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Ransomware
AI AI Hacking Cyber Crime Cyber Threats Ransomware

AI Is Fueling a New Wave of Cybercrime

 

Cybercriminals are increasingly turning to artificial intelligence, and the biggest barriers that once slowed adoption are rapidly disappearing. According to a recent Axios report, restricted access to models, high costs, and limited incentive to change old hacking methods are no longer holding attackers back. Open-weight AI models are becoming powerful enough to rival mainstream systems in some cyber tasks, while underground marketplaces are offering jailbroken tools, custom-built models, and AI-powered hacking services. That mix is making AI more practical for criminal use than ever before. 

The shift matters because hackers are no longer just experimenting with AI in isolated tests. They are now weaving it into existing workflows to speed up ransomware, fraud, phishing, and cloud intrusions. Axios cites recent cases showing how attackers are using AI to generate exploit code, steal data, and even negotiate with victims. In one example, a lone hacker used AI agents to automate most of a ransomware attack. In another, AI helped compress a cloud attack that would normally take weeks into just 72 hours. 

Researchers also say the threat is spreading across different types of crime. A separate case described by Axios involved a bank fraud scheme targeting Mexico-based financial organizations, where AI-generated malware played a role in the attack chain. These incidents suggest criminals are learning how to blend AI with traditional tactics instead of replacing human hackers entirely. That makes the attacks harder to predict, because AI is being used as an accelerator rather than a standalone weapon. 

For defenders, the most serious problem is time. AI is helping attackers move faster, which leaves organizations with fewer hours to detect suspicious behavior, investigate compromises, and patch weak spots before damage spreads. Security teams that once had days or weeks to respond may now have only a narrow window. That raises the pressure on companies to monitor systems more closely, strengthen access controls, and prepare for attacks that are increasingly automated and adaptive.

The broader message is clear: AI is lowering the cost and complexity of cybercrime while increasing the scale and speed of attacks. What once required a skilled team and long preparation can now be compressed into a shorter, more efficient operation. As criminal adoption grows, the cybersecurity industry will need to match that pace with faster detection, stronger resilience, and better incident response.
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Cyber Crime
AI Boko Haram Cambridge Study Chatbot Cyber Crime

Boko Haram Used AI Chatbots to Support Attacks, Cambridge Study Finds

 

Boko Haram has reportedly exploited mainstream AI chatbots to support terror operations, according to a Cambridge University study cited by the South China Morning Post. The research suggests the group used both US and Chinese AI tools for bomb-making, attack planning, propaganda, and day-to-day operational support. 

The study is based on interviews with 27 former Boko Haram members in northeast Nigeria, giving researchers a rare inside look at how the insurgent group adapted to new technology. Former fighters said AI tools were used to answer practical questions about weapons, tactics, surveillance, and movement, showing that the technology was not used only for messaging or recruitment. 

One of the most concerning findings is that Boko Haram reportedly organized internal AI training and created specialized units to help members use chatbot systems more effectively. The report says outside trainers, likely linked to the Islamic State network, helped members learn how to use AI tools with VPNs and encryption software, while also teaching ways to bypass built-in safety restrictions. 

Researchers said the group used AI for operational tasks such as bomb construction, improving attacks, and troubleshooting weapons. Former commanders described using chatbots to solve battlefield problems, including how to modify motorcycles for raids and how to increase the destructive power of improvised explosives. This suggests that extremist groups are no longer treating AI as a novelty, but as a repeatable support system for violence. 

The findings raise a broader security concern for governments and AI companies. If militant groups can regularly extract harmful guidance from consumer chatbots, then safety filters alone may not be enough to stop misuse. The study also strengthens calls for tighter international coordination, especially between the US and China, because the major AI systems being exploited are built in those two countries. As AI becomes more advanced and more accessible, the risk is not just misinformation or fraud, but the possibility that extremist groups will use it to become faster, better organized, and harder to stop.
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technology
AI Anthropic Banks Canada Claude Mythos Financial Institutions technology

Claude Mythos Just Caught the Attention of Canada's Banking Regulator

 



Canada's federal banking regulator has privately warned financial institutions that advances in frontier artificial intelligence are shrinking the time available to detect and contain software vulnerabilities, according to an internal email that specifically identified Anthropic's Claude Mythos, an uncommon move for a regulator that typically avoids naming individual technologies.

The email, sent on April 29 by the Office of the Superintendent of Financial Institutions (OSFI), was addressed to chief technology officers, chief information security officers and chief risk officers at federally regulated banks and insurance companies. Obtained by Reuters through Canada's Access to Information Act, the communication described advanced AI models such as Anthropic's Claude Mythos as accelerating the pace at which cyber risks can emerge, prompting institutions to strengthen the speed of risk identification, mitigation and incident response.

Unlike most regulatory guidance, which generally refers to broad categories such as generative AI or emerging technologies, the OSFI email explicitly referenced Claude Mythos by name. Financial regulators typically adopt technology-neutral language to ensure guidance remains applicable as technologies evolve, making the direct reference to a specific frontier AI model particularly notable.

According to the released correspondence, OSFI warned that advanced AI systems are compressing the timeframe available for organizations to respond to newly identified vulnerabilities before they can be exploited. The regulator indicated that the bulletin accompanying the email outlined sound practices that federally regulated financial institutions could adopt to improve the speed and effectiveness of identifying, mitigating and responding to cyber risks.

However, portions of the document released under Canada's Access to Information Act were redacted, leaving many of the regulator's recommended practices undisclosed. While the details of the guidance remain partially withheld, the available sections reveal OSFI's assessment that rapidly advancing AI capabilities are challenging long-standing assumptions underpinning vulnerability management.

For decades, many cybersecurity programs have operated on the expectation that defenders would have days or even weeks to evaluate newly disclosed vulnerabilities, test patches and deploy mitigations before attackers developed reliable exploits. Frontier AI models capable of rapidly analyzing software code and identifying exploitable weaknesses could substantially reduce that window, increasing pressure on organizations to accelerate patch management and defensive operations.

The concern is particularly relevant for financial institutions, many of which continue to operate complex legacy infrastructure supporting critical banking services. Core banking platforms often consist of decades-old software integrated with newer digital systems, making security updates and vulnerability remediation significantly more complex than in less regulated technology environments. A shorter interval between vulnerability discovery and exploitation therefore presents operational challenges for institutions responsible for maintaining highly available financial services.

Claude Mythos has drawn attention within the cybersecurity community for its reported ability to assist with sophisticated vulnerability research and exploit development in controlled environments. Anthropic introduced the model through Project Glasswing, a restricted-access initiative designed to provide selected organizations with advanced cybersecurity capabilities for defensive research rather than broad public deployment. Access to the model remains limited and subject to eligibility requirements established by Anthropic.

The timing of OSFI's communication coincided with a series of regulatory discussions surrounding frontier AI models. Earlier in April, senior executives from Canadian banks reportedly met with regulators to discuss the implications of Claude Mythos. Around the same period, U.S. Treasury Secretary Scott Bessent and then-Federal Reserve Chair Jerome Powell also convened bank chief executives to examine the potential cybersecurity implications associated with increasingly capable AI systems.

