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Think Hotel Wi-Fi Is Safe? Hackers Have Several Ways to Prove You Wrong

For many travelers, connecting to hotel Wi-Fi is one of the first things they do after checking in. But while some guests use the network for banking and work, others avoid sensitive activity unless they are connected through a VPN.

So, how safe is hotel Wi-Fi?

Cybersecurity experts say the answer is more nuanced than simply calling public Wi-Fi dangerous. Modern encryption has reduced many of the risks associated with public networks, but hotel Wi-Fi can still expose travelers to rogue networks, phishing attacks, poorly configured infrastructure and vulnerable devices.

In many cases, the biggest risk may not be the network itself, but how the user connects to and behaves on it.

The first risk can come from a fake network

Security analyst Udaya Vemuri advises travelers to be cautious about joining a network simply because its name appears to belong to the hotel.

Attackers can create fake Wi-Fi networks with names almost identical to legitimate hotel networks. The technique, known as an "evil twin" attack, can trick guests into connecting to an attacker-controlled access point.

The FBI's Internet Crime Complaint Center warned about this threat in a 2020 advisory, noting that criminals can create networks resembling legitimate hotel Wi-Fi and potentially monitor activity or redirect victims to fraudulent login pages. The agency also warned that hotel guests have limited control over the security of the infrastructure they are using, which may prioritize convenience over stronger security practices.

Travelers should therefore confirm the exact Wi-Fi name with hotel staff before connecting rather than selecting the network that merely looks familiar.

Simply sharing a network does not mean you are compromised

Dahvid Schloss, chief operating officer of cybersecurity firm Suzu Labs and a former government hacker who has security-tested hotel chains, takes a less alarmist view.

Schloss compares hotel Wi-Fi with other public networks, such as those in coffee shops. In his assessment, the likelihood of being attacked simply because another malicious user is connected to the same network is low.

That distinction matters because the common image of hackers automatically reading passwords from public Wi-Fi is outdated.

The Federal Trade Commission says most websites now use encryption, meaning information sent between a device and a legitimate website is generally protected even when the underlying network is public. HTTPS can therefore provide substantial protection against traffic interception.

However, HTTPS does not prove that a website is legitimate. Attackers can create encrypted fraudulent websites and use phishing or redirection to persuade victims to submit credentials.

This means a traveler can still be exposed even when the connection itself appears encrypted.

Fake hotel portals can steal credentials

Hotels commonly use captive portals that redirect guests to a webpage after they connect to Wi-Fi. These pages may request a room number, surname, email address or access code.

Because travelers expect this process, attackers can imitate it.

A rogue network may display a fake hotel login page or redirect users to a fraudulent Microsoft 365, email or banking page. In such cases, the attacker does not necessarily need to break encryption. The victim may simply be tricked into providing the information.

This makes phishing and social engineering an important part of the hotel Wi-Fi threat.

Network security is not a perfect guarantee

Recent research also shows why travelers should not assume that network-level protections make public Wi-Fi completely secure.

Researchers at the University of California, Riverside reported in February 2026 that weaknesses in Wi-Fi client isolation can, under certain conditions, allow attackers to bypass protections designed to prevent devices on the same network from interacting with one another.

Their AirSnitch research demonstrated techniques that could potentially allow an attacker to intercept or manipulate traffic despite client isolation.

The findings do not mean every hotel network is vulnerable, but they reinforce an important point: users should not rely entirely on the security mechanisms implemented by a public network.

Your device can be the weakest link

Both experts place considerable emphasis on user behavior.

Schloss argues that laptops can be particularly vulnerable to poor security habits because they are frequently used to download files, install software and access corporate systems. Smartphones are not immune, but their operating systems often impose stronger application restrictions.

The FBI recommends updating operating systems and applications before travel, keeping security software current, backing up important data, disabling Bluetooth when unnecessary and preventing devices from automatically reconnecting to public networks.

Automatic reconnection is particularly important because a device may join a previously saved network without the user consciously verifying that it is legitimate.

Browser warnings should also never be ignored. A certificate warning, unexpected redirect or request to install software can indicate that something is wrong with the connection or destination.

Use cellular data for sensitive activity

Vemuri takes a more cautious approach when handling sensitive information. For banking, work systems and other private activity, he uses a mobile hotspot instead of hotel Wi-Fi. When hotel Wi-Fi is unavoidable, he keeps devices updated, enables multifactor authentication and avoids sensitive tasks.

The FBI similarly recommends using a phone's hotspot instead of hotel Wi-Fi when possible, particularly for sensitive activity and telework.

