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Ethical Hacking
AI cybersecurity AI Hacking AI Systems AI Tool AI-powered hacking Cyber Security ethical AI Ethical Hacking

AI Cybersecurity Tools Raise Questions About the Future of Ethical Hacking Competitions

 

Surprisingly, artificial intelligence is changing cybersecurity faster than expected. Some elite ethical hackers now wonder whether human-driven hacking contests will stay relevant much longer. Momentum built around this idea when someone prominent at Pwn2Own this year pointed to advanced AI systems possibly surpassing numerous expert analysts. Performance gaps might widen as these tools grow stronger. 

Among those who took part in Berlin’s yearly Pwn2own contest, Valentina Palmiotti stood out - not just by name but by result. Though many go by handles online, she competes under the tag “Chompie,” a nickname familiar across security circles. Success came her way more than others’, marking her top among solo entrants. Instead of waiting for flaws to be misused, the event encourages finding hidden bugs first. Rewards follow when researchers expose weaknesses in digital tools that were not yet public knowledge. 

This year’s competition handed out close to $1..3 million for spotting 47 previously unknown weaknesses in various software and systems. Because researchers shared the details with makers first, fixes arrived ahead of potential exploitation. Midway through the event, Chompie exposed weaknesses across several platforms - some tied to Nvidia - securing significant rewards. Her method? Endless stretches of probing flaws, something she laughed about calling "zombie hacker mode," where nights blurred into days thanks to sheer persistence and concentration. 

Though today's AI tools speed up code analysis and threat detection, Chompie sees a shift on the horizon. Her view: present systems boost efficiency, yet future versions may make several classic roles obsolete. What now requires teams might soon run on smarter algorithms alone. Nowhere has scrutiny been more intense than around Claude Mythos, a powerful AI said to detect vast quantities of software weaknesses. The creators state it has uncovered countless security issues spanning many applications. Because of risks tied to abuse, only certain government bodies and cyber defense groups are allowed to use it. Access remains tightly controlled amid ongoing debate. Some scientists see things differently. 

A top Pwn2-Owned champion, Orange Tsai of Taiwan, treats artificial intelligence as a helpful tool instead of a substitute for people's knowledge. Because it speeds up testing, new approaches get checked faster - this means more attacks can be studied quickly. Still, originality, gut instinct, and sideways leaps in logic stay within human reach only; these traits often spot flaws machines miss. Though tech advances, certain mental moves resist automation. 

Though artificial intelligence is advancing, hackers now employ automation more often to speed up tasks like scanning networks, crafting phishing messages, or building malicious software. Yet a large number of breaches continue depending on older methods - manipulating people or stealing login details - instead of exploiting cutting-edge flaws. 

Even with worries over automation, some specialists think artificial intelligence might boost digital defense by spotting flaws more quickly than hackers can act. Because systems evolve fast, teams protecting networks may rely on smart tools to stay ahead - provided those resources are used carefully and shared wisely.
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Vulnerability Management
AI-Assisted Exploitation Attack Surface Management CERT-In Blueprint cyber resilience Cyber Security Exposure Management Security Automation Threat Detection Vulnerability Management

The Growing Threat of AI-Driven Exploitation in Vulnerability Management


 

In vulnerability management programs, it has been assumed that defenders will have adequate time to evaluate newly disclosed flaws, prioritize remediation efforts, and deploy patches prior to large-scale exploitations occurring. This assumption is rapidly becoming obsolete. Artificial intelligence is increasingly being utilized by threat actors to compress every stage of the attack lifecycle from vulnerability discovery to proof-of-concept to automated weaponizing to mass exploitation.

Organizations are finding themselves caught between escalating pressures to patch faster and the operational realities of maintaining critical systems while exploitation timelines continue to shrink. 

A security team's challenge is no longer just identifying vulnerabilities, but managing risks in an environment in which attackers can quickly progress from disclosure to exploitation within hours, often faster than traditional remediation mechanisms can respond. The scope of this challenge is becoming increasingly difficult to ignore. 

Even though patch management remains a fundamental security control, the increasing volume of vulnerabilities being discovered is forcing IT organizations to acknowledge the limitations of relying solely on remediation speed to prevent security breaches. 

When Anthropic reported, in May 2026, that Project Glasswing, in collaboration with nearly 50 industry partners, utilized Claude Mythos Preview to uncover more than 10,000 critical- and high-severity vulnerabilities in widely used and systemically important software within a single month through its use of Claude Mythos Preview, a tool developed by Claude Mythos. 

Several internal research programs are confirming similar outcomes, demonstrating how artificial intelligence is allowing security flaws to be identified and validated at a much faster rate, despite the fact that this shift is not limited to defenders and software vendors. In addition to simplifying vulnerability analysis and rapidly reproducing revealed vulnerabilities, threat actors are able to reduce the time it takes to operational exploitation by utilizing the same AI-driven capabilities. Thus, security imbalances are no longer solely determined by patching delays, but rather by the unprecedented speed with which both legitimate researchers and adversaries can utilize newly discovered weaknesses to accomplish their objectives. 

The growing concern is also beginning to shape national cybersecurity strategy. CERT-In recently released its Blueprint on Reducing Exposure and Protecting Digital Infrastructure against Artificial Intelligence-Assisted Vulnerabilities Exploitation, which recognizes that Artificial Intelligence fundamentally alters the economics and speed of cyber operations.

Specifically, the guidance discusses how artificial intelligence is facilitating adversaries' identification and weaponization of vulnerabilities, exposed internet-facing services, insecure APIs, weak identity controls, misconfigurations, and software supply chain vulnerabilities in an increasingly interconnected enterprise environment by identifying and weaponizing vulnerabilities.

As AI-assisted attacks accelerate multiple stages of the cyber kill chain, including reconnaissance and exploitation, lateral movement, and data exfiltration, CERT-In indicates, traditional security models are becoming increasingly difficult to maintain in response. 

According to the framework, continuous exposure management, adaptive defense mechanisms, and resilience-driven cybersecurity operations should be replaced by periodic assessments and reactive remediation. This blueprint advocates the implementation of AI-enabled, intelligence-led security programs that are capable of continuously validating defenses across stakeholders, endpoints, networks, applications, cloud platforms, operational technology environments, and evolving AI systems. 

As part of the strategy, the company places significant emphasis on strengthening governance, ensuring executive accountability, providing proactive threat hunting, ensuring incident response readiness, and reducing exposure by enhancing attack surface management and continuing security validation. 

Additionally, CERT-In emphasizes the importance of securing software supply chains, cloud ecosystems, artificial intelligence models, and third-party dependencies as a result of ongoing assurance activities such as audits, adversarial testing, red teaming, and independent assessments.

Further, the guidance emphasizes that effective defense against AI-based exploitation will require more than just technical measures, but also coordinated threat intelligence sharing, collaborative response efforts, and sustained cooperation between organizations, cybersecurity communities, and national cyber authorities. There are, however, practical limitations in eliminating risk at the speed modern threats require that go beyond identifying risk. 

The exploitation timeline has steadily contracted for years, but artificial intelligence adoption is increasing this trend to the point where newly disclosed vulnerabilities can attract active exploitation attempts within hours of public disclosure due to its increasing adoption. As attackers increasingly utilize automated workflows and highly scalable workflows, remediation processes continue to be hampered by business continuity requirements, testing cycles, change management procedures, regulatory requirements, and the complexity of modern enterprise environments. 

