “the court case Microsoft cites has nothing to do with the surveillance operation. That case concerns an account suspension. BrowserGate was never mentioned in the proceedings. Microsoft implies it prevailed. It did not. A motion for a preliminary injunction was denied. Both plaintiffs have appealed. The litigation is ongoing.”

The group has also challenged LinkedIn’s justification for scanning browser extensions, arguing that the scope of data collection goes far beyond security needs. “Scanning for 6,000 extensions and transmitting the results to third parties without user consent is not server protection. It’s an illegal spying operation,” it says. "The scan list contains thousands of extensions that have nothing to do with scraping. Religious extensions. Political opinion extensions. Job search tools. Neurodivergent aids. Amazon image downloaders. Pharmacy operations tools. Delivery schedulers. Clearly, server protection is not the goal here.”
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NHAI Ban Surveillance Tech
Chinese Cameras Cyber Security data security Highway Tolls NHAI Ban Surveillance Tech

India Bans Chinese Cameras at Highway Tolls Over Data Security Fears

 

India has taken a firm stand against potential surveillance risks by barring Chinese-made high-speed cameras from its highway toll plazas, prioritizing national security amid ongoing border tensions with China. The government's decision stems from concerns that data captured by these devices could be exploited for intelligence gathering, especially in conflict scenarios, prompting officials to replace existing installations and halt new imports of sensitive technology from China. 

This move aligns with broader efforts to reduce reliance on foreign hardware vulnerable to backdoors or remote access. The initiative is part of the National Highways Authority of India (NHAI)'s ambitious FASTag-enabled project to equip around 1,150 toll collection sites with advanced video devices that allow vehicles to pass without slowing down, enhancing traffic efficiency. 

Previously, cheaper Chinese cameras dominated due to cost advantages, but now NHAI has shortlisted trusted alternatives: Taiwan's VIVOTEK (a Delta Electronics unit), Germany's Robert Bosch GmbH, and US-based Motorola Solutions Inc. These suppliers' products, though pricier, undergo rigorous scrutiny to ensure no critical Chinese components. 

India's Standardisation Testing and Quality Certification Directorate (STQC) plays a pivotal role, testing cameras for highway tolls, CCTVs, and government deployments to verify origins and approve only those free of Chinese parts. This mirrors actions in Delhi, where over 140,000 Chinese CCTV cameras are being phased out in stages due to similar security worries.Companies like Hikvision and Dahua face effective bans on internet-connected video equipment, reflecting a nationwide push against perceived data vulnerabilities. 

The decision underscores persistent trust deficits despite recent India-China diplomatic thaws, rooted in decades-old border disputes. Globally, nations like the US, UK, and Australia have imposed restrictions on Chinese surveillance tech—Washington's watchlist targets over 130 firms with military ties, while the UK excluded Huawei from telecoms—fearing espionage via embedded software. India's proactive stance safeguards critical infrastructure handling vast vehicle data, including license plates and movements. 

While costlier, the shift bolsters digital sovereignty and sets a precedent for secure tech procurement in sensitive sectors. As India expands its highway network, this policy ensures smoother tolling without compromising security, signaling a strategic pivot toward reliable international partners.
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Windows 11
ChromeOS Cloud based services Cyber Security Google Microsoft Operating system Windows 11

Google Promotes ChromeOS Flex as Free Upgrade Option for Millions of Unsupported Windows 10 PCs

 





More than 500 million devices currently running Windows 10 are approaching a critical turning point, as many of them are not eligible for an upgrade to Windows 11 due to hardware limitations. This has raised growing concerns about long-term security risks once support deadlines pass. In response, Google is actively promoting an alternative, positioning its ChromeOS Flex platform as a free way to modernize aging systems.

Google states that older laptops and desktops can be converted into faster, more secure, and easier-to-manage devices by installing ChromeOS Flex. The system is cloud-based and designed to extend the usability of existing hardware without requiring users to purchase new machines. Although ChromeOS Flex has been available for some time, Google has now made adoption simpler by introducing a physical USB installation kit. Developed in partnership with Back Market, the kit allows users to install the operating system more easily. It is priced at approximately $3 or €3, is reusable, and is supported by recycling-focused efforts such as Closing the Loop to reduce electronic waste.

The timing of this push is closely linked to Microsoft’s decision to end mainstream support for Windows 10 in October 2025. That shift has forced users into a difficult position: invest in new hardware or continue using an operating system that will no longer receive full security updates. While Microsoft does offer an Extended Security Updates (ESU) program, it is only a temporary solution. For individual users, coverage extends for roughly one additional year, while enterprise customers may receive longer support under specific licensing agreements.

The transition to Windows 11 has also been slower than expected. Adoption challenges, largely driven by strict hardware requirements, have resulted in an unusually large number of users remaining on Windows 10 even after its official lifecycle milestone. This contrasts with Microsoft’s earlier expectations of a smoother migration similar to the shift from Windows 7 to Windows 10, which had seen broader and faster adoption.

Google is also emphasizing environmental considerations as part of its messaging. The company highlights that manufacturing a new laptop contributes significantly to its overall carbon footprint. By extending the lifespan of existing devices, ChromeOS Flex helps reduce landfill waste and avoids emissions associated with producing new hardware. Google further claims that ChromeOS-based systems consume around 19% less energy on average compared to similar platforms.

Despite this, switching away from Windows remains a debated decision. Many users rely on the Windows ecosystem for software compatibility, workflows, and familiarity. However, for devices that cannot support Windows 11, alternatives such as ChromeOS Flex present a practical workaround. Even in cases where users purchase new computers, older machines can still be repurposed using such operating systems, for example within households.

At the same time, Microsoft is continuing to strengthen its Windows 11 ecosystem. Devices already running Windows 11 are being automatically updated to newer versions to maintain consistent security coverage. The company is using artificial intelligence to determine when systems are ready for upgrades and applying updates accordingly. While a similar approach could theoretically be applied to Windows 10 devices that meet upgrade requirements, this has not yet been implemented. It remains uncertain whether this could change as future deadlines approach.

Recent developments have also drawn attention to user hesitation around Windows 11. Reports indicated that a recent update disrupted a key Start menu function, even as official communication suggested there were no outstanding issues. Subsequent updates and documentation now indicate that previously known bugs have been resolved, with Microsoft steadily addressing issues since the platform’s release in late 2024.

Additional reporting suggests that all known issues in the current Windows 11 version have been marked as resolved in official tracking systems. This reflects ongoing improvements, though it also underlines the complexity of maintaining stability across large-scale operating system deployments.

For enterprise users, Microsoft is extending support in more flexible ways. Certain legacy versions of Windows 10, including enterprise and IoT editions released in 2016, are eligible for additional security updates. These updates are delivered through ESU programs available via volume licensing or cloud solution providers. However, Microsoft continues to describe this as a temporary measure rather than a permanent extension.

For individual users, the situation is more restrictive. Extended Security Updates are limited in duration, and once they expire, devices will no longer receive security patches, bug fixes, or technical support. However, the continued availability of such programs suggests that support timelines may evolve depending on broader user adoption patterns.

The wider ecosystem is also seeing alternative recommendations. Some industry discussions encourage migration to Linux-based systems, while Google’s ChromeOS Flex represents a more consumer-friendly option. With hundreds of millions of devices affected, the coming months will play a crucial role in determining whether users remain within the Windows ecosystem or begin shifting toward alternative platforms.


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