International regulators have since demonstrated similar interest. Authorities at the European Central Bank and the Bank of England have reportedly discussed the implications of frontier AI for financial sector resilience, while Australia's corporate regulator, the Australian Securities and Investments Commission (ASIC), has confirmed that it is monitoring developments related to the technology.

Following questions from Reuters regarding the internal email, OSFI subsequently published a public bulletin addressing the governance of generative and agentic artificial intelligence. The regulator reiterated that its supervisory approach focuses on how federally regulated financial institutions identify, govern and manage risks arising from AI adoption rather than regulating individual AI models themselves.

"Our focus is not the technology itself, but how federally regulated financial institutions govern and manage the risks associated with its use," OSFI said in its public statement.

Nevertheless, the regulator's internal correspondence referred to Anthropic's Claude Mythos by name on multiple occasions, distinguishing it from the more general language typically used in regulatory communications concerning emerging technologies.

OSFI oversees Canada's federally regulated banks, insurance companies and pension plans, with responsibilities that include monitoring financial stability risks arising from cybersecurity, foreign interference, geopolitical developments and technological change. The emergence of highly capable AI models has increasingly placed these categories of risk in closer alignment as governments evaluate both the opportunities and security implications associated with frontier AI.

While the Canadian government has confirmed that it has access to Claude Mythos, it remains unclear whether any of Canada's major financial institutions currently participate in Anthropic's controlled-access Project Glasswing program. Several banks declined to comment publicly on whether they have access to the model, referring questions instead to the Canadian Bankers Association.

In response, the Canadian Bankers Association said member institutions have invested substantially in protecting Canada's financial system and continue to comply with OSFI's cybersecurity risk management and incident reporting requirements, without addressing whether banks currently have access to the frontier AI model.

At the same time, Canada's largest banks continue expanding their AI strategies across customer services, internal operations and software development. Royal Bank of Canada, TD Bank and Bank of Montreal have outlined initiatives aimed at integrating AI into business operations while reducing reliance on external technology vendors. Scotiabank, CIBC and National Bank have also disclosed AI-related programs intended to improve operational efficiency and customer services.

Bruce Ross, Royal Bank of Canada's Group Head of Artificial Intelligence, said in June that models such as Claude Mythos are changing the cyber threat environment by enabling exploit code to emerge much sooner after vulnerabilities are discovered. He said the bank's response has focused on strengthening AI-powered defensive capabilities to counter increasingly sophisticated attacks.

Anthropic has also expanded Project Glasswing in recent months, reporting that participating organizations have collectively identified more than 10,000 high- and critical-severity software vulnerabilities using the platform's advanced cybersecurity capabilities. The company has positioned the initiative as a defensive research program intended to improve software security while maintaining controlled access to highly capable AI systems.


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Ransomware
AI Cyber Attacks Cyber Extortion LLMs LockBit qilin RaaS Ransomware

Ransomware activity climbs in Q2 2026 as leading gangs consolidate attacks and AI streamlines extortion efforts

 


Ransomware groups claimed responsibility for 2,279 attacks worldwide during the second quarter of 2026, marking a 7% increase from the previous quarter and a 43% jump compared with the same period last year, according to GuidePoint Security's latest quarterly ransomware report. Researchers also recorded the highest number of active ransomware groups seen in a single quarter, reflecting an ecosystem that continues to attract new threat actors even as attacks remain concentrated among a relatively small number of established operations.

Despite the growing number of ransomware groups, a handful of operators continue to dominate victim claims. GuidePoint found that the five most active groups were collectively responsible for more than 40% of all publicly reported ransomware incidents during the quarter, suggesting that while new groups continue to emerge, only a few have achieved sustained operational scale.

Qilin remained the most active ransomware operation during Q2, accounting for approximately 13% of all recorded victim claims. It was closely followed by The Gentlemen, a comparatively new group that has expanded rapidly in recent months. Together with Akira and DragonForce, the two groups make up what GuidePoint describes as a "four-headed monster," representing the most prolific ransomware operations currently shaping the threat landscape.

Rather than relying on a single dominant ransomware syndicate, today's ransomware ecosystem is distributed across several highly active groups capable of absorbing affiliates from disrupted operations. Researchers noted that this structure could reduce the long-term impact of law enforcement takedowns, as affiliates displaced from one ransomware-as-a-service (RaaS) platform may quickly transition to another established operation without substantially disrupting attack activity.

The United States remained the country most frequently targeted by ransomware groups during the quarter, accounting for 40% of publicly claimed victims. Germany ranked second with 32%. However, GuidePoint observed a noticeable shift in targeting patterns, with the U.S. accounting for a smaller proportion of victims than in previous quarters, when roughly half of all reported incidents involved American organizations.

Researchers linked this broader geographic distribution to increased activity from groups including Qilin, The Gentlemen and LockBit, each of which claimed a larger share of victims outside the United States during Q2. The findings suggest that ransomware affiliates are expanding their operations across a wider range of regions instead of concentrating primarily on U.S.-based organizations.

Alongside changes in victim targeting, the report examined how artificial intelligence is being incorporated into ransomware operations. While concerns have grown around the possibility of AI creating entirely new forms of cyberattacks, GuidePoint found little evidence to support that scenario. Instead, threat actors are primarily using large language models (LLMs) to accelerate tasks that previously required significant manual effort, allowing them to improve efficiency without fundamentally changing their attack methods.

One case study highlighted in the report involved the data extortion group FulcrumSec. After obtaining a large volume of stolen information, the group reportedly used an LLM to examine complex databases and identify individuals appearing across multiple datasets. According to researchers, completing this level of analysis manually would have required either extensive knowledge of the victim's database architecture or a substantial investment of time by human operators.

The information extracted from the stolen data was then paired with AI-generated negotiation messages written in English. By demonstrating a detailed understanding of the compromised information, FulcrumSec strengthened its position during ransom negotiations, providing victims with evidence of the data in its possession while using those findings to justify its ransom demands.

GuidePoint also documented DragonForce's use of large language models during extortion negotiations. Researchers said the group generated convincing messages that sought to increase pressure on victims, including claims that it had legal counsel available to advise its operations. Although the report describes that assertion as almost certainly false, it illustrates how AI can help cybercriminals produce persuasive communications intended to exploit concerns around regulatory obligations, legal consequences and reputational damage.

According to the researchers, the effectiveness of these messages does not necessarily depend on their accuracy. Instead, their value lies in presenting information in a manner that appears credible enough to influence decision-making during negotiations. Large language models, which are capable of generating fluent and convincing text within seconds, are increasingly being used to support these psychological tactics.

Taken together, the findings indicate that AI is currently serving as an operational force multiplier rather than introducing an entirely new category of ransomware attacks. Tasks such as analyzing stolen data, organizing information, preparing victim communications and drafting negotiation messages can now be completed more quickly, enabling threat actors to devote more time to other stages of their operations.

