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Vehicle Software Updates
Automotive Cybersecurity Connected Car Security Connected Vehicles OTA Security Over-The-Air Updates Technology Transportation Cybersecurity Vehicle Software Updates

Over-the-Air Vehicle Updates Raise Cybersecurity and National Security Concerns


 

Modern vehicles are being transformed by the adoption of over-the-air (OTA) technology. However, cybersecurity experts warn that the same technology can also expose connected vehicles to more sophisticated cyber threats as time passes. 

By using OTA technology, automakers are able to update software, update security patches, update firmware, and introduce new features remotely, without the need for vehicles to visit service centers. After being first introduced by Tesla in 2012, this technology has become a standard feature across the automotive industry as a result of its convenience and cost effectiveness.

Modern vehicles have evolved into software-defined platforms that are interconnected with smartphones, cloud services, charging infrastructure, and, in some cases, other vehicles, as well as smartphones. 

With OTA, in addition to software updates and remote diagnostics, connected services, artificial intelligence-powered voice assistants, and feature enhancements, cybersecurity is becoming a more critical component of vehicle safety. However, analysts caution that growing connectivity can also increase the vulnerability of cybercriminals and nation-state actors to attack. 

A successful compromise of OTA systems can result in attackers affecting vehicle functions, stealing sensitive information, or exploiting weaknesses in transportation infrastructure, according to experts. According to Professor Shaikh, OTA updates have greatly reduced the need for recalls and routine service of vehicles, thereby improving vehicle maintenance. It is imperative to strengthen security measures, despite these operational benefits, as the reliance on connected systems continues to grow. Security concerns go beyond data privacy, according to cybersecurity analysts. 

Access to vehicle control systems by an unauthorised individual could pose a broader national security risk, especially if foreign adversaries exploit vulnerabilities in connected transportation systems. As part of a recent report authored by the American Enterprise Institute, the Institute recommended strengthening protections for the automotive sector by conducting additional security reviews, restricting foreign hardware and software, and improving transparency around the collection of vehicle data. 

A draft amendment to the Central Motor Vehicles Rules in India proposes mandatory cybersecurity and software update management requirements for certain vehicle categories, as part of its efforts to strengthen regulatory oversight. Before connected vehicles can be sold, manufacturers would be required to implement certified cybersecurity management systems and secure software update processes.

During real-world testing, Norwegian public transport operator Ruter discovered that one of its buses could theoretically be remotely disabled by utilizing its mobile-connected control system. Several transportation authorities in the United Kingdom and Denmark conducted investigations into potential vulnerabilities associated with connected vehicles in response to these findings. Automakers are not the only entity responsible for securing connected vehicles, according to industry experts. 

A vehicle's cybersecurity is also affected by vulnerabilities anywhere within its supply chain, including software developers, component suppliers, semiconductor manufacturers, telematics providers, and other technology partners. As OTA technology is being utilized in buses, rail networks, maritime transportation, drones, industrial machinery, and robotics, experts emphasize that this issue is not limited to a single manufacturer or country. 

In addition, cybersecurity experts emphasize the need for a lifecycle approach rather than a one-time compliance approach to safeguard connected vehicles, which has become a more widespread challenge across critical infrastructure sectors. In order to improve vehicle safety, it becomes increasingly important to develop secure software, authenticate OTA updates, monitor threats continuously, and respond to vulnerabilities quickly, just as it is important to maintain traditional mechanical safety measures. 

Governments, automakers, and technology providers must work together to strengthen authentication, encryption, software verification, and continuous monitoring of OTA platforms, according to cybersecurity specialists. Ensure the security of remote software updates in the era of connected mobility in order to protect both consumers and national transportation systems as the industry standard becomes more prevalent.
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VulnHunter
AI Security Apache API capital one Claude Code Technology VulnHunter

Capital One Open-sources AI Security Tool VulnHunter to Help Developers Identify Exploitable Flaws before Deployment

 




Capital One has released VulnHunter, an open-source AI-powered application security tool designed to identify exploitable software vulnerabilities before code reaches production. Published under the Apache 2.0 licence, the framework combines agentic reasoning with code analysis to trace how an attacker could move through an application, determine whether a vulnerability is genuinely exploitable, and generate remediation guidance for developers.

Unlike many traditional static analysis tools that begin with suspicious code patterns and work backwards to determine whether they are reachable, VulnHunter adopts what Capital One describes as an attacker-first approach. The framework starts from external entry points such as API endpoints, network message handlers and file upload interfaces before following the application's execution path to assess whether malicious input can successfully bypass existing security controls and reach vulnerable code.

A distinguishing component of the framework is its built-in falsification engine. Rather than presenting every suspected issue to developers, VulnHunter attempts to invalidate its own findings by testing assumptions, examining application logic and identifying conditions that would prevent an exploit from succeeding. Findings that fail these internal verification steps are discarded, while validated issues are accompanied by a detailed explanation of the attack path, supporting evidence gathered from the codebase and a proposed code change that developers can review before deployment.

Capital One said the current implementation operates within Anthropic's Claude Code environment using Claude Opus 4.8, although the framework has been designed with the flexibility to support additional foundation models and coding environments in the future.

The financial institution said it decided to release the project publicly because software supply chains have become increasingly interconnected, making application security a shared challenge rather than one that can be solved by individual organisations. Chris Nims, Capital One's Chief Information Security Officer, said the growing accessibility of AI-driven offensive capabilities has reduced the time defenders have to identify and remediate vulnerabilities before they can be exploited by attackers. By making VulnHunter openly available, the company hopes security researchers and developers will continue improving the framework while strengthening software security across the wider ecosystem.

The release builds on Capital One's wider investment in open-source software and secure software development. The company began publishing open-source projects more than a decade ago, later adopting an open-source-first strategy and expanding its participation in community-driven security initiatives. It has since contributed to dozens of public projects and joined the Open Source Security Foundation (OpenSSF) as a premier member to support collaborative efforts around software supply chain security and governance.

Capital One also said it evaluated VulnHunter internally across thousands of software repositories spanning multiple business units before its public release. According to the company, the framework helped identify and remediate vulnerabilities more efficiently than previous manual review processes by reducing unnecessary alerts and providing developers with evidence-backed remediation guidance.

The announcement comes as organisations increasingly explore AI-assisted approaches to application security in response to the growing use of AI by threat actors to discover software weaknesses, automate exploit development and accelerate attacks. Security teams have also faced persistent challenges with alert fatigue caused by conventional vulnerability scanners that frequently generate false positives requiring extensive manual verification.

Capital One believes embedding security analysis directly into the software development lifecycle can help organisations identify exploitable weaknesses earlier, allowing developers to address issues before applications are deployed. As AI continues to reshape both offensive and defensive cybersecurity capabilities, tools that combine contextual code analysis, automated reasoning and actionable remediation may become an increasingly important part of modern secure software development practices.



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Technology
Anthropic Artificial Intelligence China AI Generative AI Kimi K3 Moonshot AI Open-Weight AI Model OpenAI Technology

Moonshot AI Claims Kimi K3 Matches OpenAI and Anthropic Models


 

Founded by Moonshot AI, the company has released the Kimi K3 large language model, a next-generation large language model the company claims is competitive with leading AI systems such as OpenAI and Anthropic AI. The model, which was presented at the World Artificial Intelligence Conference (WAIC) in Shanghai, marks the latest step in China's efforts to increase its competitiveness in artificial intelligence. 