A cellular hotspot is not completely immune to cyber threats, but it removes the user from the hotel's shared wireless environment and reduces exposure to risks associated with public Wi-Fi.

A VPN and MFA can add protection

For travelers who need to use hotel Wi-Fi, a reputable VPN can provide another layer of security by encrypting traffic between the device and the VPN provider. The FBI recommends reputable VPNs for telework over hotel Wi-Fi.

A VPN is not a substitute for other security measures, however. It cannot prevent phishing, malware downloads or users from voluntarily entering credentials into fraudulent websites.

Multifactor authentication can limit the damage if a password is compromised. The FBI recommends MFA for sensitive accounts and advises users to enable login notifications so suspicious activity can be detected quickly.

Travelers should configure MFA before leaving home rather than waiting until they are already on the road.

What travelers should do

Before connecting to hotel Wi-Fi, users should:

Confirm the legitimate network name with hotel staff.
Update their operating system, browser and applications.
Disable automatic connection to public networks.
Enable MFA and account security alerts.
Use a cellular hotspot for banking and highly sensitive activity where possible.
Use a reputable VPN for sensitive work when hotel Wi-Fi is unavoidable.
Verify the website address and HTTPS before entering credentials.
Avoid unfamiliar downloads or software updates prompted by Wi-Fi portals.
Disable Bluetooth when it is not needed.
Never bypass browser security warnings.

So, is hotel Wi-Fi safe?

Hotel Wi-Fi is not automatically dangerous, but it should not be treated as a trusted network either.

Simply sharing a network with an attacker does not mean a modern device will automatically be compromised, particularly when legitimate services use encryption. At the same time, rogue access points, fake captive portals, phishing, vulnerable devices and weaknesses in network isolation can create opportunities for attackers.

For routine browsing, an updated device using legitimate HTTPS websites can be reasonably protected. For banking, corporate systems and other highly sensitive activity, using a cellular hotspot remains the more cautious option.

The practical rule for travelers is simple: do not panic about hotel Wi-Fi, but do not trust it blindly either. Verify the network, secure your devices and accounts, and keep sensitive activity off shared networks whenever possible.

ShinyHunters Data Leaks Fuel $2,000 Sextortion Email Scam

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User Privacy

Abortion Data Leak Data Breach Financial crime ShinyHunters User Privacy

ShinyHunters Data Leaks Fuel $2,000 Sextortion Email Scam

Cybercriminals are exploiting email addresses exposed in previous ShinyHunters data leaks to conduct a new sextortion campaign demanding $2,000 in Bitcoin. The fraudulent messages falsely claim that ShinyHunters compromised victims’ phones and computers, accessed their cameras and microphones, and recorded them visiting adult websites. However, the campaign appears to involve unrelated scammers who downloaded previously leaked information and are using it to make their threats appear credible.

The emails reportedly use random sender addresses and names such as “ShinyHunters” or “You’ve Been HACKED.” Their subject line commonly reads “Information about your online security.” In the messages, attackers mention companies whose databases were previously exposed, including Amtrak, Hallmark, Substack, Betterment, CarGurus, ADT, Panera Bread, and McGraw Hill. By identifying a company connected to the recipient’s email address, scammers attempt to create the impression that they specifically targeted the victim.

The scam messages claim that attackers installed malware capable of accessing a victim’s microphone, camera, keyboard, photographs, browsing history, conversations, and contact list. They then threaten to send allegedly recorded intimate videos to the recipient’s family, friends, colleagues, and business contacts unless payment is made within 48 hours. The emails also instruct recipients not to contact law enforcement, reply, or reset their devices, claiming that stolen data is stored on remote servers. These warnings are intimidation tactics rather than evidence of a genuine device compromise.

According to the report, the campaign may have begun in April, with victims and organizations sharing similar warnings online. Betterment acknowledged that some customers received threatening emails and described them as a common extortion scam. The company emphasized that knowing someone’s email address does not give criminals the ability to install malware or access that person’s device. It advised recipients not to reply, pay, click links, or open attachments, while asking anyone who interacted with the message to contact its fraud team.

People receiving these emails should remain calm and avoid paying the Bitcoin demand, because payment does not guarantee that scammers will stop contacting them. Recipients should preserve the message as evidence, report it to their email provider and relevant cybercrime authorities, then delete it after checking for suspicious account activity. They should also use unique passwords, enable multifactor authentication, update devices, and monitor accounts associated with the exposed email address. The campaign demonstrates how data stolen in one breach can later be reused by unrelated criminals to support convincing but false threats.