At the same time, the continued concentration of attacks among a small group of highly active ransomware operations suggests that scale, organization and affiliate networks remain key drivers of today's ransomware economy. While new groups continue to enter the ecosystem, a limited number of established operators continue to account for a disproportionate share of publicly claimed attacks, reinforcing their influence across the global ransomware ecosystem.

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Ransomware
AI Autonomous Agents Cyber Security Langflow Bug Ransomware

AI Agent Runs First End-to-End Ransomware Attack

 

Security researchers have long warned that AI would lower the barrier to cybercrime, but the latest case makes that threat tangible. In the operation described by Sysdig and covered by Forbes, an autonomous agent carried out the technical steps of a ransomware attack from initial access to encryption and ransom-note generation. The group’s analysis suggests the attack was not a simple script; it adapted when it hit obstacles, corrected its own mistakes, and kept moving without a human at the keyboard. 

The campaign reportedly began with an exposed Langflow incident, which the attacker used to gain access through a known vulnerability. From there, the agent searched for secrets, including credentials and cloud keys, then expanded into a production environment and escalated privileges. Researchers said it encrypted more than 1,300 configuration records and generated its own ransom note with a Bitcoin address, showing how an AI system can combine reconnaissance, exploitation, and extortion in one chain. 

What makes the story unsettling is not only the automation, but the speed. One reported login failure was fixed in 31 seconds, a reminder that AI can iterate much faster than a human operator can type, think, or troubleshoot. That kind of responsiveness matters because ransomware succeeds by compressing the defender’s reaction time. If attackers can use agents to scan, pivot, and encrypt at machine speed, security teams will need similarly automated detection, containment, and recovery tools to keep up. 

Still, the incident also shows that “fully autonomous” cybercrime may be more complicated than the headline suggests. Later reporting said humans may have still chosen the target, prepared infrastructure, or supplied stolen credentials, even if the AI handled the intrusion itself. That distinction matters, because it means defenders are not just facing smarter malware, but a new hybrid model in which human planning and AI execution reinforce each other. The lesson for businesses is clear: reduce exposed services, enforce strong credential hygiene, segment critical systems, and assume that the next serious attack may be built and operated with far less human effort than before.
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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 ai agents ChatGPT Claude Google Microsoft Technology

GhostApproval Symlink Codes Could Run Malicious Codes in AI Coding Agents


Cyber security experts at Wiz discovered that a bug in six famous AI coding assistants allows a booby-trapped code project to silently take over a developer’s system. The assistant can ask access to edit one innocent-looking file, but the write takes over a sensitive file.

The impacted tools are Windsurf, Google Antigravity, Cursor, Amazon Q Developer, Claude Code by Anthropic, and Augment. Wiz has termed the technique GhostApproval and posted it recently.

Three of the six AI assistants have addressed, two did not, while Anthropic argues if it is a bug. The most vulnerable are the tools that modify file before you can notice.

Attack tactic

The threat actors exploit an old Unix feature called symlink (or symbolic link), that AI assistants cannot check. 

A symlink silently directs to other files somewhere else on disk, hence writing to it particularly writes to the victim. 

“Symbolic links have been a security headache since the early days of Unix. From /tmp race conditions to privilege escalation exploits, symlinks have a long history of bypassing security boundaries by making one path silently resolve to another. It's a well-documented attack primitive - CWE-61 dates back decades,” Wiz said.

Research model

Wiz made a malicious repository with a symbolic link called project_settings.json that really directs to target’s SSH login file, ~/.ssh/authorized_keys. The repo’s README commands the assistant to put “a line” to project_settings.json, and this line is the hacker’s SSH key mimicking an innocent setting. “

If you ask the agent to “set up the workspace” or “follow the README,” it writes the key directly via the symlink into the login file. Following this, if the machine plays an SSH  service the threat actor can access, they can sign in without password. 

The second variant

Another variant of the attack writes to your shell startup file, ~/.zshrc, which the shell runs the next moment you open a terminal without needing an SSH. There are no indications that any of this has been abused in real-time operations, Wiz has only demonstrated it as their research.

“Symlinks have been exploited for decades – in race conditions (CVE-2018-15664), in package managers (CVE-2021-32803), in container escapes (CVE-2024-21626). Any time a tool writes to a user-controlled path without resolving it first, symlinks become a weapon,” Wiz wrote in its blog. 

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Google
AI Chatbots Cyber Attacks Dialogflow Google

Rogue Agent Bug Could Have Let Attackers Hack AI Conversations


A critical vulnerability in Google’s Dialogflow could have let a hacker exploit other Code-Block-enabled agents via one Code Block-power agent, in one Google Cloud project.

After this, the attacker could read chats, steal user data, and command bots to send hacker-written texts such as re-entering a password.

Discovery of the bug

Cyber security firm Varonis discovered the tactic and called it ‘Rogue Agent.’ The bug impacted only businesses that make agents with custom Code Blocks and Dialogflow’s Playbooks, which allows hackers to add their own Python. The attack was not remote, or unauthorized.

For the attack to happen, it required the dialogflow.playbooks.update green light one such agent, which restricts the hacker to an infected insider or a breached developer account, not some stranger on the web. From that point, the reach extended to every agent inside the project.

Google has patched the bug, and Varonis and Google have said there are no signs that the flaw was deployed in a real attack or campaign.

Single writable file prompted each agent Code Blocks

Dialogflow’s Code Blocks allows developers to add custom Python to a chatbot’s flow to test input, invoke defined tools, and control behavior. 

The code runs within a Google-operated Cloud Run environment, and every agent that uses Code Blocks in the similar Google Cloud project shares one incident of it. The customer cannot control or see the environment that Google runs, meanwhile Varonis discovered no real separation between the agents within it.

Attack tactic

When the agent runs a Code Block, the code is added to internal setup code and sent to Python’s exec()function. The functions and variables that block can touch are defined by the setup. 

Functions consist(), which makes the bot reply with a given string, whereas variables consist of a history of full chats and state for session information such as the session ID.

Varonis discovered code_execution_env.py, the file that does this wrapping, lying in the shared environment with write access. 

As the file was writable, a single Code Block could change it. The block downloads an altered code_execution_env.py from a threat actor-controlled server and overwrites the original within the running container.

After that, the attacker’s variant commands every Code Block deployment throughout every agent that shares the environment. The attacker’s code sits in the same place as the real code, with similar access to respond(), state, and history, 

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technology
AI AI Platform ChatGPT China Cloud based services GLM-5.2 technology

Chinese AI Model GLM 5.2 Pushes Open-Weight AI Forward

 




Chinese artificial intelligence company Z.ai, formerly known as Zhipu AI, has introduced GLM 5.2, an open-weight large language model that is attracting attention among developers for combining advanced AI capabilities with the flexibility to run on privately owned hardware. Unlike proprietary AI platforms such as ChatGPT and Claude, which are primarily accessed through cloud-based subscriptions, GLM 5.2 allows developers to download, customize, and deploy the model within their own computing environments, offering greater control over infrastructure, privacy, and operational costs.