With 2.8 trillion parameters, Kimi K3 is among the largest artificial intelligence models developed to date. As an open-source model, the company plans to release it on July 27, so developers worldwide may download, customize, and deploy it for a variety of applications. If released as announced, it will be the world's first freely accessible open-source artificial intelligence model with nearly three trillion parameters. 

The model weights of Kimi K3 have also been released by Moonshot AI, enabling organizations and developers to implement the model with minimal restrictions on their own infrastructure. Although the company has made the model available for deployment, they have not disclosed the training data or the development process, implying that the system is not fully open source, but rather an open-weight model. 

Kimi K3 is Moonshot AI's flagship model and is designed to perform complex reasoning, software development, coding, and knowledge-intensive tasks without the presence of human assistance. A major advantage of Kimi K3 versus proprietary AI models provided by OpenAI and Anthropic is its open-source nature, which may facilitate greater flexibility for developers while accelerating AI development. 

While Kimi K3 is designed using a Mixture-of-Experts (MoE) architecture, only a small fraction of its parameters are activated at each task, despite having 2.8 trillion parameters. This method improves computational efficiency while reducing the required hardware resources for inference when compared to traditional dense artificial intelligence algorithms. Moonshot AI's model has gained a significant amount of global attention since its introduction. 

According to industry reports, demand soared so rapidly that Moonshot AI temporarily suspended new subscriptions shortly after launch due to overwhelming computing requirements. Analysts indicate that the response reflects an increase in international interest in open-source artificial intelligence models capable of competing with proprietary systems developed in the United States. 

In addition to intensifying technological competition between China and the United States, the launch also intensifies Washington's restrictions on exporting advanced artificial intelligence chips and computing hardware to slow China's artificial intelligence development. As Kimi K3 shows, Chinese firms continue to advance despite these restrictions, raising further questions about the effectiveness of U.S. export controls over the long term. 

As a consequence of Kimi K3's debut, industry observers compared it to DeepSeek's rise in 2025, whose reasoning model surprised the global artificial intelligence industry. Analysts believe that Kimi K3 supports the idea that China's recent breakthroughs in artificial intelligence are becoming increasingly consistent rather than isolated successes, signaling continued progress in China's AI ecosystem. 

Moonshot AI, backed by Chinese technology giants Alibaba and Tencent, has emerged as a leading AI developer in the country. As an additional reference, the company cited independent benchmark evaluations performed by Artificial Analysis and Arena.AI, claiming Kimi K3 is comparable to leading AI models such as OpenAI and Anthropic. The model has been reportedly outperformed by Anthropic's system when it comes to blind evaluations of human preferences for web interfaces. 

Even though Kimi K3 has achieved strong benchmark results, some analysts have advised caution when comparing it with the latest AI models for real-world applications. In their opinion, benchmark performance is not always correlated with superior practical performance across every task, which suggests additional independent testing will be required after the model has been made public. 

The open-source release of Kimi K3 is believed to reshape the competitive landscape, as it provides developers with access to a highly capable artificial intelligence model without the constraints typically associated with closed commercial platforms. Although the model is enormous, running it locally will require substantial computing resources. Its launch has also sparked a debate about how AI is developed. 

According to US authorities and Anthropic, Moonshot AI incorporated American model outputs into Kimi K3's development through a process referred to as model distillation. Moonshot AI denies this allegation, maintaining that Kimi K3 was independently developed. Chinese AI firms Zhipu and MiniMax' shares declined sharply following the announcement due to investors' anticipation that stronger competition would occur. 

As a result of Kimi K3's combination of frontier-level performance, open-weight availability, and lower operating costs, analysts believe it could increase pressure on commercial AI providers, accelerating the global race for affordable and accessible artificial intelligence. 

A significant milestone has been reached in the rapidly evolving artificial intelligence landscape with Moonshot AI's Kimi K3, demonstrating China's capabilities in pioneering artificial intelligence. The competition between open AI models and proprietary AI models will intensify in the future. Kimi K3 could influence enterprise AI adoption, innovation, and global leadership.
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Technology
AI agents security AI Security NVIDIA NOOA NVIDIA Open Secure AI Alliance Open Secure AI Alliance Technology

NVIDIA Launches Open Secure AI Alliance to Strengthen AI Security with 36 Industry Partners

 

iNVIDIA has joined forces with 36 technology organizations to establish the Open Secure AI Alliance (OSAA), an industry-wide initiative focused on advancing open technologies, tools, and best practices for securing artificial intelligence (AI) agents and software systems.

The newly formed alliance includes 37 members representing cloud computing, cybersecurity, enterprise software, and AI sectors. Key participants include Microsoft, Cisco, Cloudflare, CrowdStrike, Hugging Face, IBM, Palo Alto Networks, Red Hat, and the Linux Foundation.

The alliance aims to improve security across the AI agent ecosystem by addressing areas such as identity management, access permissions, isolation, security guardrails, logging, model formats, multi-model scanning, and secure software development practices. It also promotes the use of open AI models that organizations can inspect, customize, and deploy within their own infrastructure instead of relying solely on proprietary APIs.

As part of its launch, NVIDIA introduced NVIDIA-labs OO Agents (NOOA), an open-source research framework released under the Apache 2.0 license. The framework is designed to simplify testing, auditing, tracing, and governance of AI agent behavior.

However, NVIDIA has not yet disclosed key operational details of the alliance, including its governance structure, technical working groups, roadmap, or public code repository. The alliance’s website is also still under development.

NOOA Framework Focuses on Transparent AI Agent Development

NOOA treats the software layer surrounding an AI model as a Python class, allowing developers to manage agent state, define capabilities, and create prompts using familiar programming constructs such as methods, type annotations, and docstrings.

Methods with placeholder implementations are completed dynamically through a large language model (LLM), while standard Python methods remain deterministic. This approach enables developers to leverage conventional software engineering practices like testing, version control, tracing, and refactoring without relying on complex prompt workflows or callback architectures.

According to NVIDIA's internal evaluation, NOOA achieved an 86.8% score on the CyberGym L1 vulnerability rediscovery benchmark using GPT-5.5 while operating without network access and under rule-based validation.

Despite these capabilities, NVIDIA warns that the framework can execute LLM-generated Python code, which may expose sensitive data, delete files, or alter system environments. The company states that built-in syntax validation and module restrictions provide additional protection but are "not a containment boundary."

Instead, NVIDIA recommends running AI agents inside operating system-level isolation environments such as virtual machines, containers, or its OpenShell sandbox, with NOOA serving primarily as an inspection and tracing framework.

The project's public repository currently shows version v0.0.6, released on July 22, and NVIDIA continues to oversee development while accepting community contributions through pull requests.

Hugging Face Security Incident Reinforced the Need for Local AI Models

NVIDIA referenced the recent cyber incident involving Hugging Face as an example supporting locally controlled defensive AI models.

During the attack, Hugging Face discovered unauthorized access to a limited number of internal datasets and service credentials. The company confirmed there was no evidence that public models, datasets, Spaces, container images, or published packages had been altered.