Across the industry, this disparity has become increasingly pronounced. The Verizon Data Breach Investigations Report 2026 (DBIR) indicates that the median remediation time for critical vulnerabilities increased from 32 days to 43 days over the past three years, illustrating the growing gap between organization response capability and exploitation speed. 

With regulators such as CERT-In advocating more aggressive remediation timelines for critical vulnerabilities as well as sub-day patching expectations, security leaders are faced with balancing the need for urgency with the needs of operational stability. The emerging reality is that some vulnerabilities will inevitably be targeted prior to the completion of full remediation. 

The effectiveness of cyber defense cannot be solely assessed by the pace at which patches are deployed, but also by an organization's ability to limit exposure, contain exploitation opportunities, and maintain resilience during the period between vulnerability disclosures and remediation. As a result, automation is increasingly becoming regarded as a prerequisite rather than an enhancement to modern security operations against this backdrop. 

CERT-In focuses its efforts on continuous monitoring, verification, and adaptive defense, reflecting a broader industry recognition that manual security workflows cannot cope with the scale and velocity of AI-driven threats. Ruvala commented that traditional operating models based on human analysis and response are becoming increasingly unsustainable as security teams contend with an expanding attack surface, growing number of vulnerabilities, and a constant flow of alerts and telemetry generated across distributed environments. 

It is no longer feasible for security events to be manually investigated and prioritized under such circumstances. The use of artificial intelligence-enabled security platforms is therefore being increased for the purpose of accelerating threat detection, coordinating activities between disparate systems, automating investigative processes, and determining the priority of remediation efforts based on real-time risk exposure. 

In light of adversaries' use of artificial intelligence to accelerate reconnaissance, vulnerability identification, and active exploitation, these capabilities are becoming increasingly important. To achieve better response effectiveness at scale, Ruvala believes the industry is shifting toward platform-centric, increasingly autonomous Security Operations Center (SOC) models with artificial intelligence, automation, and unified visibility.

Unless these levels of operational augmentation are in place, most organizations will remain challenged to meet the rapid remediation and response timeframes now expected by regulators, business leaders, and threat realities alike. Increasingly, artificial intelligence is becoming increasingly influential when it comes to vulnerability discovery and exploitation, reshaping long-held assumptions about cyber security. 

As the gap between vulnerabilities being disclosed and actively exploited narrows, organizations are being forced to acknowledge that remediation alone is no longer sufficient to protect against malicious attacks. As threats evolve rapidly, the challenge is not simply responding faster, but developing security programs that continuously identify vulnerabilities, validate controls, prioritize risks, and adapt accordingly. 

As adversaries and defenders have increasingly powerful AI capabilities available, the ability of organizations to effectively combat the next generation of cyber threats will be determined by resilience, visibility, and operational agility.
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Windows driver
API BYOVD Attack Cyber Security Lenovo Windows driver

Signed Lenovo Driver Could Be Misused to Shut Down Security Software, Researcher Warns

 


A security researcher has uncovered a weakness in a Lenovo-signed Windows driver that could allow attackers to disable antivirus and endpoint security tools, potentially weakening a system's defenses before carrying out additional malicious activity.

The finding involves BootRepair.sys, a driver linked to Lenovo PC Manager. According to research conducted by security researcher Jehad Abudagga, the driver contains functionality that can be exploited to terminate processes directly from the Windows kernel. Because the file is legitimately signed by Lenovo, it may appear trustworthy to operating systems and security products that rely on digital signatures when evaluating software.

At the time of the analysis, the driver, identified by the SHA-256 hash 5ab36c116767eaae53a466fbc2dae7cfd608ed77721f65e83312037fbd57c946, reportedly had no detections on VirusTotal. Security researchers note that attackers often favor signed and seemingly legitimate software components because they can help malicious activity blend into normal system operations.

The research surfaces the growing nature of this particular attack technique known as Bring Your Own Vulnerable Driver, or BYOVD. In these attacks, threat actors deliberately use trusted but flawed drivers to gain elevated capabilities inside a system. Rather than exploiting security software directly, attackers abuse weaknesses in legitimate drivers to bypass protections and interfere with defensive tools.

A detailed examination of BootRepair.sys revealed several security weaknesses. The driver creates a device object called "\Device\::BootRepair" without applying a secure discretionary access control list (DACL). In practical terms, this means users with limited privileges may still be able to communicate with the driver.

The driver also creates a symbolic link named "\DosDevices\BootRepair," making the functionality accessible from user-mode applications. Researchers further found that the driver does not perform access-control validation when processing IRP_MJ_CREATE requests. As a result, any user can potentially obtain a handle to the driver without undergoing meaningful permission checks.

Analysis of the driver's input and output control functionality identified a single exposed IOCTL code, 0x222014. This control code accepts a four-byte input buffer that contains a process identifier, commonly referred to as a PID. Once received, the PID is passed to an internal routine responsible for terminating the specified process.

The underlying mechanism relies on the Windows kernel function ZwTerminateProcess. Because the operation is performed in kernel mode, the driver can terminate processes that would ordinarily be protected from interference. This includes security-sensitive services and endpoint protection products that are designed to prevent unauthorized shutdown attempts.

According to the research, these weaknesses create two primary attack opportunities. If the driver is already installed on a target system, an attacker with limited privileges could interact with it directly and terminate antivirus or endpoint detection and response (EDR) processes. If the driver is not present, an attacker could deploy the signed driver as part of a BYOVD operation, load it into the kernel, disable security controls, and then proceed with post-compromise activities.

In a proof-of-concept demonstration, the researcher showed that even protected processes could be terminated once the driver had been loaded. The test used standard Windows APIs to communicate with the driver. The process involved opening a handle to "\\.\BootRepair," sending a target process identifier through IOCTL code 0x222014, and allowing the driver to terminate the selected process from kernel mode.

The simplicity of the proof-of-concept demonstrates how little effort may be required to exploit the functionality once access to the driver is available. Researchers warn that after security products are disabled, attackers may be able to run credential theft tools, information stealers, or other post-exploitation utilities with a lower likelihood of detection.

The findings also reinforce concerns surrounding BYOVD attacks, which have become increasingly common in ransomware operations and advanced intrusion campaigns. Because vulnerable drivers often carry legitimate digital signatures, they can sometimes evade security controls that place significant trust in signed software.

To reduce exposure, organizations are encouraged to implement Microsoft's vulnerable driver blocklist, monitor systems for unusual driver-loading activity, restrict the installation of unauthorized drivers, and watch for suspicious kernel-level behavior. Security teams should also ensure that endpoint protection platforms are configured to detect attempts to abuse legitimate drivers.

The research serves as another example of how trusted software components can become security liabilities when design weaknesses are present. As attackers continue searching for legitimate tools that can be repurposed for malicious activity, organizations will need stronger controls around driver management, behavioral monitoring, and endpoint visibility to prevent security products from being disabled before an attack fully unfolds.

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Signal Jamming
Cyber Security Defence Secretary RAF Jet Russian Border Signal Jamming

RAF Jet Carrying UK Defence Secretary John Healey Has Signal Jammed Near Russia Border

 

An RAF jet carrying UK Defence Secretary John Healey experienced signal jamming near the Russian border earlier this week, highlighting the growing security risks faced by military and government flights operating close to tense front lines. The incident took place while Healey was returning to the UK after visiting British troops stationed in Estonia. According to the BBC report, the aircraft’s GPS was affected, forcing the crew to rely on an alternative navigation system for the three-hour journey. 