The release comes as open-weight AI models continue to narrow the performance gap with leading commercial systems. While proprietary models have traditionally dominated the AI ecosystem with stronger reasoning capabilities, newer open-weight alternatives, including Meta's Llama family, Mistral, and now GLM 5.2, are demonstrating that many enterprise workloads no longer require exclusive reliance on premium cloud-hosted models. Businesses commonly use AI to summarize extensive document repositories, generate and debug software code, automate repetitive workflows, and retrieve information from internal knowledge bases, making cost-efficient deployment an increasingly important consideration.

Unlike fully open-source AI projects that typically publish training code, data processing pipelines, evaluation frameworks, and other development components, open-weight models primarily provide access to the trained model parameters. This enables organizations to fine-tune and integrate the model into their own applications while maintaining considerably more flexibility than closed AI services, where the underlying model remains inaccessible.

Interest in GLM 5.2 has also grown following demonstrations showing the model running locally on high-end Apple systems, including the Mac mini. Although these deployments require powerful hardware, they illustrate how advanced AI models are gradually becoming practical outside centralized cloud infrastructure. For organizations handling sensitive financial information, medical records, intellectual property, or confidential research, local deployment reduces the need to transmit data to third-party platforms, strengthening privacy protections while supporting regulatory compliance and data sovereignty requirements.

Despite its flexibility, GLM 5.2 remains an exceptionally demanding model. Built using a Mixture-of-Experts architecture containing between 744 billion and 753 billion parameters, the model occupies approximately 1.51TB of storage and memory in its original form. Developers therefore rely on quantization, a compression technique that reduces memory requirements by lowering the numerical precision of model weights. Even after aggressive optimization, approximately 240GB of memory is still required to load the model. GLM 5.2 also supports a one-million-token context window, allowing it to process entire software repositories, lengthy technical documentation, and extensive research collections within a single prompt, though doing so places additional demands on system memory.

As organizations continue evaluating how AI should be deployed across their operations, GLM 5.2 reflects a broader industry movement toward flexible AI ecosystems where proprietary, open-weight, and locally hosted models each serve different operational needs. Rather than replacing commercial AI platforms outright, models such as GLM 5.2 provide businesses with additional options to balance performance, cost, security, and data control as enterprise AI adoption continues to evolve.

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Gemini
AI BioShocking ChatGPT Claude Cyber Security Gemini

BioSchocking Attacks Tricked AI-powered Browsers into Data Theft


A new prompt injection termed “BioShocking” can manipulate AI-based browsers into treating malicious actions as a video game, and give away your login credentials. The technique was discovered by experts at security firm LayerX. The experts tricked six AI-powered browsers and assistants into recording users’ credentials and sending them to the threat actor. 

The browsers include:

ChatGPT Atlas from OpenAI

Comet from Perplexity

Anthropic’s Claude browser

Fellou

Genspark browser

Sigma browser

LayerX experts made a proof-of-concept (PoC), which was tested against these agentic AI browser products. The findings revealed that only one browser addressed the issue after receiving the report.

What is an AI browser?

An AI browser can streamline the entire workflow for the users. If you switch it to agent mode, it can click type, and visit sites that the user has already logged into. Access is the key point hare, which also becomes the problem.

BioShocking attack tactic

Experts made a (PoC) in which an infected webpage showed a BioShock-themed puzzle that rewards wrong answers. This tricks the browser that normal rules are not applicable. 

The trap works because of how these AI-powered browsers read. The webpage and instruction surface as a single stream of text, which allows a malicious page access in commands mimicking ordinary content or game rules. The agent can not tell which is which. Experts have termed this indirect prompt injection.

Tricking the browser

For instance, the compromise starts with a web page made as a puzzle. 3+4+=9 is a wrong answer but the browser rewards it. When the agent accepts that wrong answer is the reward, it follows game puzzle logic not security logic. Following this, the puzzle asks the browser to record login credentials. All six browsers could not flag it as something malicious. To win the game, the agent is commanded to go to a GitHub repository and share the data in the code, such as sensitive data like passwords.

When the link is sent to the target's GitHub repository, it retrieves SSH login credentials and sends them to the hackers. The main issue here is that browsers can’t differentiate between real scenarios and malicious fictional ones. 

According to LayerX, “Once the agents figured out the rules and learned that 'incorrect' actions are acceptable, they were no longer tied to reality.” “When tasked with the final step of the puzzle – compromising user credentials – all 6 agents failed to identify it as going against their safety guardrails,” the experts continued.

The PoC did not execute any malicious commands but warned that it could do so.

AI vendors’ response

According to experts, only OpenAI implemented a working patch for BioShocking in its browser.

Anthropic tried to fix the issue on its chrome login, but the patch was not working against the PoC. Perplexity did not fix the issue, and closed the report. 

LayerX advises that AI vendors should add specific user acknowledgement for sensitive work, and stronger security checks.

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Technology
AI Anthropic AI Claude AI KYC Technology

Anthropic to Restore Access to Claude Fable 5 After U.S. Lifts Export Controls



Anthropic is preparing to restore access to its Claude Fable 5 artificial intelligence model after the U.S. Department of Commerce lifted export controls that had temporarily restricted deployment of the company's most advanced AI systems.

The company announced on X that access to Claude Fable 5 will begin returning on Wednesday following the government's decision. Anthropic also confirmed that the export restrictions affecting both Claude Fable 5 and Claude Mythos 5 have been removed.

"We've received notice that the Department of Commerce has lifted export controls on Claude Fable 5 and Mythos 5," the company said in its statement, adding that it will begin restoring access on Wednesday and provide additional updates as the rollout progresses.

Anthropic also thanked its community for its patience during the temporary suspension and acknowledged the teams involved in preparing the models for redeployment.

Although the rollout is set to begin immediately, the company has not clarified whether Claude Fable 5 will become available to all users at the same time. It remains uncertain whether users outside the United States will regain access during the initial phase of the deployment or whether availability will expand gradually across different regions.

The export restrictions were introduced earlier after U.S. authorities raised national security concerns surrounding the deployment of highly capable frontier AI models. During that period, Anthropic temporarily suspended access while it worked to comply with government requirements and strengthen safeguards governing the release of its latest systems.

While restoring access to its models, Anthropic also appears to be expanding identity verification measures for certain Claude services.

Recent references to Know Your Customer (KYC) procedures discovered on the company's website suggest that some users may soon be required to verify their identities before accessing specific Claude capabilities. The references have prompted speculation that advanced models such as Claude Fable 5 could initially be limited to verified users or become available only in certain regions as Anthropic gradually expands access.

According to Anthropic's support documentation, identity verification is being introduced for a limited number of use cases. Users may encounter verification requests when using particular Claude features, during routine platform integrity reviews, or as part of broader safety, security and regulatory compliance checks.

The company says the verification process is intended to reduce abuse of its AI systems, enforce platform usage policies and meet legal obligations associated with operating increasingly powerful AI technologies.