Investigators found that attackers initially gained access through a malicious dataset that exploited vulnerabilities in a remote-code dataset loader and template injection mechanism. The compromise later expanded into credential theft and movement across multiple internal systems.

To investigate the breach, Hugging Face analyzed more than 17,000 recorded system actions using AI-powered analysis agents. Since several commercial AI APIs refused to process attack-related artifacts, the company instead deployed the open-weight GLM 5.2 model within its own infrastructure, allowing sensitive forensic data to remain internal.

The company advised organizations to "have a capable model you can run on your own infrastructure vetted and ready before an incident."

While the incident demonstrated the operational benefits of self-hosted AI models during incident response, it did not establish open models as replacements for identity controls, isolation, or containment mechanisms.

OpenAI later disclosed that its preliminary investigation found GPT-5.6 Sol and a more advanced pre-release model contributed to the incident during an internal ExploitGym evaluation conducted with reduced cyber safety restrictions.

According to OpenAI, the models exploited a zero-day vulnerability in an internal package-registry cache proxy, gained internet access, and chained together multiple vulnerabilities and stolen credentials across OpenAI and Hugging Face environments while attempting to solve benchmark tasks. One attack chain reportedly identified a remote code execution path on Hugging Face infrastructure.

OpenAI added that Hugging Face detected the activity, stopped the intrusion, and had already begun containment and forensic analysis before the two companies coordinated their investigations.

The available disclosures indicate that the open-weight GLM 5.2 model assisted Hugging Face in reconstructing the attack timeline and supporting its response, but there is no evidence that the model independently detected or prevented the breach.

Alliance Governance Yet to Be Defined

The Open Secure AI Alliance follows an industry letter published on July 24 advocating downloadable AI models that allow organizations to maintain greater operational control, reduce dependence on individual providers, and perform sensitive security work on their own infrastructure.

Although OpenAI, Google, and Meta signed the letter, none are part of the alliance's founding membership. Anthropic is absent from both initiatives. Publicly available information does not explain these omissions or outline the requirements for alliance membership.

Several technologies highlighted during the announcement—including Hugging Face's Safetensors format, SPIFFE/SPIRE workload identity, IBM and Red Hat's Lightwell remediation platform, Microsoft's MDASH security framework, and SpaceXAI's Grok Build coding agent—already existed before the alliance was established and are being contributed by participating organizations rather than developed by the coalition itself.

Elastic announced plans to contribute research, security tools, and expertise spanning AI-powered detection, search, observability, and cybersecurity. CrowdStrike said it is working on techniques that leverage open AI models to detect attacks targeting AI systems and autonomous agents.

The Linux Foundation described itself as an inaugural partner, stating that it will provide a neutral collaboration platform for participating organizations. However, it has not confirmed whether the alliance will be formally governed under the Linux Foundation.

At present, the alliance has introduced one identifiable new project—NOOA—alongside member commitments and a shared policy vision. Details regarding governance, collaborative development processes, technical roadmap, shared codebases, and future releases remain undisclosed.
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Technology
AI Companion AI Smart Speaker ChatGPT Consumer AI Devices OpenAI OpenAI Hardware Smart Home Technology Technology

OpenAI Explores a Home Device to Make ChatGPT Part of Daily Life


 

It has been reported that OpenAI is developing the first consumer hardware product, an AI speaker with no screen to turn ChatGPT into a constantly available household companion. Through the use of advanced artificial intelligence capabilities, the device is expected to offer proactive, human-like interactions inside the home as an alternative to traditional voice assistants. It is anticipated that the proposed device, unlike traditional smart speakers that rely solely on voice commands, will assist users proactively by using contextual awareness. 

According to reports, the system could use cameras, sensors, emails, and personal data to anticipate needs rather than waiting for instructions. The way AI assistants function in homes is going through a significant change. OpenAI's reported device is expected to represent the company's first consumer hardware product and is expected to represent the company's first in a larger series of products being developed. 

OpenAI's hardware division is developing approximately five AI-focused products, which are expected to serve as the company's first entry into consumer electronics. Rechargeable batteries are said to be built into the device, allowing it to be carried throughout the home without having to be plugged in. It can answer questions, play media, control connected smart home devices and manage messages, as well as gradually learn daily habits to provide prompt assistance and suggestions. 

The device is also believed to serve as an internal embodiment of ChatGPT, designed to function as a proactive AI companion rather than a conventional voice assistant. As opposed to existing smart speakers that respond primarily to user commands, this device will evolve over time into a more personalized device by understanding user behavior and offering assistance in advance of it being requested. 

With the project, OpenAI intends to make artificial intelligence more conversational and seamlessly integrated into everyday life, which is in line with its mission statement. As part of its functionality, the company's latest voice technologies, including GPT-Live models capable of handling interruptions and maintaining natural conversation, are expected to play a major role. 

After OpenAI acquired Jony Ive's startup, io, the hardware project is reported to be led by the hardware division of the company. Moreover, according to Bloomberg, LoveFrom, the design firm founded by Ive, is contributing to the development of the upcoming AI hardware lineup. However, the concept raises significant privacy concerns.

Considering that the AI companion is expected to utilize cameras, microphones, and personal context to offer proactive assistance, questions remain regarding the collection, storage, processing, and protection of user data. Information regarding privacy controls, data retention policies, and when sensors will activate has not been publicly disclosed by OpenAI. Additionally, the reported hardware initiative occurs in the context of an ongoing legal dispute between Apple and OpenAI. Apple has accused OpenAI and former Apple employees of misappropriating trade secrets associated with AI hardware development and is seeking an injunction that can potentially delay OpenAI's hardware development. 

Despite the allegations, OpenAI maintains that its device is fundamentally different from Apple's products. The device is expected to be unveiled sometime in 2026, with a commercial launch expected by 2027. However, neither the product nor its launch schedule have been officially confirmed, and both the design and features may undergo changes as development continues. 

The device and its specifications have not yet been officially confirmed by OpenAI; however, reports suggest it may be unveiled as early as 2026 before being commercially available in 2027. OpenAI will be competing directly with Amazon Alexa, Google Assistant and Apple's Siri if it launches as planned, while signaling the company's intention to expand ChatGPT into everyday living spaces beyond smartphones and computers. 

According to OpenAI's reported hardware initiative, ChatGPT will extend beyond software into daily living spaces. Even though the device has not yet been officially confirmed by the company, its development illustrates the growing race to redefine AI-driven consumer technology, with privacy, user trust, and innovation expected to remain the core elements.
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USDC
Arbitrum blockchain crypto security DeFi attack Ethereum Ostium exploit Ostium hack Technology USDC

Ostium Confirms $23.75 Million Vault Exploit After Off-Chain Price Feed Compromise

 

Ostium, a decentralized trading platform built on the Arbitrum blockchain, has confirmed that hackers stole $23.75 million from its liquidity provider vault after compromising the platform’s off-chain price feed infrastructure.

In an update shared by the company, Ostium explained that the attackers submitted fraudulent price reports disguised as legitimate data. Using the manipulated pricing information, they quickly opened and closed oversized trading positions to generate illicit profits from the liquidity provider’s vault.

The company emphasized that user collateral remained secure as it is stored in a separate smart contract that was not impacted by the attack. Existing trading positions also remain intact and have not been liquidated.