The reported disruption has raised fresh concerns about electronic interference in areas bordering Russia, where GPS jamming and related forms of signal disruption have become a familiar feature of the strategic environment. The BBC said it is suspected that Russia was behind the interference, although it remains unclear whether Healey himself was deliberately targeted. The flight path was reportedly visible on aircraft-tracking platforms, which may have made the plane easier to monitor. 

Signal jamming is not only a technical nuisance; it can also carry serious operational implications. When GPS is disabled or distorted, pilots must depend on backup systems and heightened crew awareness to maintain safe navigation. The BBC noted that a similar incident occurred in 2024, when an RAF aircraft carrying then-Defence Secretary Grant Shapps also faced GPS jamming near Russian airspace. That history suggests the latest case is part of a broader pattern rather than an isolated event. 

For the UK, the episode underlines the pressures of supporting allies in Eastern Europe while deterring hostile interference. Britain has maintained a military presence in Estonia as part of its NATO commitments, and visits by senior officials send a message of solidarity and readiness. Yet incidents like this show that even routine travel in the region can be affected by electronic warfare and other forms of disruption. The incident adds another layer of caution for defence planners and transport crews working in contested airspace. 

Although the full circumstances remain under review, the incident is a reminder that modern conflict is increasingly fought in invisible ways. Jamming signals, disrupting navigation, and probing aircraft movements are part of a wider contest that extends beyond traditional battlefields. As European tensions remain high, the UK and its allies are likely to keep paying close attention to the safety of flights operating near Russia’s borders.
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Google Research
AI Generated Content Law AI manufacturing research Cyber Security Fake Data generative AI fraud Google Research

AI-Generated Fake Citations Surge Across Scientific Papers and Peer-Reviewed Journals

 

Surprising numbers of made-up sources now show up in research articles, thanks to artificial intelligence. Instead of slowing down, the problem grew fast - around 150,000 false references slipped into academic work just in 2025 alone. While some stay hidden in early drafts online, others make it through review systems and land in official journals. What once seemed rare has become common, raising concerns across universities and publishing houses alike. 

From 2020 to 2025, scholarly articles totaling 2.5 million were examined by analysts at Cornell, UCLA, and Berkeley. These documents contributed a citation count of 111 million. Data originated in prominent archives - arXiv, bioRxiv, SSRN, and PubMed Central being among them. Attention shifted toward references that lacked confirmation in standard indexing systems. Tools like Semantic Scholar, OpenAlex, and Google Scholar failed to validate certain paper titles. Scrutiny centered on these unverifiable instances. Work unfolded without reliance on assumed accuracy. 

Instead, gaps in traceability became the point of departure. Midway through 2024, a noticeable spike emerged in made-up citations. This shift came alongside broader adoption of advanced language software - systems initially built for drafting text but now able to produce full reference lists. Although such tools speed up writing tasks, they sometimes invent scholarly sources that sound real yet lead nowhere. 

A paper called "LLM Hallucinations in the Wild" traced this pattern directly to how these models operate when asked to cite materials. Because false references mimic genuine ones so closely, spotting them becomes difficult without careful checking. Surprisingly, the investigation reveals fabricated citations appear beyond clearly dishonest work. These false references turn up across credible-looking documents, implying certain authors include AI-suggested sources without checking them first. What stands out is how casually unverified material slips into accepted formats. 

Most current safety measures faced questions about how well they work. The research showed that close to 78.8% of made-up citations got through arXiv’s review process without detection. Even after some bioRxiv papers appeared in journals listed by PubMed Central, around 85.3% still kept their false references unchanged. A study appearing in The Lancet highlighted recurring issues in biomedical literature. 

Over 4,000 false references turned up in nearly three thousand reviewed articles from 2023 through early 2026. Papers drawn from that span showed a sharp climb in made-up sources. While just one in 2,828 works contained such problems at the start, the proportion jumped - by early 2026, it was one out of every 277. Growth like this signals deeper cracks forming beneath the surface. 

One concern gaining traction: false references might cycle back into AI training data once they land in shared digital archives. Because these inaccuracies can persist, journals are being pushed toward using software checks on citations prior to accepting articles. 

As artificial intelligence plays a larger role in research tasks, closer scrutiny seems less like an option and more like a necessity. Some now see automated validation not as extra effort but as basic hygiene in scholarly communication.
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Holiday Shopping
Cyber Scams Cyber Security Cyberfrauds Digital payment system Digital Scams Digital Security Holiday Shopping

Online Shopping Red Flags That Could Signal Fraud and Financial Scams

 

Shopping online offers convenience and savings, but it also comes with risks. Fraudsters use fake deals, deceptive websites, and misleading advertisements to target consumers. Despite growing awareness, online shopping scams remain widespread. Recognizing warning signs early can help prevent the loss of money and personal information. 

A major red flag appears when a seller requests payment through gift cards, wire transfers, or money orders. Legitimate retailers typically offer secure payment options such as credit cards or trusted digital payment services. Scammers prefer irreversible payment methods because victims have little chance of recovering their funds. 

Text-message scams, known as smishing attacks, are becoming increasingly common. These messages often promote incredible discounts or claim there is an urgent issue with an account. Their goal is to direct users to malicious websites or trick them into revealing sensitive information. Because they frequently imitate trusted brands, careful attention is required to spot them. Fake retail websites are another common threat. 

These sites often copy legitimate logos, images, and designs to appear authentic. Checking the website address carefully can reveal suspicious characters, misspellings, or unusual formatting. Genuine retailers generally use straightforward domains that match their brand names. Unrealistic discounts are also a common warning sign. Offers advertising products at 90% off or more are often designed to lure shoppers into scams. 

Comparing prices across multiple retailers can help determine whether a deal is genuine or suspicious. Legitimate discounts rarely fall dramatically below market value. Phishing emails continue to target online shoppers. These messages may claim there is a problem with an order or offer a limited-time promotion. Clicking links can lead to malware infections or fake websites that steal personal data. Verifying the sender’s address and watching for spelling or grammar mistakes can help identify fraudulent emails. 

Shipping-related scams are also common. Fraudsters send messages pretending to be delivery companies, claiming a package is delayed or requires action. Instead of clicking links, consumers should visit the courier’s official website and check shipment details using legitimate tracking information. Fake coupon offers shared online present another risk. While retailers frequently promote discounts through official channels, scammers create counterfeit vouchers to attract victims. 

Confirming offers directly through a retailer’s website or customer support can help avoid malware and financial fraud. Even shopping on major online marketplaces is not completely risk-free. Third-party sellers sometimes offer counterfeit versions of popular products. Luxury goods, designer items, and branded electronics sold at unusually low prices should be approached cautiously. Deals that appear exceptionally cheap often involve counterfeit or low-quality merchandise. 

By paying attention to these warning signs and verifying offers before making purchases, shoppers can reduce their exposure to scams. A few extra checks can help protect personal information, prevent financial losses, and make online shopping a safer experience.
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quantum computing
AI AI in cybersecurity Blockchain Security Cyber Security post-quantum cryptography quantum computing

AI and Quantum Computing Convergence Raises New Security Concerns for Crypto and Digital Infrastructure

 

The long-standing debate within the cryptocurrency sector over whether quantum computing could threaten blockchain networks such as Bitcoin and Ethereum is taking on renewed urgency. Industry experts now believe that artificial intelligence (AI) may be speeding up the arrival of quantum breakthroughs, prompting concerns about the future of digital security.