"Being responsible with powerful technology starts with knowing who is using it," Anthropic said while explaining the purpose of the new verification measures.

Anthropic has selected Persona as its identity verification provider. Users who are asked to complete verification may be required to submit a valid government-issued photo identification document, including a passport, driver's license, state or provincial identification card, or a national identity card.

The company notes that several forms of identification will not be accepted during the verification process. These include photocopies, screenshots, scanned documents, mobile IDs, student identification cards, employee badges, bank cards and temporary paper identification documents.

Some users may also be asked to complete a live selfie verification using the camera on a computer or mobile device. According to Anthropic, the entire verification process typically takes less than five minutes to complete.

Addressing privacy concerns, the company says identity documents and selfie data are collected and stored by Persona rather than directly within Anthropic's own systems. However, Anthropic may access verification records through Persona when necessary, including during account review or appeal processes.

Anthropic also emphasized that identity verification information is not used to train Claude's AI models. Instead, the data is used solely to confirm a user's identity and to satisfy the company's legal, safety and compliance responsibilities.

The restoration of Claude Fable 5, together with the introduction of targeted identity verification measures, reflects the growing intersection of frontier AI development, government oversight and platform security. As developers release increasingly capable AI systems, compliance requirements, export regulations and stronger user verification are becoming a more prominent part of deploying advanced models responsibly.

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Trump administration AI
AI GPT-5.6 release OpenAI GPT-5.6 Sam Altman Technology Trump administration AI

OpenAI Delays GPT-5.6 Public Launch After US Government Seeks Limited Rollout

 

OpenAI has agreed to delay the wider release of its upcoming AI model, GPT-5.6, after the Trump administration requested that the company initially restrict access to a limited group of government-approved partners. The request was made due to concerns surrounding the model's advanced capabilities and potential national security implications.

The development, first reported by The Information on June 25, 2026, reflects the growing role of the US government in overseeing the deployment of cutting-edge artificial intelligence models. The move also signals a shift in how frontier AI systems may be introduced to the public going forward.

The government's request comes shortly after its dispute with rival AI startup Anthropic. Earlier this month, on June 12, the Trump administration directed Anthropic to temporarily take its latest AI models, Fable 5 and Mythos 5, offline under new export control measures aimed at preventing access by foreign nationals. Officials cited national security risks behind the decision.

Anthropic described the action as a "misunderstanding" and said it hoped to restore access "as soon as possible," though the incident established a significant precedent for government intervention in AI model releases.

Mythos had been shared with around 40 organisations, including Google, Microsoft and JPMorgan Chase, through a restricted programme known as Project Glasswing. According to reports, the model's ability to autonomously identify software vulnerabilities and carry out complex, multi-step cybersecurity attacks without human involvement raised concerns among US officials.

GPT-5.6 Viewed as Comparable to Mythos

A source familiar with the matter said both OpenAI and the US administration consider GPT-5.6 to be "on par" with Anthropic's Mythos, particularly regarding its cybersecurity capabilities. That assessment prompted officials to recommend a phased rollout instead of an immediate public launch.

OpenAI CEO Sam Altman reportedly informed employees during an internal Q&A session on June 25 that GPT-5.6 would first be made available to a select group of enterprise customers.

In a follow-up internal memo, Altman explained that the government would be "approving access customer by customer during this preview period." The request reportedly came from the Office of the National Cyber Director and the Office of Science and Technology Policy, while Commerce Secretary Howard Lutnick also advised OpenAI not to proceed without approvals from multiple federal agencies.

Although OpenAI agreed to the arrangement, Altman indicated that the company does not see this as a long-term solution. According to The Information, he wrote: "We’ve made clear to the U.S. government that this is not our preferred long-term model, and will work with them and others in industry to achieve a more sustainable approach for future releases."

Meanwhile, a White House official told CNN that the administration continues "to collaborate with frontier AI labs to develop shared approaches for addressing the challenges of scaling this technology."

The broader public release of GPT-5.6 is expected to take place a "couple of weeks" after the limited preview, depending on how the government-led approval process progresses.

AI Oversight Continues to Evolve

The latest development highlights the absence of a formal federal regulatory framework governing the review of advanced AI models before public deployment.

President Trump's executive order on "Promoting Advanced AI Innovation and Security" encourages AI companies to voluntarily provide frontier models to the government for cybersecurity assessments for up to one month before public release. However, compliance with the programme is voluntary rather than legally required.

For now, OpenAI's agreement with the US government represents one of the clearest examples of collaboration between federal authorities and an AI company. The outcome of GPT-5.6's controlled rollout could influence how other leading AI developers introduce powerful new models in the future.

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Anthropic Alleges Alibaba Conducted Massive AI Capability Extraction Campaign Against Claude

 


Anthropic has accused Chinese technology conglomerate Alibaba and its AI research division, Qwen, of carrying out a large-scale effort to extract capabilities from its Claude family of artificial intelligence models, describing the incident as the most extensive distillation operation the company has encountered.

The allegations were detailed in a June 10 letter sent to U.S. Senate Banking Committee Chair Tim Scott and Ranking Member Elizabeth Warren. In the correspondence, Anthropic claimed that operators linked to Alibaba and Qwen systematically interacted with Claude in an attempt to capture and reproduce some of the model's most advanced capabilities.

According to the company, the activity occurred between April 22 and June 5, 2026. During that period, Anthropic says it recorded more than 28.8 million exchanges associated with the operation. The requests were allegedly distributed across nearly 25,000 fraudulent accounts, enabling the actors to conduct high-volume interactions with the platform while obscuring the true source of the activity.

Anthropic stated that the campaign was not focused on general-purpose chatbot functions. Instead, it allegedly targeted capabilities considered among the most valuable within the Claude ecosystem, including software engineering tasks and advanced agentic reasoning. These functions form a critical component of the company's Mythos Preview model, one of Anthropic's most sophisticated AI systems designed to perform complex reasoning and autonomous task execution.

At the center of the allegations is a technique known as adversarial distillation. In machine learning, distillation generally refers to the process of training a model using outputs generated by another system. While the approach itself is commonly used within the AI industry, Anthropic argues that the method becomes problematic when it relies on unauthorized access to proprietary models.

According to the company, the actors behind the campaign repeatedly queried Claude and collected its responses at scale. Those outputs could then be used as training material for another AI system, allowing developers to reproduce aspects of Claude's behavior without investing the time, computational resources, and research expenditure typically required to build a frontier model from the ground up.

Anthropic warned lawmakers that such activity enables organizations to appropriate years of research and development through large-scale extraction campaigns. The company argued that these operations are designed to gather capabilities developed by leading U.S. AI laboratories and incorporate them into competing systems without bearing the costs associated with original model development.

Beyond intellectual property concerns, Anthropic also raised questions about safety. The company noted that models trained through adversarial distillation may replicate useful capabilities while failing to inherit the safeguards, alignment mechanisms, and risk controls embedded within the original system. As a result, the practice could create AI models that retain advanced functionality but operate with fewer protections against misuse.