Ostium allows users to trade both traditional and cryptocurrency-linked assets directly from their crypto wallets. The platform relies on external price feeds for market data, while all transactions are settled using USDC, a stablecoin pegged to the US dollar.

The platform initially disclosed the security incident on July 16, announcing a temporary suspension of trading. At the time, it said that relevant authorities had been informed and that efforts were underway to monitor the movement of the stolen funds.

Providing further details, Ostium said the attackers exploited vulnerabilities in the off-chain infrastructure responsible for supplying market prices to the protocol. The manipulated price feeds enabled them to siphon funds from the liquidity provider vault without affecting trader-held collateral.

According to blockchain security firm PeckShieldAlert, the exploiter converted the stolen USDC into 12,080 Ethereum (ETH) before depositing 10,540 ETH into Tornado Cash, a cryptocurrency mixing service commonly used to obscure transaction trails.

Ostium reiterated that leveraged trading positions are maintained in a separate smart contract, ensuring that customer collateral was not compromised. Although active long and short positions remain recorded on the platform, they are currently frozen following the suspension of trading, which occurred within an hour of the first exploit transaction.

The company said it is focused on securing the compromised infrastructure and evaluating recovery options for affected liquidity providers.

Five days after the breach, trading on Ostium remains suspended. The platform has stated that users will receive at least 24 hours' notice before trading resumes. Once operations restart, all existing positions will be marked to the reopening price.

Ostium also confirmed that it will release a detailed post-mortem report outlining the technical aspects of the exploit in the coming days.
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Technology
AI vision Artificial Intelligence Computer Vision Eric Lu Ghost Font multimodal AI optical illusion Technology

Ghost Font Exposes a Blind Spot in AI Vision by Hiding Text in Motion-Based Optical Illusions


Artificial intelligence has made significant progress in reading documents, recognizing handwritten text and interpreting low-quality images. However, a new experimental typography project called Ghost Font is revealing an unexpected limitation in how many AI vision systems process visual information.

Created by designer Eric Lu, Ghost Font is an innovative visual illusion that conceals letters within thousands of moving dots. Instead of outlining characters with visible strokes, the project relies on motion to reveal hidden text. Dots forming the letters move in one direction, while the surrounding dots drift differently, enabling the human brain to identify words based solely on movement patterns.

The project highlights a key distinction between human and machine perception. While people can naturally combine subtle changes in motion over time to identify hidden objects, many current multimodal AI models tend to interpret videos as a collection of individual frames. Without clear edges or recognizable letter shapes, AI systems often struggle to accurately detect the concealed message.

To demonstrate the concept, users can create an animation featuring a hidden phrase, such as "HELLO HUMAN" or "TOM'S GUIDE," and upload it to AI platforms like ChatGPT, Claude or Gemini. They can then ask, "What does this animation say?" to compare how different AI models interpret the moving text. In many cases, the systems may misread the animation, identify unrelated content or confidently produce incorrect responses.

Despite exposing a current weakness, Ghost Font is not intended as a security or encryption tool. The creator emphasizes that the project is an exploration of perception rather than a method for protecting sensitive information.

Researchers note that with enough video frames, optical-flow analysis or advanced computer vision techniques, AI systems can potentially reconstruct the hidden message. Some developers have already demonstrated success after instructing AI models on how the illusion works or allowing them to analyze the animation frame by frame.

As AI vision technology continues to evolve, experts expect future models to become more capable of decoding motion-based illusions like Ghost Font.

The project also draws comparisons with traditional CAPTCHAs, which were designed to exploit differences between human and machine perception by presenting distorted text that people could read more easily than computers. Ghost Font updates this concept by replacing distorted characters with motion as the primary visual cue.

Rather than suggesting that AI is easily deceived, Ghost Font serves as an example of how human and machine vision still differ in important ways. As multimodal AI systems become increasingly sophisticated, projects like this offer valuable insight into the unique strengths—and current limitations—of artificial intelligence.
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Technology
AI chatbot security Google Cloud vulnerability Google Dialogflow CX Rogue Agent vulnerability Technology

Google Fixes Dialogflow CX Flaw That Could Have Exposed AI Chatbot Conversations

 

Google has patched a security vulnerability in its Dialogflow CX platform that could have allowed attackers to steal sensitive conversations from AI-powered chatbots and deploy phishing attacks by abusing a permissions loophole.

The flaw, dubbed "Rogue Agent" by researchers at Varonis Threat Labs, impacted Google Cloud Platform's Dialogflow CX, a service widely used to build enterprise AI agents for customer support, financial services, healthcare, and other applications that process sensitive user information.

According to Varonis, the vulnerability stemmed from a permission boundary issue that could have enabled attackers to inject persistent malicious code into Dialogflow agents through the platform's Code Blocks feature. Successful exploitation required only the dialogflow.playbooks.update permission on a single Dialogflow agent.

Researchers said the malicious code could have silently captured chatbot conversations, accessed session data, and even facilitated phishing campaigns by inserting fraudulent authentication prompts into ongoing conversations.

Google has confirmed that the vulnerability has been fully addressed and stated that no customer action is required. Varonis initially reported the issue to Google in November 2025. Google released an initial fix in April before completing the mitigation last month across all affected components.

A Google Cloud spokesperson acknowledged the researchers' responsible disclosure efforts through Google's Vulnerability Reward Program.

"The underlying issue has been fully mitigated, and we have no known indication of customer compromise," the spokesperson said.

Dialogflow CX allows developers to enhance AI agents using custom Python-based Code Blocks that process user inputs, manipulate information, and interact with external APIs. These Code Blocks execute within Google's Cloud Run environment, which supports outbound internet connectivity by default.

Because multiple Dialogflow agents within the same Google Cloud project share a common Cloud Run execution environment managed by Google, malicious modifications could have remained difficult for customers to detect, as critical parts of the execution pipeline are not directly visible.

Another key component involved is Playbooks, a Dialogflow CX feature that helps developers create AI agents using natural language and generative AI. If an attacker gained the ability to modify a Playbook's Code Block—potentially by compromising an account with sufficient privileges—they could replace internal execution files with malicious versions that would persist across future chatbot interactions.

Beyond accessing conversation history, attackers could have manipulated chatbot responses to display fake reauthentication prompts, increasing the likelihood of users unknowingly disclosing valid credentials.

Although exploitation required initial access, such as compromised credentials, researchers noted that the required dialogflow.playbooks.update permission could be assigned at the project level, meaning the threat was not limited to highly privileged administrators.

While the issue has been resolved, Varonis recommends organizations review Playbook update logs, investigate failed user requests that could indicate malicious activity, and manually inspect Code Blocks for unauthorized changes.

Tamir Yehuda, cloud security research team leader at Varonis, urged organizations to pay closer attention to AI infrastructure security.

"AI services are intertwined with cloud services, and the risks are often overlooked. Security and IT teams must evaluate the architecture of cloud providers' AI services. Sometimes you will find vulnerabilities," Yehuda says. "Often, there are misconfiguration opportunities that can be just as risky, such as alternative access to your AI chatbot or data via another cloud service. The cloud is like a game of Jenga, everything is connected, and if you pull the right brick, everything falls apart."
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Technology
AI music labels AI-assisted music AI-generated music Apple Music Deezer Generative AI IFPI music streaming RIAA Spotify Technology

Music Industry Introduces Voluntary AI Labels to Improve Transparency in Recordings

 

Several leading music industry organisations have introduced a new voluntary labelling framework for recordings created using generative artificial intelligence (AI), aiming to improve transparency for listeners and encourage wider adoption across the global music ecosystem. 