Specialists working in blockchain protection and post-quantum cryptography say the intersection of AI and quantum computing is reshaping cybersecurity. AI is increasingly being used both by attackers seeking vulnerabilities and by developers strengthening defenses. At the same time, it is helping advance quantum computing research at a faster pace.

“The security landscape of the future is going to be different,” said Alex Pruden, CEO of Project Eleven, a company focused on quantum-resistant infrastructure for crypto.

“Between quantum and AI, we’re going to go into a world where security, and this is more broadly than just crypto, you simply cannot count on the way you’ve always done things,” Pruden said.

The growing concern follows warnings from technology companies and researchers suggesting that quantum computers capable of breaking current cryptographic systems could arrive sooner than expected. While experts continue to debate the exact timeline, many agree that AI could significantly accelerate progress in the field.

“AI is definitely being used to accelerate the development of quantum computing,” Pruden said. Researchers are already using machine learning systems to optimize quantum error correction, one of the field’s biggest engineering bottlenecks.

Illia Polosukhin, co-founder of NEAR Protocol and a former Google AI researcher, noted that AI has been enhancing scientific innovation for years.

“AI is becoming more and more of an accelerator,” Polosukhin said. “The rate of research is going to accelerate from here, and we have already seen progress that people didn’t expect would come this early.”

Reflecting on his experience at Google in 2016, Polosukhin explained that machine learning was already contributing to the discovery of new materials. “It might be that the next generation quantum computer will be built with AI and quantum computers of this generation,” he said. “It’s feeding into itself.”

Security experts are increasingly focused on a strategy known as “harvest now, decrypt later,” where sensitive encrypted information is collected today in anticipation of future quantum systems being able to decode it.

“If I know quantum computers are coming in a couple of years, I will start trying to capture all possible data that’s going around,” Polosukhin said.

“Everything we’re putting on the internet, if you’re identifiable as a person of interest, you can assume will be decrypted in two years,” he added. “It’s most likely happening already.”

For the cryptocurrency industry, the risks are particularly significant. Most blockchain networks rely on elliptic curve cryptography, a security standard widely used across the internet. A sufficiently advanced quantum computer could potentially derive private keys from public keys, exposing wallets and digital assets to theft.

However, experts argue that the real challenge lies not in quantum computing alone but in its combination with AI, creating an ongoing cybersecurity arms race.

Artificial intelligence is becoming increasingly capable of identifying coding weaknesses, software flaws, and security vulnerabilities. According to Pruden, these advances may increase the frequency and sophistication of cyberattacks.

“I would expect the advent of AI to accelerate… even more hacks,” Pruden said. “You have these AI models that are able to find either implementation bugs in the underlying cryptography or increasingly, I think, break the cryptography itself.”

At the same time, developers are leveraging AI to improve software security through code reviews, testing, and formal verification processes.

“AI can help with formal verification of post-quantum systems,” Pruden said. “That theoretically makes them more secure.”

Researchers believe this evolving environment means security can no longer be treated as a static framework that receives occasional updates. Instead, digital systems may require constant adaptation to stay resilient.

“Nothing is going to be as static as it’s been in the future,” Pruden said. “Either a quantum computer comes online to break some fundamental assumption, or AI gets smart enough to break that assumption too.”

This shift is already influencing blockchain ecosystems. Networks including Ethereum, Zcash, Solana, Ripple, and NEAR are exploring or implementing strategies designed to support post-quantum security.

NEAR recently revealed plans to integrate post-quantum cryptography into its account architecture, enabling users to switch cryptographic methods without moving assets to new wallets.

“Back in 2018, when we were designing [NEAR], we were like: ‘Hey, quantum will come, we should have an easy way to do it,’” Polosukhin said.

Despite growing momentum, the transition remains challenging. Current post-quantum cryptographic solutions often require more computational resources and larger data sizes than existing standards.

“The cryptography that’s currently standardized for post-quantum is very big and slow,” Polosukhin said.

According to researchers, the broader impact of AI and quantum computing is forcing a rethink of one of the digital era’s core assumptions—that encryption can remain secure for extended periods. As technology evolves, cybersecurity may increasingly depend on continuous upgrades and adaptive protection mechanisms rather than long-term static safeguards.

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U.S. Crypto
CFTC CLARITY Act Cyber Security U.S. Crypto

CLARITY Act Explained: How the 2025 U.S. Crypto Bill Ends a Decade of Regulatory Chaos

 

For over a decade, the U.S. cryptocurrency industry has faced crippling regulatory uncertainty, with the SEC and CFTC locked in a bureaucratic tug-of-war over jurisdiction. The CLARITY Act (Digital Asset Market Clarity Act of 2025) is Washington’s most serious attempt to resolve this conflict by writing clear regulatory rules into federal law. Passed by the House in July 2025 with strong bipartisan support, the bill recently cleared the Senate Banking Committee on May 14, 2026, marking a pivotal turning point for crypto regulation in America. 

The core purpose of the CLARITY Act is to divide crypto oversight between two agencies: the SEC regulates digital assets that behave like securities (investment contracts sold by centralized teams), while the CFTC gains exclusive authority over digital commodities like Bitcoin and Ethereum that operate on decentralized networks. The legislation creates three distinct categories: digital commodities (CFTC), investment contract assets (SEC), and permitted payment stablecoins (joint oversight). This framework ends the legal vapor that has forced companies like Coinbase and Binance to spend millions on litigation instead of building products. 

For crypto businesses and developers, the Act offers transformative benefits including easier compliance, reduced risk of surprise enforcement actions, and expanded innovation opportunities in payments and trading. Crucially, it provides safe harbors for DeFi developers who write open-source code without touching user funds, stopping smart contract publication from being treated as running an unlicensed money transmitter. Banks also gain a legal on-ramp for custody, settlement, and tokenized assets, transforming these from regulatory grenades into normal business lines. 

However, three major fights could still derail the legislation before it reaches President Trump’s desk. First, law enforcement groups argue the bill makes illicit finance through DeFi too easy, with Senator Warner negotiating stricter provisions. Second, Senate Democrats demand ethics language preventing officials (including President Trump, who holds significant crypto holdings) from profiting from industry regulation, which the White House opposes. Third, banks panic over stablecoin rewards, with the current compromise blocking direct yield but permitting activity-linked rewards to protect traditional banking deposits. 

If passed, the CLARITY Act would establish the first actual statutory framework for digital assets in the United States, written by Congress and binding on every regulator, exchange, developer, and investor. A merged Senate bill is plausible by late summer 2026, with final passage by year-end realistic if the three open conflicts resolve. For the first time since Satoshi’s Bitcoin whitepaper, crypto purgatory might finally be ending, bringing the U.S. in line with regulatory clarity already enjoyed in Singapore, Switzerland, and Dubai.
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Digital Token
cryptocurrency Cryptocurrency Cybersecurity Cyber Networks Cyber Security Cyber Vulnerabilities Digital Token

MAPO Token Crashes 96% After Cross-Chain Bridge Exploit Triggers Massive Unauthorized Mint

 

A major shock hit cryptocurrency markets when the MAPO token crashed nearly 96% after a vulnerability in the Butter Network cross-chain bridge was exploited. The attacker created an enormous number of unauthorized tokens, flooding the market with supply far beyond legitimate circulation. 