The allegations against Alibaba follow earlier claims made by Anthropic regarding unauthorized access attempts linked to Chinese AI developers. In February 2026, the company disclosed that DeepSeek, the startup whose low-cost AI models attracted global attention in 2025, was among several organizations accused of attempting to improperly obtain Claude outputs. Anthropic now characterizes these incidents as part of a broader pattern of repeated efforts to extract capabilities from leading U.S. AI systems.

The dispute emerges amid growing government scrutiny of advanced AI technologies. Earlier this month, Anthropic revealed that it had received guidance from the Trump administration requiring the company to restrict access to its newest AI models, including Fable 5 and Mythos 5. Under the directive, access would be limited to U.S. persons, preventing non-U.S. citizens, including some employees, from interacting with the latest systems.

The issue is also beginning to influence policy discussions on Capitol Hill. Senators Bill Hagerty and Andy Kim are reportedly preparing legislation that would authorize sanctions or other penalties against Chinese organizations found to have improperly obtained outputs from U.S. AI models for the purpose of training competing systems. The proposal reflects growing concern among lawmakers that frontier AI capabilities have become both strategic economic assets and matters of national security.

Alibaba has not publicly responded to the allegations.

The dispute surfaces a new battleground in the global AI race. As companies invest billions of dollars to develop increasingly capable models, concerns are shifting beyond traditional cybersecurity threats toward the protection of model knowledge itself. For AI developers, the challenge is no longer limited to securing infrastructure and data. It increasingly involves preventing the large-scale extraction of capabilities that can be repurposed to accelerate the development of rival systems.

With governments, technology companies, and regulators paying closer attention to model security, the Anthropic-Alibaba dispute may become an early test case for how the industry addresses unauthorized AI capability harvesting and the growing geopolitical competition surrounding advanced artificial intelligence.

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Technology
AI CISO Cyber Threats Cybersecurity ISSA Technology

Cybersecurity Leaders Face Growing Workloads as AI Changes the Job

 



The responsibilities placed on cybersecurity leaders are becoming increasingly difficult to manage as organizations face a growing number of cyber threats, rapid adoption of artificial intelligence technologies, and increasing demands for security oversight across the business.

A recent survey conducted by the Information Systems Security Association (ISSA) International and research firm Omdia found that 68% of cybersecurity and IT professionals believe their jobs are more difficult today than they were two years ago. More than half of respondents reported heavier workloads and greater operational complexity (55%), while 52% said the volume and intensity of cyber threats have become more overwhelming.

Security teams are being asked to protect increasingly complex digital environments while also helping organizations adopt new technologies such as generative AI. At the same time, many security leaders say they are struggling to secure sufficient support from other parts of the business.

According to Shawn Murray, former president of ISSA and a fractional Chief Information Security Officer (CISO), many security executives regularly work long hours while attempting to address security concerns that are often introduced without their involvement. In some organizations, new technologies are adopted before security teams are included in planning discussions, creating additional challenges for risk management and governance.

As a result, some experienced CISOs are leaving traditional full-time leadership positions and choosing consulting or fractional roles instead. These arrangements allow security professionals to work with multiple organizations while focusing on businesses that are willing to involve cybersecurity leaders in strategic decision-making.

While legal accountability was once considered one of the largest concerns facing CISOs, the survey suggests that anxiety around personal liability has become less prominent than in previous years. Instead, many respondents identified the security implications of artificial intelligence as one of the most significant new sources of pressure.

AI has created both opportunities and challenges for cybersecurity teams. One growing concern is the rise of "shadow AI," where employees begin using AI tools and services without notifying security teams or obtaining formal approval. Similar issues emerged during the early stages of cloud adoption, when departments could deploy new services independently without providing visibility to cybersecurity staff.

This lack of visibility can create greater security gaps. When security teams do not know which AI applications, models, or processes are being used across an organization, it becomes more difficult to identify risks, monitor suspicious activity, and respond effectively to potential incidents.

Despite these concerns, cybersecurity professionals are increasingly interested in using AI to improve their own operations. The survey found that 37% of respondents are already using AI-powered tools to address cybersecurity challenges, while another 46% plan to adopt such technologies in the future.

Among the most common use cases identified by respondents were automated cybersecurity assessments, software testing, predictive risk analysis, and threat detection. These capabilities could help security teams reduce manual workloads and process large volumes of security data more efficiently.

Alex Hutton, CISO at Atlantic Union Bank, noted that the cybersecurity environment has changed significantly in recent years. Whether organizations fully embrace advanced AI systems or not, security professionals must continuously learn about new technologies, understand emerging risks, and adapt their security strategies accordingly.

The survey also highlighted a notable shift in how organizations obtain cybersecurity leadership. The percentage of companies employing full-time CISOs declined from 76% in 2024 to 63%, while the use of fractional CISOs increased from 6% to 15% over the same period.

Industry observers believe this trend reflects growing demand for cybersecurity expertise rather than a reduction in the importance of the CISO role. Many small and mid-sized organizations face the same security, compliance, and governance challenges as larger enterprises but often lack the budget required to hire a full-time executive.

Cyber insurance requirements are also contributing to demand for experienced security leadership. Organizations are increasingly expected to demonstrate strong cybersecurity practices and effective risk management controls before obtaining coverage or meeting insurer requirements. CISOs frequently play a central role in helping businesses assess risks, improve security programs, and document compliance efforts.

According to Hutton, the rise of fractional and virtual CISOs provides organizations with access to executive-level security guidance without requiring a full-time appointment. Rather than signaling the decline of cybersecurity leadership positions, the change may represent an expansion of cybersecurity services to organizations that previously could not afford dedicated executive expertise.

As cyber threats continue to grow and AI reshapes business operations, cybersecurity leaders are expected to remain critical decision-makers. However, the role itself is changing, requiring security professionals to balance technical oversight, business strategy, regulatory expectations, and emerging technologies in an increasingly demanding environment.

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Technology
AI Claude Crypto Data Malware Attack Technology

Hackers Exploit Fake Claude Code Installers and Install Malware


Developers looking into Claude Code deployment instructions could be lured into an advanced malware campaign that hides itself as a genuine AI tooling documentation. 

Fake Claude code exploit

Experts found a few fake Claude Code and developer platform websites built to steal credentials, cryptocurrency, and API keys.

According to Straiker researchers, “the attack chain runs on the same unchecked trust that makes AI developer tools so easy to adopt.  “You copy a command. You paste it in your terminal. By then, it’s already too late,” said Straiker researchers in their analysis of the campaign. 

Highlights of the fake Claude code campaign 

1. Experts found over 88 fake domains mimicking Claude Code and other developer sites. The campaign utilises SEO infection and Google ads to deploy malicious install web pages over genuine documentation.

2. Threat actors hide infected commands within genuine installation commands, without impacting the deployment process.

3. The malware particularly attacks AI-based assets such as cloud development credentials, API keys, and verification tokens.