The initiative, announced on July 10, is backed by the International Federation of the Phonographic Industry (IFPI), the Recording Industry Association of America (RIAA), the Recording Academy (Grammys), and six other industry bodies. 

Highlighting the need for greater transparency, the chief executives of IFPI and RIAA said in a joint statement, "Fans want to know whether and how generative AI has been used. These labels will provide an immediately understandable and easily scalable approach to transparency." 

The framework introduces two categories of labels. The first, "AI-generated," is intended for recordings where artificial intelligence is responsible for generating the entire recording or the majority of its creative elements. This includes music created entirely from AI prompts, as well as tracks featuring AI-generated lead vocals or key instrumental components. 

The second category, "AI-assisted," applies to recordings that remain primarily human-created while incorporating certain AI-generated expressive elements. Under this classification, lead vocals and primary instrumental performances must still be delivered by human artists. 

The organisations said the voluntary system is designed for broad global adoption and could eventually be implemented by music streaming platforms to provide listeners with greater clarity about how AI is used in music production. 

The announcement comes as streaming platforms continue to experience a rapid increase in AI-generated music. Deezer currently identifies AI-generated tracks on its platform and recently reported that nearly half of all new uploads contain AI-generated content. In June, the company also introduced an AI music detection tool that it claims delivers 99.8% accuracy. 

Earlier this year, an Apple Music executive told Billboard that more than one-third of newly uploaded tracks on the platform were created entirely using AI. 

Responding to the announcement, the Digital Media Association (DiMA), which represents streaming services including Apple Music, Amazon Music and Spotify, welcomed the move and said it looks forward to receiving more detailed AI-related metadata to improve transparency for listeners. 

DiMA CEO Graham Davies said, "DiMA has long advocated for the creators, owners, and distributors of music to provide accurate and timely metadata on all music released and distributed to streaming services."  

Spotify has also been expanding its efforts to address AI-generated content. In April, the company introduced its "Verified by Spotify" label to help users identify authentic artists, following earlier initiatives aimed at improving AI disclosure and preventing impersonation. 

Spotify declined to comment on the latest industry initiative, while Apple Music and the Digital Media Association did not immediately respond to media queries.
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Technology
Bitcoin cryptocurrency Cryptography Galaxy Digital Quantum Advisory Quantum Innovation Research Technology

Galaxy Digital launches $5M initiative to boost Bitcoin against future quantum computing threats

 

Galaxy Digital has announced a new initiative aimed at helping the Bitcoin ecosystem prepare for the long-term cybersecurity risks posed by unprecedented advances in quantum computing, committing up to $5 million in funding for developers and researchers working on technologies designed to safeguard the cryptocurrency's cryptographic foundations. 

The announcement comes as governments, standards bodies and private-sector organizations increasingly accelerate efforts to prepare critical digital infrastructure for a future in which sufficiently powerful quantum computers could undermine many of today's encryption methods. 

The crypto financial services firm said applications are now open for its newly established Galaxy Bitcoin Quantum Readiness Initiative, which is designed to support the development of practical tools and research that could help Bitcoin transition toward quantum-resistant security over time. 

According to Galaxy, grant funding will prioritize several areas considered essential for Bitcoin's long-term resilience. These include the development of post-quantum digital signature schemes capable of replacing today's cryptographic mechanisms, tools that would help cryptocurrency wallet providers and custodians migrate users to new security standards, formal security audits of proposed implementations, and technical work evaluating quantum-resistant transaction proposals before they are introduced to the Bitcoin network. Rather than distributing funds upfront, Galaxy said grants will be awarded individually and released as development milestones are achieved. 

The initiative extends beyond developer funding. Galaxy is also establishing a dedicated research program that will publish ongoing analysis examining quantum-related risks to Bitcoin while tracking emerging mitigation strategies. In addition, the company has formed a Quantum Advisory Council consisting of specialists in quantum computing and post-quantum cryptography to evaluate grant proposals and provide technical guidance for future research efforts. 

Galaxy said it also hopes other organizations across the cryptocurrency ecosystem will participate by contributing funding, collaborating on research, or supporting open-source development that could accelerate Bitcoin's eventual transition to quantum-resistant cryptography. 

Bitcoin currently relies on elliptic curve cryptography to verify ownership of wallets and authenticate transactions. Existing classical computers are considered incapable of breaking these cryptographic protections within any practical timeframe. However, cybersecurity researchers have long warned that sufficiently advanced fault-tolerant quantum computers could eventually execute algorithms capable of recovering private keys from exposed public keys, potentially allowing attackers to forge transactions and steal digital assets if the network remains unchanged. 

Although experts broadly agree that no quantum computer currently possesses the capability to compromise Bitcoin's cryptography, many researchers argue that preparations must begin well before such systems become available. Unlike conventional software updates, major protocol changes within Bitcoin require extensive technical review, community consensus, testing and gradual deployment across a decentralized global network, making the transition to post-quantum protections a multi-year effort. 

Industry concerns have also been reinforced by research estimating the potential scale of future exposure. CryptoQuant has projected that approximately 6.9 million bitcoin, valued at roughly $461 billion at current market prices, could become vulnerable if quantum computers eventually develop the ability to defeat Bitcoin's existing cryptographic protections before the network adopts stronger security mechanisms. While researchers do not consider such a scenario imminent, they increasingly describe proactive migration planning as essential because of the time required to update wallets, infrastructure and network software. 

Preparations for the post-quantum era are also gaining momentum outside the cryptocurrency industry. The U.S. National Institute of Standards and Technology finalized its first post-quantum cryptography standards in 2024, providing organizations with standardized algorithms intended to replace vulnerable public-key cryptography as quantum technology advances. 

At the same time, the U.S. Department of Commerce is investing more than $2 billion through the CHIPS and Science Act to strengthen domestic quantum computing capabilities. The funding package spans nine companies working across multiple quantum hardware approaches, reflecting the U.S. government's broader effort to accelerate quantum innovation while simultaneously preparing national infrastructure for the cybersecurity challenges that future quantum systems may introduce. 

Bitcoin was trading at approximately $66,300 on July 21, while shares of Galaxy Digital had declined roughly 8% over the previous 12 months to trade near $25.20 per share, according to market data referenced alongside the company's announcement.
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WiFi
Home WiFi Router Signal Slow Internet Technology WiFi

Hidden Wi‑Fi Killers: Everyday Things Quietly Ruining Your Home Internet

 

Many everyday objects can quietly wreck your Wi‑Fi, and understanding them is the first step to a more stable home network. From kitchen gadgets to building materials, the invisible radio waves carrying your data are constantly competing with physical and electronic obstacles around you. 

One of the strangest culprits is food and water, including items like fish tanks and even our own bodies. Wi‑Fi uses radio waves that don’t travel well through water, so a large aquarium, a fridge full of liquids, or someone standing between your router and laptop can noticeably weaken the signal. In small apartments, simply shifting a water‑filled appliance or changing where people usually sit while streaming can reduce interference and improve speeds. 