GrapheneOS Duress Feature Puts Digital Privacy and Evidence Laws to the Test

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Digital Privacy Risks

Cyber Security Data Privacy Risks Data protection data security Digital Privacy Digital Privacy Risks

GrapheneOS Duress Feature Puts Digital Privacy and Evidence Laws to the Test

A federal case concerning a local Atlanta activist is fueling controversy over privacy issues relating to cell phone searches and whether simply wiping data from a device qualifies as destroying evidence. The case involves GrapheneOS, an open-source privacy-focused customized Android OS that utilizes the so-called duress PIN/password to permanently delete data from a phone if the correct code is entered by investigators.

GrapheneOS developers describe their creation’s features on the project’s website, noting that it includes a “duress PIN/password” that causes the phone to immediately wipe all user data and any eSIMs from the device when the “wrong” passcode is entered at the time of credential prompt. According to court records, and reports by the press, in January 2025, Samuel Tunick, an Atlanta-based activist, was taken into custody by the US Customs and Border Protection (CBP) agents at the airport in Atlanta upon his return from the Dominican Republic.

It seems Tunick was questioned by the customs officials several times and eventually gave them a password to his phone. His phone was wiped immediately after he entered the code. Samuel now faces charges brought by federal prosecutors who alleged that he “conspired to destroy property of the United States.” The defense is arguing that the search was not lawful; the activist was not informed of his constitutional rights and was not allowed to contact a lawyer.

Additionally, Samuel’s attorney points out that Tunick was accused of possessing child sexual abuse material, and the only reason why he was searched was because of his activism surrounding the Stop Cop City movement. It is worth noting that privacy and security specialists have raised concerns regarding the matter and regard it as an important precedent. The GrapheneOS Foundation, an entity that maintains the software, has stated that it believed that its customized Android OS features “security capabilities that are appropriate and legitimate.”

Some experts suggest that even if Tunick did wipe his phone, there is no way investigators could prove that he did not do so because of his decision to employ GrapheneOS. The case creates grounds for debate about the potential for cell phone software to create challenges for law enforcement. In particular, the case’s outcome will set a legal precedent about whether a device owner’s intentional interference with a search (by wiping data) constitutes evidence tampering.

GrapheneOS itself is a valid privacy-centric OS, but the case concerning the Atlanta activist will shape the jurisprudence surrounding the wiping of cell phone data by users and the extent to which such action may be regarded as obstructing law enforcement.

Nearly 800 Malicious npm Packages Found Delivering Cross-Platform RAT and Infostealer

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Software Supply Chain Security

AI Slop-Squatting Cross-Platform RAT Infostealer Malware Malicious Npm Packages malware Npm Malware Npm Supply Chain Attack Software Supply Chain Security

Nearly 800 Malicious npm Packages Found Delivering Cross-Platform RAT and Infostealer

An extensive software supply chain attack targeting developers and systems running Windows, Mac OS, and Linux has identified approximately 800 malicious packages on the npm registry as part of this campaign. Researchers report that the campaign represents a shift from traditional typosquatting to high-volume "AI slop-squatting."

A malicious attacker may generate an enormous number of plausible-looking package names rather than merely imitating a few popular libraries, which may be selected by mistake through developer typos, automated suggestions, or artificial intelligence coding assistants. The threat actors can cast a much wider net over the NPM ecosystem this way, according to OpenSourceMalware researcher Paul McCarty. The packages appear legitimate by using AI-generated, squatted, randomly generated, or typosquatted names. Upon installation, they deploy WEL1DROPPER, a downloader designed to identify the operating system and processor architecture of the victim before retrieving the appropriate malware payload.

The README files of the packages instruct developers to load the malicious modules using JavaScript's built-in require() function, as opposed to many npm supply chain attacks that utilize preinstall or postinstall scripts.

A malicious behavior may be less apparent during installation using this approach. Furthermore, the campaign highlights how threat actors are increasingly distributing RAT components across multiple NPM packages as opposed to relying exclusively on a single malicious package. By using this approach, malware can be spread across a broader developer ecosystem, and individual malicious components can be more difficult to detect during routine package reviews. This campaign targets developers working across Windows, Linux, and macOS environments, increasing the reach of the campaign beyond one operating system.

When the HTTPS delivery fails, it switches to DNS TXT records associated with the domain wel1[.]ru. If the next-stage payload cannot be downloaded from Cloudflare Workers. Upon access to the compromised system, the malware retrieves multiple encoded chunks, combines them, decodes the resulting data, and executes the payload.