The sudden imbalance disrupted trading across Ethereum-linked decentralized finance platforms and triggered widespread panic selling. Blockchain security researchers found that the flaw allowed the creation of one quadrillion MAPO tokens, vastly exceeding the project’s intended supply. Investors reacted quickly, dumping holdings as confidence collapsed. 

Within hours, the token’s value fell from nearly $0.003 to around $0.0001, wiping out significant market value and damaging trust in the ecosystem. The attack centered on Butter Network bridge infrastructure. Investigators reported that a newly created external wallet was used to move roughly one billion MAPO tokens into decentralized exchanges. 

During the exploit, nearly 52 ETH, worth about $180,000 at the time, was drained from Uniswap liquidity pools. Analysts traced the activity back to the bridge vulnerability and the attacker’s newly established account. Although a large portion of the unauthorized tokens was sold, researchers noted that the attacker still controlled nearly a trillion MAPO tokens. 

Those remaining holdings continue to threaten liquidity pools and exchanges supporting the token. The incident once again highlights the security challenges facing cross-chain bridges, which remain attractive targets because of their complexity and large asset reserves. The exploit adds to a growing list of attacks affecting blockchain and decentralized finance projects.

Security experts have repeatedly warned that systems connecting multiple networks create additional risks. Vulnerabilities within cross-chain infrastructure can remain hidden until specific conditions trigger them, making these platforms particularly difficult to secure. Following the breach, Map Protocol confirmed that the issue originated within its Solidity-based smart contracts. 

The project temporarily paused mainnet operations and began migration efforts while the investigation continued. Butter Network also suspended ButterSwap services as a precaution, though officials stated that user funds were not directly compromised. The team later announced plans for a new contract deployment and a snapshot of token holdings to support recovery efforts. 

Any assets remaining in attacker-controlled wallets will be invalidated and excluded from future migration or conversion processes. Blockchain records showed that nearly one billion MAPO tokens were transferred to Uniswap shortly after the unauthorized minting occurred. Further analysis revealed that the attacker first submitted a legitimate oracle multisignature message before deploying a malicious smart contract at a carefully selected address. 

A manipulated retry message was then resent with the same transaction hash, making it appear authentic. Because the bridge incorrectly validated the altered message, it approved the creation of the massive token supply. Researchers emphasized that no private keys were stolen and no light-client systems were compromised. 
Instead, the breach resulted from a smart contract validation flaw involving dynamic fields in Solidity code. 
The incident demonstrates how weaknesses in contract logic can create severe consequences, putting liquidity ecosystems, blockchain projects, and investor funds at risk even without traditional network-level compromises.
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enterprise cybersecurity
Accenture AI technology AWS Cyber Advancements Cyber Protection Cyber Security enterprise cybersecurity

UK Post Office Awards £410 Million Contracts to Replace Horizon System After Long-Running Scandal

 

Now beginning its largest tech overhaul yet, the UK Post Office handed out £410 million in contracts to Accenture and OneView Commerce. This shift follows years of public scrutiny tied to the flawed Horizon system. Known for fueling a historic wave of wrongful convictions, that earlier platform is being phased out slowly. Instead of repeating past mistakes, officials are betting on updated tools built for accuracy. Behind the scenes, work has already started on untangling old code. What comes next will depend heavily on how well new systems adapt under real conditions.

Taking charge under fresh contracts, Accenture steps into managing and shifting the Post Office’s current tech setup. Worth £269 million across half a decade, the deal includes room to stretch further by another pair of years if needed. Out goes Fujitsu - the firm behind the original 1990s build of Horizon, the system handling sales and money tracking at counters. Instead comes a push led by Accenture: keeping daily operations steady while refreshing essential programs, guiding change toward modern cloud-based systems within an overall plan to renew outdated digital tools. 

Now beginning, OneView Commerce wins a distinct deal worth £141 million to build a fresh tech foundation for retail operations. This setup runs through the cloud, aiming to refresh daily functions inside Post Office locations. Electronic cash handling, portable access points, interactive client systems, data insights, along with stand-alone service stations form part of the rollout. Running within AWS or an equivalent online infrastructure ensures flexibility. Custom adjustments fit specific workflow demands across different sites. Years of dispute preceded the removal of Horizon.

Launched in 1999, it managed money tasks in Post Office locations nationwide. Faults within the program created incorrect account balances. These flawed reports triggered accusations against numerous branch managers - many charged with stealing, dishonest recordkeeping, or deceit. From 1999 until 2015, roughly 736 people faced unjust legal actions due to data flaws in the technology. Lives unraveled as a result: savings vanished, reputations damaged, mental health weakened. 

Still ongoing, a public investigation begun in 2021 examines how the scandal unfolded. By 2025, results showed top figures at the Post Office, together with staff from Fujitsu and earlier ICL, were aware - or ought to have been - of flaws in Horizon causing faulty financial records. Lives shattered under pressure; suicides occurred, tied directly to legal actions and what followed after. What emerged was not just system failure but personal tragedy etched into official findings. 

Come May 2025, the Post Office dropped its plan to build a new system on its own. Instead, it opened up bidding to outside firms. Winning proposals came from Accenture and OneView Commerce. Firms like IBM and Escher Software also submitted bids during the selection round. Now comes a shift - fresh agreements signal serious commitment, not just to upgrade tools but to restore confidence across the Post Office network.

Instead of clinging to outdated setups, leaders choose next-generation cloud solutions to replace the long-troubled Horizon infrastructure. This time around, progress means fewer breakdowns, smoother daily operations. Past mistakes weigh heavily; avoiding them shapes every decision going forward.
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zealot
Artificial Intelligence Authentication ChatGPT Cisco Security Cyber Security GitHub Phishing zealot

Researchers Show How ChatGPT Summaries Could Be Used for Phishing Attacks

 


Researchers have identified a technique that could allow malicious content embedded within a web page to appear inside ChatGPT responses, creating an opportunity for phishing, tracking, and social-engineering attacks through a platform users generally regard as trustworthy.

The attack method, named "ChatGPhish" by cybersecurity firm Permiso Security, focuses on how ChatGPT handles Markdown-formatted content when summarizing information from external websites. Markdown is a commonly used formatting language that allows web content to include elements such as hyperlinks and images.

According to Permiso Security researcher Andi Ahmeti, ChatGPT's web interface trusts Markdown links and image URLs originating from third-party pages that users ask the assistant to summarize. When a response is generated, the platform can automatically retrieve those images and present hyperlinks as active, clickable elements within the chatbot's interface.

In a scenario outlined by the researchers, an attacker could place a small hidden payload within a web page. If a user later asks ChatGPT to summarize that page, the embedded content may become part of the model's processing context. During response rendering, attacker-controlled images could be automatically requested, potentially exposing information such as the visitor's IP address, browser User-Agent string, and Referer data.

The researchers also found that links embedded in a manipulated page could appear as legitimate clickable items inside the AI-generated summary. Beyond directing users to phishing destinations, attackers could display fabricated security notifications, account-warning messages designed to imitate system alerts, or QR codes hosted on attacker-controlled infrastructure such as an Amazon S3 bucket. A victim scanning such a code with a mobile device could be redirected to a malicious destination, bypassing certain desktop-based URL filtering mechanisms and enterprise security controls.