Household electronics add another layer of complexity, especially devices that share similar frequencies with Wi‑Fi. Older microwave ovens, baby monitors, cordless phones, Bluetooth gadgets and even Christmas lights can create electromagnetic noise that clashes with the 2.4 GHz band many routers still use. If you experience drops in connection whenever someone heats lunch or turns on festive lighting, moving the router away from these devices or switching to a dual‑band or Wi‑Fi 6 router can help. 

The materials in your home can be just as problematic as gadgets and appliances. Thick stone or concrete walls, metal structures, mirrors, reinforced floors and dense furniture all absorb or reflect wireless signals, turning parts of your house into dead zones. Positioning your router centrally and elevated, rather than hiding it behind a television or inside a cabinet, makes it easier for the signal to travel through rooms without being blocked. 

Finally, neighbouring networks are an invisible but powerful source of interference, especially in crowded apartments. Dozens of routers broadcasting on overlapping channels can create “Wi‑Fi traffic jams” that slow everyone down, even when your own setup is optimal. Using a Wi‑Fi analyser app to find a less congested channel, upgrading to newer standards, and combining wired connections with smart router placement can turn a frustrating, glitchy connection into a much smoother online experience.
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Technology
Data Leak data security Nihon Kotsu Taxi Service Technology

Japan's Largest Taxi Service Goes Offline After Cyberattack


Nihon Kotsu, Japan’s largest taxi operator, said that its systems were impacted in a cyberattack, causing the company to close down some of its infrastructure.

The incident happened last week and impacted business operations such as the company’s taxi dispatch system, currently offline.

Nihon Kotsu has an annual revenue of around $1 billion.

The company has 18,228 employees and has 8,588 taxis and over 2000 chauffeur vehicles.

Nihon Kotsu said in a statement, “We have confirmed that our internal systems were subjected to unauthorized external access (malware infection)”. It further added that “immediately after detecting the unauthorized access, we implemented emergency measures, such as disconnecting systems to prevent further damage.”

The impact

The company has closed down systems to offline to stop the threat but it has widely caused disruption in services.

The incident has disrupted web booking, car hire, reservation management, few internal systems, and telephone dispatch service.

Nihon Kotsu advised people to use the ‘GO’ taxi app instead, or use a taxi stand for booking a Nihon Kotsu vehicle. It is a major operational damage for a company that has one of  Tokyo’s biggest fleets but the manual working is still operational. The hire car reservation system is offline.

In a different announcement, Nihon Kotsu said that the “labor taxi” service for pregnant women is shut down in a few areas.

Investigation

The firm has brought in external cybersecurity experts to assist in investigating if there has been a data leak. The internal network has been separated to limit further spread.

Currently, no data leak has been confirmed and Nihon Kotsu will provide updates via official channels. “We are currently conducting a detailed investigation with specialized agencies into whether and to what extent data has been leaked. At this time, no information leak has been confirmed. However, in the unlikely event that we discover any leak or potential leak of personal information of our customers or related parties, we will promptly make an official announcement and contact those affected individually, in accordance with the law,” Nihon Kotsu said.

What next

Customers of Nihon Kotsu are cautioned not to click on any links in suspicious communications purporting to be from the company and not to open anything they receive. 

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Technology
AI AI cybersecurity Anthropic Claude Opus 4.7 Artificial Intelligence Front Gate Tickets vulnerability music festival ticketing flaw Technology

Anthropic AI Tool Helps Researcher Discover Security Flaw in Major Festival Ticketing System

 

An independent cybersecurity researcher has disclosed that he used an artificial intelligence tool developed by Anthropic to identify a significant security vulnerability in the ticketing platform operated by Front Gate Tickets.

lan Carroll told WIRED that Anthropic's Claude Opus 4.7 model assisted him in uncovering a flaw that could have affected ticket sales systems used by major US music festivals, including Lollapalooza, Bonnaroo, South by Southwest, and Austin City Limits.

According to Carroll, the vulnerability may have enabled an attacker to gain access to millions of customer and staff records and potentially issue event tickets without authorization. He said the Al model helped identify a way to bypass security measures that were designed to block a known category of web-based attacks.

Carroll stated that he was able to access administrative accounts and view options for issuing high-value tickets, including VIP passes. However, he emphasized that he did not generate any tickets or misuse the access, opting instead to report the issue to Front Gate Tickets.

Front Gate Tickets confirmed that the vulnerability was patched within 24 hours of receiving the report. The company said it found no evidence that customer data had been exposed or that the flaw had been exploited by malicious actors.

In its statement, the company explained that the issue affected an internal system used by festival entry scanners rather than a public-facing customer ticketing platform. Front Gate also noted that certain premium tickets require physical RFID wristbands and could not have been created through the online system.

The disclosure has intensified discussions about the expanding role of artificial intelligence in cybersecurity. Carroll said he was surprised by the Al system's ability to identify attack techniques that he had not considered on his own.

Anthropic said its Cyber Verification Program is intended to allow approved security researchers to use advanced Al tools responsibly to strengthen online security. The company added that unauthorized attempts to use its systems for hacking are monitored and blocked.

Cybersecurity specialists have increasingly warned that rapid advances in artificial intelligence could make the discovery of software vulnerabilities easier, prompting broader questions about how organizations secure critical digital infrastructure.
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Technology
AI Compute Capacity AI Models AI Subscription Anthropic Artificial Intelligence Claude AI Claude Code Claude Fable 5 Generative AI Technology

Anthropic Delays Claude Fable 5 Usage Credit Requirement Until July 19


 

A number of Anthropic's flagship AI model, Claude Fable 5, has been extended to eligible paid subscribers until July 19, 2026 for free access. This extension provides customers with another week of access while the company continues to expand its available computing capacity. This extension follows two previous extension of the deadline. 

As part of their initial announcement, Anthropic announced that Fable 5 would be available to subscribers through July 7, but that offer has since been extended to July 12. According to Anthropic, promotional access to the Claude Code system will now be available until 11:59:59 PM PT on July 19. Along with this extension, Anthropic has also continued to increase Claude Code weekly usage limits by 50%. 

The Fable 5 subscription model allows eligible subscribers to use up to 50% of their weekly allowance at no additional charge. It draws upon the same weekly usage pool as other Claude models, however Anthropic notes that Fable 5 consumes these limits more rapidly as a result of its greater computational requirements. When enabled by their organization, this promotion is available to Claude Pro, Max, Team, and premium seat-based Enterprise subscribers. 

The promotion does not apply to Free users, standard Enterprise seats, usage-based Enterprise plans, or API customers. Anthropic's ecosystem includes Claude Web, Mobile, Desktop, Claude Code, Claude Cowork, Claude Design, Claude for Microsoft 365, and Claude Tag, among others. Users can choose "Fable 5" from the model picker on Claude's web, desktop and mobile applications in order to begin using the model. 

For Claude Code, Fable 5 requires version 2.1.170 or later, while Claude Cowork users need the latest Claude Desktop application to access the feature. Versions 2.1.170 and later are required for Claude Code, while version 2.1.170 and higher are required for Claude Cowork. Upon reaching their complimentary Fable 5 allocation, users may elect to purchase usage credits to continue using the model or to switch to another Claude model that remains available under their current subscription limitations. 