Sonatype has identified the campaign as Flooding Dropper. In its analysis, Sonatype found additional capabilities designed to evade security monitoring and maintain persistence. In Windows, the malware is reported to interfere with Event Tracing for Windows (ETW) and Antimalware Scan Interface (AMSI), check for virtual environments and sandboxes, as well as establish persistence through Registry Run keys and scheduled processes.

A compromised development environment or continuous integration/continuous delivery system can contain valuable credentials and secrets, including cloud access credentials, SSH credentials, NPM tokens, source code, and environment variables. These risks extend beyond the individual developer workstation. Infections of such systems can therefore allow attackers access to resources that go well beyond the machine originally compromised.

As with the MacOS version, the macOS variant searches for analytical and debugging artifacts before establishing persistence with a LaunchAgent. This Linux version has been delivered as an ELF executable packed with UPX and will allow Sliver, an open-source control framework, to be deployed. Among the packages, researchers also found a legitimate file called telemetry.js. It appears, however, that the file has the same downloader functionality and is intended to create additional noise and make the packages appear to be ordinary analytics or profiling software, thus confusing.

According to researchers, the macOS payload contains references to Russian banking and payment services, suggesting that the campaign has ties to Russian financial targets. As suspected by OpenSourceMalware, this operation could represent an evolution of the Moika campaign, which previously involved hundreds of malicious npm packages. As opposed to a conventional software vulnerability, the activity is being treated as a malware distribution campaign that has been actively deployed. Packages have been published to the public npm registry and are being removed as they become apparent.

In addition, researchers indicated that the campaign is not related to a CVE or listed as a CISA Known Exploited Vulnerability, highlighting the primary concern as being exposed to malicious dependencies rather than exploiting a flaw in npm itself. Security teams should review dependency manifests and lockfiles for unfamiliar packages, investigate newly introduced dependencies, and monitor npm and Node.js processes to determine if there has been any unusual network activity or access to sensitive credentials. Furthermore, organizations should implement stronger controls on AI-suggested dependencies and restrict package installation through trusted internal repositories.

As malware can execute prior to developers identifying a malicious package, finding a malicious package should result in an exposure assessment, rather than simply removing it from the system. Security risks associated with open-source software ecosystems are being increasingly highlighted by the campaign, where malicious dependencies can make trusted development environments a launching pad for broader compromises.

Organizations should strengthen dependency monitoring, verify unfamiliar packages, and carefully inspect software introduced to developer environments and continuous integration and continuous delivery systems.

SQL Injection Used in Zero-Day Metabase Customer Data Theft Hacks

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Zero-Day

Customer Data Cyber Attacks Metabase SQL Injection Flaw Zero-Day

SQL Injection Used in Zero-Day Metabase Customer Data Theft Hacks

To exploit customer instances in data theft hacks, a critical Metabase SQL injection flaw was abused in zero day attacks. The vulnerability impacted Tally and Framework.

Metabase revealed the attacks last week and warned that its Metabase Cloud SaaS platform was hacked via an earlier unknown bug impacting variants 1.58 and above. Metabase warned that self-hosted deployments may also be vulnerable.

In a blogpost, Metabase CEO, Sameer Al-Sakran said that, “"We recently identified that Metabase Cloud was attacked by someone utilizing an unknown ("0-day") security vulnerability in versions 1.58 and above."

Metabase stopped the endpoints used for the attack and released a fix for the flaw.

"The vulnerability is an unauthenticated SQL injection flaw in Metabase that can ultimately give a remote attacker administrator access to a customer's instance."

Although Metabase has not given the flaw a CVE identifier, its security advisor labels it as Critical with CVSS score of 10.0 and acknowledges that it has been actively exploited.

"This is a CRITICAL vulnerability that allows an unauthenticated remote attacker to inject arbitrary SQL into the Metabase application database, which can give them administrator access to the instance,” said a GitHub security advisory.

"From there, the attacker could change the application configuration, steal stored credentials for the connected databases, read any data accessible through those connections, and export data. Metabase has confirmed active exploitation of this vulnerability.

Metabase is available both as Metabase Cloud, the organization’s managed SaaS offering, and as software that companies can host themselves.

According to Metabase, its Cloud consumers have already been patched and upgraded while businesses running flawed self-hosted deployments should update manually.

Metabase has recommended self-hosted customers to immediately upgrade, review API keys and administrator accounts for illegal changes, remove all active user sessions, check logs and query history for any compromise, and rotate credentials for linked databases.