About the credential theft campaign 

The campaign attacked users of famous AI and developer tools, such as Claude Code, JetBrains, Perplexity Comet, and Cline. 

As per the experts, the operation depends on over 88 domains hosted throughout genuine platforms and constantly shuffles infrastructure, letting malicious sites to immediately resurface after shutdowns. To trap targets, threat actors use redirect chains, SEO poisoning and paid Google ads that place scammed installations over genuine documentation in search results.

These websites closely impersonate genuine vendor resources and demonstrate installation commands that look genuine but include hidden separators, such as “&,” that launch malicious actions along with the expected software deployment.

In various incidents, the genuine command still runs effectively, helping hide the hack.

Delivery of malware and launch tactics

Experts found various delivery techniques, such as rundll32.exe loading infected DLLs, Base64-encoded commands, mshta.exe abuse, JavaScript-based payloads, and GitHub-hosted scripts. 

By such techniques, hackers improve their potential to escape convention detection tools. Contrary to infostealers, the campaign pick on AI assets like authentication tokens, API Key, and cloud development credentials from tools such as Continue[.]dev, Cline. 

After execution, the malware uses a multi-level malicious chain that features encoded C2 communications, anti-analysis capabilities, fileless execution tactics, and credential theft functions.

Experts found the primary payload as ACRStealer, a malware family that steals information and has developed to include sophisticated encryption and escape tactics. Experts also identified a cryptocurrency clipboard hacker that rediverts transactions by replacing copied wallet addresses.

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AI ai agents Computing Microsoft Technology

Microsoft Unveils Project Solara, AI Agents to Replace Computing


Satya Nadella, Microsoft CEO, said computing has entered a new era where AI agents will take over to become the main interface, not applications or operating systems. 

Microsoft launches project Solara

Microsoft also released Project Solara, a Qualcomm powered platform built to support Agentic-AI devices that can work across apps, screens, and workflows. According to Microsoft, the next era of computing will not be characterized by such things. 

At the Microsoft Build 2026 developer conference, Nadella said that Microsoft is shifting from a world based on apps and devices to one where AI agents will dominate the main interface between computers and users.

Nadella said this while Microsoft showcased Project Solara, a new chip-to-cloud platform built in partnership with Qualcomm which is currently called “agent-first computing”. Microsoft said that agentic AI is developing beyond assistants integrated inside applications and will streamline operations across workflows. This may impact the future of computer usage. 

Project Solara is based on the company’s belief that agentic AI will become the key technology for people to interact. Instead of running apps individually and  tasks manually, users will use AI agents.

About Project Solara

It is a chip-to-cloud platform that integrates Azure cloud services, hardware, and software to enable agent-first usage. It will also allow people to interact dynamically with AI via specific form factors. Solara is built around the goal that AI agents are the latest unit of programming and a novel way for people to interact with computers.

In a research paper published around the same time, Microsoft said that computing has shifted from mainframes to PCs, smartphones, and IoTs. 

Each generation inches closer to users. AI agents will become the next interaction layer, letting people interact with computers via natural language instead of interfaces, menus, and navigating apps.

How will the AI agents replace apps?

Microsoft laid three levels of integrating AI. 

In the first stage, AI is put beside an app as a helper, like the LLM chatbots of today. 

In the second level, AI is directly integrated inside apps, which makes it central to user experience. 

In the third level, AI operates outside the individual apps, streamlining workflows while maintaining context. Solara is particularly built for the third stage.
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Nvidia Introduces AI-Focused PC Chip as Industry Pushes Toward Local AI Processing

 Nvidia has announced a new processor designed to run artificial intelligence applications directly on personal computers, signaling the company's latest effort to expand beyond the data center market and into everyday computing devices.

The announcement was made by Nvidia Chief Executive Officer Jensen Huang during a keynote presentation in Taipei ahead of Computex, one of the world's largest technology trade shows. The new chip, called RTX Spark, was developed as part of a long-running collaboration between Nvidia and Microsoft aimed at adapting personal computers for increasingly complex AI workloads.

Unlike many current AI services that rely on cloud infrastructure to process requests, the RTX Spark platform is designed to execute AI tasks locally on laptops and desktop systems. This allows certain AI functions to operate directly on the device rather than sending data to remote servers for processing. Industry observers believe this approach could improve response times, reduce dependence on internet connectivity, and give users greater control over sensitive information.

Nvidia said the processor was developed in partnership with Taiwanese semiconductor company MediaTek. Systems powered by the chip are expected to become available later this year through several major computer manufacturers, including Dell, HP, Lenovo, ASUS, MSI, and Microsoft's Surface product line. Additional products from Acer and GIGABYTE are also expected to follow.

The launch places Nvidia in more direct competition with companies such as AMD, Intel, Apple, and Qualcomm, all of which are pursuing their own strategies for bringing artificial intelligence capabilities to personal computers. While Nvidia has established a dominant position in hardware used to train large AI models, the company is now increasingly focused on technologies that run AI applications after those models have already been developed.

A major objective behind the RTX Spark platform is support for so-called AI agents. Unlike conventional chatbots that simply answer user questions, AI agents are designed to perform sequences of tasks with limited human intervention. Potential applications include managing schedules, conducting research, organizing information, generating content, and carrying out routine administrative work.

According to Nvidia, future personal computers will need significantly more processing capability to support these systems because AI agents are expected to operate continuously in the background rather than responding only when a user initiates an action.

The company's emphasis on local AI processing reflects a broader trend emerging across the technology sector. Many firms are exploring ways to move AI workloads closer to users instead of relying entirely on cloud-based infrastructure. Supporters of this approach argue that local processing can improve performance while reducing network delays and operational costs.

The commercial success of AI-powered PCs, however, remains uncertain. Although several manufacturers have promoted AI-enabled devices as the next phase of personal computing, adoption has been uneven. Some vendors have reported positive contributions to sales, while others have indicated that demand has not reached the levels initially anticipated when the category was introduced.

Technology analysts nevertheless view the market as an area with long-term growth potential. Neil Shah, co-founder of Counterpoint Research, said the shift from application-centered computing toward AI-assisted systems could fundamentally change how users interact with their devices. He suggested that personal AI agents operating on local hardware may become increasingly common as the technology matures.

During his presentation, Huang also highlighted Nvidia's Vera central processing unit, which he previously described as providing access to a market opportunity worth approximately $200 billion. Nvidia stated that organizations including OpenAI, Anthropic, and SpaceX are among the early adopters evaluating the technology.

The Computex presentation also featured discussion about the future direction of artificial intelligence across the computing industry. Qualcomm Chief Executive Officer Cristiano Amon, speaking separately ahead of the event, argued that the industry is moving beyond AI systems that simply generate responses to prompts and toward software capable of carrying out tasks independently. He described 2026 as a potential turning point for agent-based AI, adding that existing device architectures were largely designed around actions initiated by users rather than autonomous software systems.

Huang also addressed concerns that advances in artificial intelligence could reduce employment opportunities for software developers. Rejecting that view, he argued that AI tools are increasing productivity and enabling organizations to undertake larger software projects, which in turn could create additional demand for engineering talent.