The research adds to a growing body of evidence showing that AI-powered summarization tools can become unintended delivery channels for attacker instructions. Earlier this year, Permiso Security disclosed a separate attack involving Microsoft Copilot, where specially crafted instructions hidden inside an email influenced the output generated by the AI assistant. That technique was classified as a cross-prompt injection attack, also known as indirect prompt injection.

According to the researchers, the primary issue is not simply that prompt injection is possible. The more significant concern is how the manipulated content is ultimately presented to the user. A standard web page summarized by ChatGPT can cause phishing links, deceptive warnings, QR codes, and remotely hosted content to be displayed directly inside the assistant's interface, giving attacker-controlled material an appearance of legitimacy.

As AI assistants become common tools for workplace research, document review, and information gathering, this behavior introduces a new risk. Any web page processed by an employee could potentially contain hidden instructions or malicious content capable of influencing both the generated summary and the way that information is displayed.

Permiso Security noted that this shifts phishing activity beyond traditional delivery methods. Users no longer need to open a suspicious attachment or interact with an obviously fraudulent email. In some cases, simply asking an AI assistant to summarize a webpage may expose them to attacker-controlled content.

The disclosure arrives alongside research from Adversa AI detailing two attack techniques aimed at AI coding assistants and agentic development tools. The first, known as SymJack, allows a malicious code repository to achieve remote code execution through an AI-powered coding assistant.

According to Adversa AI researcher Rony Utevsky, the attack relies on convincing the AI assistant to perform what appears to be a harmless file-copy operation. The destination, however, is a symbolic link pointing to the assistant's own configuration file. As a result, attacker-controlled content is written into the configuration. When the assistant is restarted, a malicious Model Context Protocol (MCP) server is launched and executes arbitrary code using the victim's privileges.

The second technique, called TrustFall, uses a repository containing a malicious MCP server together with configuration settings that automatically approve its execution. A developer only needs to clone or open the repository in an AI coding environment and accept a folder-trust prompt. Once that action is taken, the attacker-controlled MCP server can start automatically without requiring additional tool approval, running with the same operating-system permissions as the developer.

Adversa AI explained that a victim who clones the repository, launches Claude, and accepts the generic trust prompt effectively allows the malicious MCP server to start as a native process on the machine. The payload executes immediately when the server starts, before additional prompts or tool requests occur.

The ChatGPhish findings emerge amid a steady stream of research examining weaknesses in modern AI systems, coding agents, and autonomous workflows.

Researchers recently described a jailbreak method called Involuntary In-Context Learning (IICL), which exploits the tension between a model's contextual learning behavior and its safety mechanisms to bypass protections in GPT-5.4.

Separate research from Cisco found that many AI security evaluations fail to reflect how real-world attackers operate. Rather than relying on a single prompt, attackers often use multiple interactions, gradually changing their wording, adopting different personas, and breaking objectives into smaller steps. Cisco argued that single-turn testing overlooks these techniques because real attacks frequently unfold across extended conversations.

Additional research has uncovered a vulnerability affecting Anthropic Claude Code in which a user-level configuration file, "~/.claude.json," can be altered through a rogue npm package. The attack enables modification of MCP endpoints and can place an attacker between Claude Code and an OAuth-protected MCP server, creating an opportunity to capture authentication tokens used to access downstream software-as-a-service platforms.

Researchers have also documented a technique involving OpenClaw skills that appear harmless during installation but later retrieve remote updates. In one scenario, attackers can influence an AI agent through workspace files after instructing users to append specific content to a file called HEARTBEAT.md during setup.

Another study demonstrated how hidden text embedded inside phishing emails can manipulate AI-based email security products. Attackers concealed text taken from legitimate newsletters and romance novels to make malicious messages appear benign to automated filtering systems.

LayerX researchers separately disclosed a flaw known as ClaudeBleed affecting Claude's Chrome extension. According to the company, any browser extension, including one without elevated permissions, could communicate with Claude's language model through the extension's content script because the code does not adequately verify the source of incoming instructions. This could allow another extension to issue commands and trigger actions through the AI assistant.

Cisco researchers also examined typographic prompt injection attacks against vision-language models. In these attacks, adversarial text is embedded inside images. The manipulated image may appear unreadable or resemble visual noise to humans and OCR-based filters while remaining interpretable to the target AI model.

Other recently disclosed vulnerabilities include flaws in Microsoft Semantic Kernel, tracked as CVE-2026-25592 and CVE-2026-26030, which researchers said could allow prompt-injection attacks to progress into host-level remote code execution.

Researchers additionally described the Neural Exec attack and abuse of the Unicode right-to-left-override function to bypass safety mechanisms protecting Apple's local AI models. The issue has since been addressed in iOS 26.4 and macOS 26.4.

A separate indirect prompt-injection vulnerability known as WebPromptTrap affected BrowserOS, an open-source agentic browser. The technique relied on hidden instructions embedded in an otherwise legitimate article to influence an AI-generated summary and persuade users to approve an authorization request. The issue was patched in BrowserOS version 0.32.0.

Research into the broader AI-agent ecosystem has uncovered persistent security weaknesses. An audit covering 3,984 skills published through ClawHub and skills.sh found that 534 skills, representing 13.4% of the total, contained at least one critical security issue. Researchers also identified 1,467 skills with broader weaknesses, including malware distribution risks, prompt-injection opportunities, exposed secrets, hard-coded API credentials, insecure handling of authentication data, and unsafe exposure to third-party content.

Additional studies identified attacks against NemoClaw, NVIDIA's reference framework for securing OpenClaw agents. Researchers demonstrated methods for extracting OpenClaw data through the platform's default sandbox configuration using either a malicious GitHub repository or a compromised npm package.

Security researchers are increasingly examining how advances in AI capability could affect offensive cyber operations. According to researchers at Palo Alto Networks Unit 42, more capable AI models could allow attackers to exploit both newly discovered and previously known vulnerabilities at a scale, speed, and level of automation that has traditionally required specialized expertise.

Last month, Unit 42 presented a proof-of-concept AI agent called Zealot that was capable of carrying out cloud attack operations with limited human involvement. The system chained together reconnaissance, exploitation, privilege escalation, and data-exfiltration activities by leveraging known weaknesses and misconfigurations.

Researchers argue that cloud environments are particularly susceptible to this type of automation because most administrative functions are accessible through APIs, multiple discovery mechanisms exist for identifying resources, configuration errors remain common, and access control often depends heavily on credentials.

According to Unit 42 researchers Yahav Festinger and Chen Doytshman, current large language models are already capable of coordinating reconnaissance, exploitation, privilege escalation, and data theft activities with relatively little human guidance. The techniques themselves are not necessarily new. What is changing is the speed and scale at which those established attack patterns can now be executed through AI-assisted automation.

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Phishing Attacks
Android Malware Android Security APK Fraud Cyber Security Cybercrime Karnataka Digital Fraud Fake APK Apps Mobile Banking Scam Phishing Attacks

Fake APK Apps Fuel 190% Rise in Digital Fraud Across Karnataka

 


Cybercrime is rapidly changing in Karnataka. Threat actors are increasingly shifting their focus from traditional phishing and investment scams to highly sophisticated APK-based attacks designed specifically for Android platforms. It has been reported by security experts and law enforcement agencies that the number of Android Package Kit (APK) fraud cases has increased by 190% during the first four months of 2026, demonstrating how malicious application files are used to intrude smartphones, gather sensitive credentials, and carry out unauthorized financial transactions using malicious applications. 