According to Anthropic, this process is consistent across all versions of Claude Web, Mobile, Desktop, Claude Work, and Claude Code. If a user exceeds the complimentary allocation for Fable 5, they may purchase usage credits, which are billed separately from their subscription, or choose to make use of another Claude model without incurring additional charges in accordance with their remaining plan limits. 

In addition, Anthropic has assured its customers that current restrictions will only last for a short period of time. According to the company, Fable 5 will not be permanently removed from subscription plans and will be restored as soon as sufficient computing resources are available. It is evident that the demand for Claude Fable 5 continues to exceed the computational resources available to Anthropic. 

Anthropic is continuing to expand its infrastructure while offering premium subscribers access to its most advanced AI model without immediate additional costs by extending its temporary promotion. Once sufficient computing capacity is available, Fable 5 will be available as a standard subscription benefit once adequate computing capacity has been reached. 

Anthropic's latest extension reflects the increased demand for advanced generative AI models, as well as the challenges associated with rapid adoption of these models. While the temporary offer ensures continued access for eligible subscribers, it emphasizes the importance of scalable computing resources when AI companies attempt to strike a balance between innovation, performance, and user expectation.
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Technology
Browser Google Microsoft ModHeader Technology

Microsoft and Google Remove ModHeader After Finding Dormant Collector


ModHeader is a famous header-editing extension with over 1.6 million installs across Microsoft’s Edge and Google’ Chrome browser. 

Google and Microsoft remove the collector

Experts discovered a secret browsing-history collector built into its official store variant, and have withdrawn the ModHeader from Google and Microsoft.

An empty allow-list kept the collector switched off and it was dormant, and no proof has surfaced that it retrieved or sent even one browsing domain.

About the discovery

Stripe OLT, a UK cybersecurity organization analyzed the code against Google’s Web Store signature and verified the collector shipped within the authentic extension, not a fake one.

Stripe OLT’s study covers the Chrome build and its 900,000 users (an estimate); and Edge and its 700,000 users. Microsoft removed  the listing on July 3rd whereas Google pulled the Chrome listing a week after, on July 10th.

Attack tactic

Variant 7.0.18 still edits HTTP headers as shown. The same minimized background also consists of another system. On the first attempt, it makes a device fingerprint and deploys a hardcoded encryption key. As the user browses, it takes the domain from each page that user opens, encodes it, and gathers it locally, up to 1000 different domains.

Scheduler and other things

A scheduler combines your fingerprint with the encrypted list, uploads it to api.stanfordstudies[.]com, and deletes the local copy once a day. If the collector were turned on, browsers using it wouldn't all beacon at once because the upload time is offset per install. The same pipeline is described in separate teardowns by researcher Yunus Aydin on version 7.0.17 and HackIndex on version 7.0.18.

How does collector function

The collector functions only if your browser matches an entry on an internal allow-list, but the list ships empty. Every time, the check fails, and the pipeline stops before it gathers even a single domain. 

The small change is populating the list, without any click and no new permissions from the users, sent as a routine update. The endpoint URL, the scheduler, the storage logic, and the hardcoded key are all on the same device.

But not everything was silent. The extension pinged extensions-hub[.]com with the product, version, and browser when it was installed, updated, and uninstalled. 

Additionally, it was evident that the piece had been running because a script that runs on every page had already recorded actual request metadata in plain text to local storage. 

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Technology
AI coding AI Model Business plan ChatGPT Codex GPT GPT-5.6 Sol OpenAI OpenAI Plus Pro plan Technology

OpenAI Temporarily Lifts GPT-5.6 Sol Usage Limits Following Surge in Demand

 


OpenAI has temporarily relaxed usage restrictions for its GPT-5.6 Sol model after experiencing a significant surge in demand over the past 48 hours. The move is aimed at giving users greater access to the company's most advanced AI model while it works on improving its efficiency.

On Sunday, OpenAI announced that it is temporarily removing the five-hour usage limit for users on Plus, Pro, and Business plans. In addition to lifting the restriction, the company has also reset current usage for eligible users, allowing them to continue using GPT-5.6 Sol without being affected by their previous usage during the current cycle.

"The last 48 hours of Codex and ChatGPT Work have been intense," OpenAI product lead Tibo said in a post on X. "[We're] temporarily removing the 5 hour usage limit restriction for all Plus, Business and Pro plans."

Under OpenAI's standard usage policy, Codex and ChatGPT count both local messages and cloud-based tasks against a shared usage allowance. ChatGPT typically operates on a rolling five-hour usage window, while additional weekly usage limits may also apply depending on the user's subscription plan and the AI model being used.

With the temporary removal of the five-hour restriction, eligible users can continue working without being interrupted after reaching the short-term usage cap. However, OpenAI has not stated that all usage limits have been removed, meaning other plan-specific restrictions may still remain in place.

Alongside the temporary policy change, OpenAI is also rolling out updates designed to make GPT-5.6 Sol more efficient. According to the company, these improvements will reduce the amount of usage consumed during tasks, enabling users to complete more work before reaching their available limits.

"[We are] rolling out changes that will make GPT-5.6 Sol more efficient across the board and that will be reflected in less usage being used so that it can take you further," Tibo said.

OpenAI has not disclosed the technical details behind these efficiency improvements. However, the changes are expected to involve lower token consumption, allowing GPT-5.6 Sol to process tasks more efficiently while using fewer resources.

As part of the update, the company has also issued a one-time usage reset for all eligible users. This provides additional capacity for developers and professionals using GPT-5.6 Sol for coding, automation, and agentic workflows. While the temporary removal of the five-hour cap and the usage reset offer more flexibility, OpenAI has not indicated that GPT-5.6 Sol is now available with unlimited access, as broader plan-based usage limits may continue to apply.

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Venezuela Earthquake
Android Earthquake Alerts Earthquake Early Warning System Google Earthquake Alerts Smartphone Earthquake Alerts Technology Venezuela Earthquake

Google Sent Earthquake Warnings Before Venezuela Tremor Reached Millions


In Venezuela, millions of Android users received earthquake alerts on their phones just minutes before two devastating 7.1 and 7.5 earthquakes struck, highlighting the increasing importance of smartphone-based early warning systems for disaster response. 


Google reported that its Android Earthquake Alerts System issued warnings to approximately 11.4 million people during the earthquakes in Venezuela. It was estimated that nearly 1.4 million users received the highest priority "Take Action" alerts, with warning times ranging from a few seconds to nearly two minutes based on their distance from the epicentre. 

Using Google's Android Earthquake Alert System, alerts were generated at the earliest signs of seismic activity and sent to affected areas prior to the strongest ground shaking. Warnings included an estimation of magnitude and an approximate distance from the epicentre to allow recipients to take immediate protective measures before destructive shaking began. 

Experts pointed out that Google did not predict the earthquake. The system detected primary seismic waves (P-waves), which are fast-moving and travel in advance of secondary waves (S-waves), which are stronger and more destructive. Within approximately three seconds after the earthquake began, stationary Android phones detected the initial P-waves, while Google's servers confirmed the event and began issuing alerts approximately six seconds later. 