The announcements come as Nvidia continues to expand its presence across multiple segments of the AI market. After becoming one of the leading suppliers of hardware for AI model training, the company is now seeking a larger role in personal computing, inference processing, and AI applications designed to run directly on consumer devices.

The developments were unveiled in Taiwan, a location Huang described as central to the global AI supply chain. The Nvidia chief, who was born in the southern Taiwanese city of Tainan, has repeatedly emphasized the island's importance to the future development and production of advanced computing technologies.

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Cyber Security: Six Cyber Threats to Look Out for in 2026


With industries being digitized, cybercrime is also advancing. This year, besides being opportunistic, threats have also become highly targeted, intelligent, and automated. 

The data comes from UK Government’s Cyber Security Breaches Survey 2025, which hints that 43% of businesses and 30% of charities listed an attack or a cyber breach or attack in the past 12 months. That’s a surprising 61,000 charities and 612,000 businesses impacted. 

Despite the data, businesses can lower their risk of cyber threats. But it is important to understand these key risks to stay safe and prepare for the next danger.

Six rising common cyber threats

1. Deepfakes: Deepfakes have shifted from niche technology to a major threat. Hackers nowadays use AI-generated audio and media to mimic organization staff. This can be risky in procurement or finance, where hackers push staff to send funds, share personal data, or approve finances, where the hackers pose as business leaders.

2. Supply-chain attacks: Instead of targeting organizations directly, hackers are targeting third-party vendors to get access to various firms at once via supply-chain attacks. The attack tactic abuses trust and internal security sometimes may not address all the threats in the supply chain. One hacked vendor can prompt a domino effect throughout hundreds of businesses. 

3. AI-powered phishing hacks: Phishing is one of the most common attacks in the past 12 months, and the tactic has changed significantly over the years. Most of the phishing attacks today are supported by AI tools and hackers are copying internal comms.

4. Credential stuffing attack: Weak passwords are the biggest reasons for hacks these days. In such attacks, hackers use stolen login credentials from past hacks and test them automatically across distinct platforms.

5. IoT and device flaws: As IoT is increasing, the hack surface also widens. Many devices such as sensors, cameras and industrial machinery still have limitations. Hackers abuse these flaws to access larger corporate networks. Traditional cyber security methods tend to ignore these flaws, and this has resulted in a significant risk.

6. Cloud errors: A simple thing such as exposed storage bucket or false access setting can expose sensitive data publicly accessible. These cases don’t get hacked as the information is unprotected. Currently, cloud storage environments are advanced, and building robust configuration hygiene has become a top critical priority.

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Technology
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Akira Gang Claims Ransomware Attack at Convention Center, Extorts $250 Million


Akira gang extorts $250 million

Akira, the infamous ransomware gang has extorted over $250 million from businesses globally. It is now blackmailing to leak 46 GBs of data allegedly extorted from the Buffalo Convention Center. The stolen data includes financial information, contracts, employee records, and private data linked to around 1,80,000 people.

What do the experts say?

Resilience director at Gate 15, Ben Taylor has warned that ransomware gangs often boast the amount of data stolen. The alleged figure of 1,80,00 impacted people suggests data retrieved via a third-party provider, exaggerated claims to extort victims, or direct breach of venue systems. 

The dark web monitoring firm Breach Sense verified the Buffalo Convention Center data breach. The FBI has classified Akira as a ransomware-as-a-service gang that extorted over $250 million from hundreds of businesses since 2023.

Convention centres have become a lucrative target for hackers

Convention centers, which increasingly act as repository for guest registrations, exhibitor information, payment data, contracts, and operational systems, are facing an escalating cybersecurity issue as a result of the alleged incident.

Ransomware gangs claim that they have gained access to a company in order to obtain leverage for a swift and simple payment. According to Taylor, there are situations in which these assertions are true and some that are not.

Ransomware as double extortion

Additionally, the attack illustrates how contemporary ransomware operations have evolved. "Double extortion" is a common method used by organizations such as Akira. Before encrypting networks, they take confidential files and threaten to reveal the information if payment is not received.

According to Taylor, developments in AI are intensifying the problem by making it simpler to scale and customize phishing campaigns and other cybercrime tactics.

About the victims

Buffalo Convention Center was not the only enterprise to suffer a ransomware attack. 

High-case hospital hacks showcase the operational effect of a ransomware attack. According to MGM Resorts, in 2023, a cyberattack leaked personal data linked to millions of guests and impacted hotel operations for days. Another famous enterprise, Caesars Entertainment was also breached and allegedly paid $15 million in ransom to hackers.

The dangers go beyond convention centers. In April, Carnival Corporation was attacked by a gang that claims to have stolen over 8.7 million records such as dates of birth, names, and other personal data. 

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US
AI Cyber Attacks Data Donald Trump MyPillow Play Gang Ransomware US

Play Gang Claims Responsibility for MyPillow Hack, Company CEO Denies the Breach


The US military has always known that threat actors could use location data to spy on troops’ devices. The military also knows the easy solutions for the problem. But the Pentagon implemented none of these security measures. 

Recently, CySecurity reported that threat actors were using digital advertising data to attack US soldiers in war zones. The US law enforcement recently warned about the “anti-tech” extremism because the AI criticism was growing in the country.

Play gang takes responsibility 

The Play ransomware hacking group claimed the data theft behind the US pillow manufacturer called MyPillow. It stole personal and private confidential data from the victim. 

About the target

MyPillow was founded by 2020 Minnesota gubernatorial candidate and 220 election conspiracy theorist Mike Lindell.

The stolen data claim first surfaced on Play’s blog recently, it threatened that it was able to steal an unknown amount of information which may be exposed soon which may leak “"private and personal confidential data, clients and etc. documents, budget, payroll, IDs, taxes, finance information."

The claim, which appeared on Play's dark web leak portal earlier this week, threatens that an undeclared amount of data will be released on Friday, potentially exposing "private and personal confidential data, clients and etc. documents,budget, payroll, IDs, taxes, finance information."

High profile case

Straight Arrow News first reported about the incident. But MyPillow’s high-profile CEO Mike Lindell has denied claims of any ransomware attack which happened at all.

MyPillow was a lucrative victim for the threat actors, as Lindell’s role in pumping the controversial claims that the 2020 US presidential campaign was rigged against the now President Donald Trump.

According to Straight Arrow News, Lindell claimed in a recent interview on his website, Lindell TV, that political attacks during the previous few years cost MyPillow $400 million in damages. 

What next?

Lindell stated that he will submit an application for reimbursement from Trump's $1.8 billion "Anti-Weaponization Fund," which was established as part of Trump's settlement of an Internal Revenue Service lawsuit. 

The settlement, according to critics, offered Trump a slush fund to compensate rioters on January 6 and other individuals who have spread election conspiracy theories.

Whether MyPillow was hacked is not confirmed at the time of writing. The company denies the claim, whereas Play gang takes responsibility.
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