By April, there were 458 complaints filed, and it is anticipated that the number will surpass 1,300 before the year is up, according to investigators. The misuse of fake APK installers has emerged as an aggressive and technically dangerous form of mobile-enabled financial cybercrime currently affecting users across the state, particularly senior citizens and those without digital experience. 

Cybersecurity experts and investigators continue to find that seniors are disproportionately susceptible to APK-based attacks, primarily due to limited familiarity with Android security architecture and the increasing sophistication of social engineering techniques embedded within fraudulent messages. 

APK installers are increasingly being masked as urgent service notifications involving electricity bill disconnection, pending KYC verification, unclaimed credit card rewards points, courier updates, or even digital wedding invitations distributed through WhatsApp and Telegram platforms. When downloaded and manually installed outside of official app markets, these files can be silently gaining intrusive permissions on a device, allowing threat actors to monitor SMS-based OTPs, capture bank credentials, access contact lists, and manipulate financial applications remotely. 

Exclusive data obtained by DH indicates that Karnataka has experienced a steep 190.46% increase in APK fraud incidents, increasing from 325 reported cases in 2024 to 944 in 2025. 458 complaints have already been filed by April 2026 alone. Authorities estimate that by the end of the year, approximately 1,374 APK-related fraud complaints could occur in the state, based on its current monthly average of 114.5 cases.

The APK fraud campaign differs from the digital arrest scams or investment-linked pig butchering operations that rely heavily on prolonged psychological manipulation. As a result, law enforcement and cybercrime response teams face significant operational challenges resulting from low public awareness and weak digital vigilance. APK fraud campaigns are designed for rapid compromise through deceptive mobile payload delivery. 

Various authorities have urged citizens to avoid downloading APK files from unverified sources, restrict unnecessary application permissions, and report suspicious digital activities as soon as possible to the national cybercrime helpline 1930 or to designated cyber police units. 

It has been attributed that the rapid expansion of APK-enabled fraud networks is due to the widespread penetration of low-cost Android smartphones, the increased use of instant messaging platforms, and the existence of a persistent digital literacy gap among a wide range of user groups. There is an increasing sophistication of cybercriminal operations, with fraudulent APK payloads embedded within region-specific and multilingual communication used to imitate legitimate service providers, financial institutions, delivery platforms, and government verification systems, according to investigators. 

Users are advised to refrain from downloading applications that may have been transmitted via WhatsApp forwards, SMS hyperlinks, Telegram attachments, or unfamiliar third-party websites. Additionally, experts recommend enabling the "Install from Unknown Sources" setting on Android devices only when absolutely necessary for verified enterprise use. 

The security analysts recommend that electricity bills, courier delivery alerts, banking updates, and KYC requests be authenticated through official websites or authorized mobile applications, in recognition of the increasing use of clones and fabricated urgency by attackers to expedite victim responses.

Investigators of cybercrime have also advised against sharing one-time passwords, facilitating screen-sharing sessions, or granting access permissions to individuals who appear to be bank officials, police personnel, or government officials, since such access can facilitate remote surveillance, credential intercept, and unauthorized financial transactions. These campaigns identify seniors as one of the most at risk demographics, and encourage them to verify suspicious communications with trusted family members before engaging in links or application files. 

As a further warning, fraud syndicates are increasingly utilizing emotional manipulation, fear-based narratives, and professionally formatted communication templates for bypassing user suspicions and taking advantage of impulsive behavior. 

Considering the proliferation of APK fraud campaigns in social media ecosystems and regional languages, cybersecurity professionals believe technological safeguards alone are insufficient in the absence of parallel investments in community-driven awareness initiatives, multilingual cyber hygiene education, improved law enforcement coordination and stronger enforcement of mobile application security. 

It is evident that the escalating trend is indicative of how India’s increased adoption of digital technologies has simultaneously led to an increased attack surface for financially motivated cybercrime, according to experts. Through this transformation, cybersecurity is becoming a broader challenge of public awareness and social resilience that requires coordination between authorities, banks, and technology providers. 

As APK-based fraud escalates across Karnataka, it symbolizes a broader shift in the landscape of cyber threats in India, where mobile devices have evolved into both essential digital lifelines and high-value attack surfaces for financially motivated hackers. Social engineering tactics and malicious application delivery methods continue to be refined by cybercriminals. 

The most effective defences, experts believe, will require not only advanced cybersecurity infrastructure but also sustained public awareness, responsible digital behavior, and rapid incident reporting. Increasingly, mobile-first services are being utilized in an ecosystem in which sensitive financial and personal information can be compromised as soon as a single unverified download is completed. Therefore, authorities and cybersecurity professionals stress the importance of vigilance, verification, and informed digital practices as routine parts of everyday online activity rather than reactive measures in response to fraud.
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Login Credentials
AI in robotics AI password attacks Cyber Security Data protection data security Device Security Login Credentials

Yarbo Robotic Lawnmower Flaw Exposed Thousands of Devices With Shared Passwords

 

A single password opened thousands of Yarbo’s robot mowers worldwide, leaving owners in over thirty nations vulnerable without knowing it. While testing how these smart devices manage login requests, analyst Andreas Makris spotted the weak point - simple as typing “admin” into a forgotten backdoor. Some of these exposed devices operate using Linux platforms, linked straight to the web, depending on camera inputs, location signals, wireless links - also automatic map functions. 

Units across many regions used identical preset login details, investigators found. Remote entry into such hardware could happen without consent, Makris explained. Midway through the review, personal data came into view - email addresses, exact lawn mower locations, and network credentials laid bare. Testing revealed a real-time display pinpointing above 11,000 units active in at least thirty nations. 

While examining traffic patterns, digital trails linked each machine to specific geographic points. Visibility extended beyond basic details once hidden layers were uncovered. Not just limited to leaked information, the dangers included remote hijacking of lawn robots. Through experiments, scientists showed unauthorized users might trigger motion controls, switch on built-in imaging tools, while also probing residential networks for weak spots - all from a distance. 

Operating much like standard web-linked machines, these gadgets may end up pulled into coordinated hacking efforts. Such capabilities raise concern about their role in broader digital threats. A test shown to journalists supposedly let someone in Germany steer a 200-pound lawn mower near a home in New York, though they were separated by thousands of miles. Commands sent from afar took priority over hands-on operation, yet people close by received no warning when shifts occurred.  
Warnings emerged about gadgets placed close to critical infrastructure raising wider safety risks. Not far from power stations or manufacturing zones, fragile automated machines might operate, Makris noted - highlighting growing unease over threats to both physical setups and digital networks. Fixing the problem via firmware patches did not work - systems kept falling back to identical default passwords. 

Even after updates, the same login details resurfaced across devices. Experts pointed out that swapping passwords alone misses larger flaws: built-in factory access remains, while remote management tools stay vulnerable by design. Later, Yarbo admitted the issues once details emerged. Though based openly in New York, it holds ties to Hanyang Tech located in Shenzhen, China. Reports indicate the firm shut down some remote diagnostics pathways following scrutiny. 