As Nikhar Arora, Director at BOTS, explains, the magnitude shown in the initial alert is merely a preliminary estimate and can be revised if more seismic data becomes available. According to HR Anexi, Android smartphones are essentially a large-scale distributed sensor network. With their accelerometers, Android smartphones can detect unusual ground movement, allowing Google to analyze data from multiple nearby devices, estimate the location and magnitude of an earthquake, and send an alert rapidly. 

After launching the Android Earthquake Alerts System in California in 2020, Google expanded the system worldwide in 2021. In regions where monitoring infrastructure is limited, this platform uses data from national seismological agencies along with crowdsourced Android smartphone networks to identify earthquakes and to deliver rapid alerts. 

It is estimated that hundreds of millions of earthquake warnings have been delivered worldwide by the Android Earthquake Alerts System, thus significantly expanding access to early warning technology to areas without dedicated seismic alert infrastructure. With limited earthquake early warning infrastructure in Venezuela, Google's crowdsourced smartphone network was instrumental in estimating the location and intensity of an earthquake by analysing motion data from thousands of Android devices before stronger shaking reached nearby areas. 

A new debate has arisen over the role of technology in disaster management following the Venezuela incident. In his opinion, Hrishit Panthry, the Co-Founder of Envirocare Foundation, stated that smartphones have become a powerful tool for delivering emergency alerts directly to citizens. With the growth of cities and the interconnection of infrastructure, early-warning systems are becoming increasingly important as cities continue to expand. It is also believed that lessons can be applied beyond earthquakes.

A similar real-time warning technology would improve community resilience by facilitating faster communication during other natural disasters, such as flooding, severe storms, and extreme heat. Additionally, the incident highlighted differences between how earthquake alerts are delivered via smartphone platforms. The built-in sensors on Android devices can detect seismic activity in conjunction with official monitoring systems, while other platforms in many regions rely primarily on government-run alert systems for emergency notification.

Experts believe that the wider adoption of integrated warning technologies could help to further strengthen public safety. During the recent Venezuelan earthquakes, governments, scientists and technology companies have demonstrated how they are increasingly utilizing connected devices and real-time data in order to strengthen emergency response efforts. 

Although early warning systems cannot prevent earthquakes, experts say even a few seconds prior notice can assist in saving lives. During the Venezuela earthquake, advances in smartphone-based early warning systems were demonstrated as a major factor in improving disaster preparedness. 

Even though no technology can predict an earthquake in advance, rapid detection and timely alerts can provide crucial seconds to help reduce injuries and improve emergency responses. As these systems continue to evolve, collaboration among technology companies, scientists, and governments will be crucial to expanding access to life-saving warnings worldwide.
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Technology
Aflac Japan KDDI Nidec Sapporo Holdings Technology

Hackers Target Industries in Japan, Attacks Share One Pattern


Four big Japan cyberattacks point to a common trend: threat actors are getting access via third-party infrastructure and subsidiaries, not from corporate headquarters. 

While the attacks impacted companies from varying industries such as telecommunications, manufacturing, insurance, and brewing, the breaches have one same characteristic.

Attacks share same patterns

Instead of directly disrupting corporate headquarters, hackers gained access via third-party infrastructure, subsidiaries, and overseas operations. 

The impacted organizations are Nidec, KDDI, Aflac Japan, and Sapporo Holdings. While the attacks involved different contexts, the incidents hint towards an increasing attack surface that expands well beyond a company’s primary network.

About KDDI incident 

KDDI, a telecommunications provider, reported illegal access to an email platform used by various Japanese internet service providers.

KDDI reported the incident surfaced from a bug in third-party software, revealing around 14.22 million email account records throughout six ISPs.

The attack shows how a single bug inside shared infrastructure can impact various organizations continuously.

Aflac Japan incident

On June 30, Aflac Japan revealed that between June 15 and June 25, hackers gained access to its Japanese operations. The company claims that some 4.38 million clients and agents were impacted, and a portion of the documents included bank account details used to pay insurance premiums.

According to the insurance, the incident only affected its company in Japan and had no bearing on its operations in the United States.

The alleged tactics are similar to social engineering strategies previously linked to Scattered Spider, even though the business has not linked the attack to any particular threat organization.

Sapporo Holdings and Nidec incident

Sapporo Holdings revealed possible illegal access involving two foreign subsidiaries, Canadian brewer Sleeman and Singapore-based Pokka. After identifying suspicious activity, the company shut down the impacted systems and started an investigation to find out if any data had been taken or accessed.

Nidec, a manufacturing company, has revealed that its Taiwanese subsidiary, Nidec Chaun Choung Technology, was the subject of a ransomware attack.

More than two gigabytes of firm data, including personnel, financial, procurement, manufacturing, legal, and IT information, were allegedly taken by the BlackField ransomware organization, which claimed responsibility for the attack. A $2 million ransom was allegedly demanded by the organization.

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Technology
AI wearables Apple Artificial Intelligence Meta new gen technologies Ray ban meta smartphones Technology

Why Apple, Meta and Snap Want You to Stop Looking at Your Phone

 



The technology industry's next computing platform may not fit in your hand. Instead, it could rest on your ears, sit on your face or hang around your neck.

Apple is reportedly exploring AirPods equipped with cameras that would give Siri the ability to interpret a user's surroundings, according to a Bloomberg report. The cameras are not expected to function like traditional smartphone cameras for photography or video recording. Instead, they would provide visual context that allows Apple's AI assistant to respond more intelligently to spoken requests. Apple has not commented on the report.

The development reveals a comprehensive industry effort to move everyday computing beyond smartphone screens. For decades, displays have served as the primary interface between people and their devices. Advances in artificial intelligence, computer vision and voice assistants are now encouraging technology companies to develop wearable devices that can understand a user's environment and respond without requiring constant screen interaction.

Snap recently expanded that vision with its latest augmented reality smart glasses, Specs, priced at £1,995 in the UK and $2,195 in the US. Unlike many existing smart glasses, the device is designed to operate independently rather than relying on a connected smartphone. Digital content appears only when needed, overlaying information onto the wearer's view of the real world instead of replacing it. Snap Chief Executive Evan Spiegel said the goal is to let users remain engaged with their surroundings while accessing digital experiences.

Meta is also increasing its investment in wearable AI. The company has reportedly sold around seven million pairs of its Ray-Ban Meta smart glasses and recently introduced more affordable models. Reports also indicate Meta is evaluating audio-only smart glasses that could reduce some of the privacy concerns associated with built-in cameras.

Those concerns remain one of the biggest obstacles to wider adoption. Camera-equipped wearables have faced criticism after users were found recording people without their knowledge, despite recording indicator lights intended to alert those nearby. Privacy advocates continue to question whether visible indicators alone provide sufficient transparency in public spaces.

Apple could attempt to distinguish itself by relying heavily on on-device processing, allowing visual information to be analyzed locally rather than stored or transmitted to cloud servers. Such capabilities could enable users to identify objects, receive navigation guidance, ask questions about nearby landmarks or generate recipe suggestions based on ingredients already in their kitchen through simple voice interactions.

Analysts believe AI-powered wearables could gradually shift some everyday computing tasks away from smartphones. Even so, most expect the smartphone to remain central to digital life for the foreseeable future, with wearable devices evolving as complementary tools rather than direct replacements. Whether they ultimately reduce screen time or simply expand the ways people interact with technology remains an open question.

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