Root passwords were reset shortly afterward. Access without authentication saw restrictions applied. Instead of using one password for every machine, new measures shifted toward unique credentials per device. Despite pledges of improved audit mechanisms and stricter controls on remote diagnostics, concerns lingered. Backdoor-style access by manufacturers allegedly persists in the equipment, skeptics noted - undermining claims of real change. Hidden backdoors and minimal built-in safeguards in smart gadgets are drawing sharper scrutiny, according to researchers. 

With households increasingly using AI-powered tools, robotic aids, or connected sensors, vulnerabilities multiply. Instead of isolated digital leaks, failures might now trigger real-world harm - door locks failing, cameras hijacked, entire home networks invaded. Security flaws once seen as minor glitches may now enable intrusions beyond data theft. 

When manufacturers skip strong defaults, everyday convenience turns into risk points across neighborhoods. Because these devices interact physically with environments, weaknesses aren’t just virtual - they can reach into living rooms, garages, even children's bedrooms. So while automation spreads rapidly, oversight lags behind, leaving gaps attackers can exploit.
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Vehicle Surveillance
Connected cars Cyber Security Data collection Smart Car Privacy Vehicle Surveillance

Your Car Is Spying on You—and It’s About to Get Worse

 

Cars used to be simple machines that carried people from one place to another. Today, they are rolling computers packed with sensors, microphones, cameras, GPS receivers, and internet connections. That shift has turned the modern vehicle into a powerful data collector, often recording far more than location or mileage. For many drivers, the unsettling part is not just that cars gather information, but that the process is now built into the way many features work. 

The data collected can be surprisingly intimate. Depending on the brand and model, cars may track where you go, how fast you drive, when you brake, what entertainment you use, and even physical or behavioral cues such as voice commands, seat settings, facial expressions, or body weight estimates. Some systems can also log passengers and nearby devices, creating a broad picture of who is in the car and how they behave. What makes this especially worrying is that drivers often do not see the full extent of what is being gathered. 

The bigger issue is what happens after the data is collected. Privacy policies can allow manufacturers, service providers, insurers, advertisers, and other third parties to access or share the information. In practice, opting out may be difficult or impossible because many connected features depend on data collection to function. That means consumers may face a trade-off between convenience and privacy, often without realizing how much personal information they are giving away. 

This is why the debate around connected cars is no longer just about safety or convenience. It is also about consent, transparency, and accountability. Drivers may assume their vehicle is a private space, but modern software can turn it into a monitoring platform. As automakers add more digital services, remote controls, and subscription features, the amount of data generated by each trip is likely to grow even further. 

The lesson is simple: buying a car now involves more than checking the engine, fuel economy, or price. It also means understanding the privacy cost of connected technology. Drivers should review data settings, read privacy terms carefully, and think about which features are worth the information they reveal. In the era of smart vehicles, the road ahead is not only about mobility; it is also about who gets to see your life along the way.
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Cyber Security
Ad Data Privacy AI Chatbot AI Privacy AI Security chatbot security Cyber Privacy Cyber Security

WhatsApp Incognito AI Chats Raise Privacy and Accountability Concerns

 

Private AI chats are now arriving on WhatsApp through a new incognito mode where conversations disappear once they end. Neither users nor Meta will retain copies of these exchanges, according to the company. Executives say the feature was designed for sensitive discussions involving health, finances, relationships, or personal struggles, where users may not want permanent records stored online. 

Unlike most AI systems that retain chat history for moderation, improvements, or future model training, Meta claims these AI conversations will not be saved on company servers at all. CEO Mark Zuckerberg described it as one of the first major AI systems built without maintaining conversation logs. According to Will Cathcart, many users feel uncomfortable sharing private information when companies can later review chat histories. 

To address this, the new setting automatically erases AI discussions after completion, leaving no retrievable record behind. Although WhatsApp says the feature provides protections similar to end-to-end encryption, the company acknowledged the underlying technology differs from the encryption used for regular WhatsApp messages. Meta nevertheless maintains that users should expect comparable privacy safeguards while interacting with AI tools. 

Despite the stronger privacy focus, cybersecurity experts warn the system could create accountability challenges. Alan Woodward from the University of Surrey noted that while the feature is unlikely to weaken WhatsApp’s broader security infrastructure, disappearing AI chats could make it difficult to investigate harmful responses or dangerous recommendations generated by the chatbot. Companies including OpenAI and Google have already faced legal scrutiny tied to allegations that AI conversations contributed to emotional harm, unsafe behavior, or psychological distress. 

If AI chats vanish permanently, neither users nor Meta may be able to review what was said during critical interactions. Experts also warn that disappearing chat histories may reduce transparency around misinformation, moderation failures, or unsafe advice shared privately by AI systems. Without stored records, proving what responses were generated during sensitive moments becomes far more difficult. Meta says additional safety protections are still being developed. 

Initially, the incognito mode will support only text conversations rather than image processing, while stricter moderation guardrails are expected to block prompts considered harmful, illegal, or dangerous. The feature also reflects Meta’s broader push to integrate AI across Instagram, Facebook, and Messenger. Despite criticism from some users after Meta AI was added to WhatsApp without a full removal option, the company continues aggressively expanding its AI ecosystem. 

Industry analysts say Meta’s growing investment in AI infrastructure is tied to intense competition across the technology sector. The company is expected to spend heavily on artificial intelligence throughout 2026 to improve advertising systems, shopping features, and user engagement tools. Investors, however, remain cautious about whether those enormous investments will ultimately generate long-term returns. 

WhatsApp’s disappearing AI conversations highlight an increasingly important debate surrounding privacy and accountability. While users may value confidential AI interactions, experts warn that removing all conversation records could also make it harder to investigate misuse, harmful outcomes, or dangerous AI behavior later on.
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User Privacy
Cyber Security Meta Meta Glass Smart Glasses User Privacy

Meta Smart Glasses Secretly Film Women: Privacy Invasion Crisis Explained

 

Smart glasses are moving from novelty to mainstream, and Meta’s Ray-Ban model is leading the market. The BBC says Meta accounts for about 80% of sales in the smart-glasses category, helped by the familiar Ray-Ban design and the addition of a built-in camera, speakers, and AI features. That combination has made the product appealing to early adopters who want hands-free music, calls, photos, and information on the go. 

But the same features that make smart glasses attractive also make them controversial. The report describes women being filmed without their knowledge by men wearing the glasses, often in everyday settings such as beaches, shops, and sidewalks. Those videos can later appear online and attract harassment, while the people recorded may not even realize it happened until much later. 

Privacy concerns are not limited to casual misuse. The report says some wearers have been surprised to discover what their glasses were recording, while lawsuits have also been filed over videos captured through the devices and used for AI training. In addition, experts quoted in the report warn that if smart glasses become common, it may become much harder to enforce norms around sensitive places like courthouses, hospitals, museums, and bathrooms. 

Meta says the glasses are designed with privacy in mind and that users should behave responsibly. The company’s spokesperson told the BBC that it has teams focused on limiting misuse, but also argued that the ultimate responsibility lies with individual users. Even so, the report notes that visible indicators like the recording light may be too subtle to reliably alert bystanders, especially in bright outdoor conditions.

Despite the backlash, the commercial momentum is strong, and other major tech firms are preparing their own versions. Apple, Snap, and Google are all reportedly working on smart-glasses products, suggesting this could become a major new consumer category rather than a passing trend. The BBC’s reporting points to a familiar tech dilemma: a device can be genuinely useful while still raising difficult questions about consent, surveillance, and the limits of public privacy.
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