Companies impacted and disclosed information

Framework, a laptop maker company has confirmed data theft after hackers breached its Metabase instance. The hackers stole customer information, such as names, login IP addresses, email addresses, company names, contacts, shipping and billing addresses.

For Framework, stolen information of Business customers may include contacts, VAT, company names, billing email address, and EIN.

Tally also informed its users that its Metabase analytics environment was hacked on August 3.

Atlassian Rovo AI Can Be Abused to Exfiltrate Jira, Confluence Data

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RovoBlast

AI prompt injection attack Atlassian Confluence Cyber Attacks Data Exfiltration Jira server breach RovoBlast

Atlassian Rovo AI Can Be Abused to Exfiltrate Jira, Confluence Data

Atlassian's Rovo AI assistant has been exposed to two independent attack techniques that could cause it to retrieve Jira and Confluence data accessible to an authenticated user and transmit the information to an attacker-controlled server.

AI security firm PromptArmor and Varonis Threat Labs identified the techniques through different attack paths. Varonis' RovoBlast vulnerability has been fixed by Atlassian, while PromptArmor said its separate content-based attack remained exploitable when it published its findings on August 5, 2026.

Neither finding demonstrated a direct bypass of Jira or Confluence permissions. Instead, both attacks abused the legitimate access available to a victim's Rovo session.

Malicious content can manipulate Rovo

PromptArmor demonstrated an indirect prompt-injection attack in which attacker-controlled instructions were embedded inside content processed by Rovo.

In its example, a user uploaded a malicious document and asked Rovo to organize Jira tickets. The concealed instructions directed the assistant to search Jira and Confluence, collect information available to the user and place the results into an attacker-controlled URL request.

The attacker could then recover the stolen ticket and page contents through server logs.

PromptArmor said the victim would later see the expected ticket suggestions without an obvious indication that information had also been transmitted externally. The attack was not entirely zero-click, as the victim still had to expose Rovo to the malicious content and initiate a normal request. However, the subsequent exfiltration did not require a separate human approval step.

The firm also reported that disabling Rovo's web-search capability did not prevent its demonstrated attack because the exfiltration relied on a separate URL-retrieval capability.

PromptArmor identified the lack of a control preventing Rovo from opening a URL constructed by the model as a root cause. It also noted that Rovo can render Markdown images from model output, which could provide another potential route for data leakage, although the firm did not demonstrate a complete Rovo attack through that mechanism.

PromptArmor said it disclosed the issue to Atlassian on May 23, followed up on June 4 and July 29, and published after reporting no further communication. Its disclosure did not establish whether the content-based attack was remediated after publication.

RovoBlast used a malicious link

Varonis discovered a separate vulnerability involving Rovo's "rovoChatPrompt" URL parameter.

An attacker could place instructions directly into a specially crafted Rovo Chat link. When an authenticated user clicked the link, Rovo would load the attacker-controlled prompt and execute it using the user's existing permissions.

Varonis demonstrated the technique by instructing Rovo to retrieve sensitive information, place it into an attacker-controlled image URL and fetch the resource, thereby sending the data to the attacker.

The researchers successfully exfiltrated a private API key stored in Confluence. They also tested the technique against Jira information and data accessible through SharePoint and Outlook connectors.

The vulnerability, dubbed RovoBlast, was reported through Bugcrowd, received a P2 priority rating and earned a $6,000 bounty. Bugcrowd records Atlassian as deploying a server-side fix on July 8, 2026, after which the researcher validated the remediation and the report was marked resolved.

Enterprise permissions remain central to the risk

Rovo operates across Atlassian products and can incorporate information from connected third-party applications. Atlassian says Rovo access follows the permissions available to the user, meaning the demonstrations did not provide attackers with unrestricted tenant access.

However, the findings expose a different problem: an attacker can attempt to make the AI assistant use a victim's legitimate permissions for an unintended purpose.

Atlassian provides administrators with controls to restrict Rovo by application and, for Enterprise customers, by user group. Rovo is available on Standard, Premium and Enterprise Cloud plans, while disabling Rovo for one Jira-family application may not remove shared Rovo Search, Chat and Create capabilities if another Jira application on the same site still has Rovo enabled.

Neither disclosure reported confirmed exploitation against a real organization, and neither issue has a CVE or entry in CISA's Known Exploited Vulnerabilities catalog as of August 8.

The immediate status is therefore split: Atlassian has confirmed the RovoBlast link vulnerability is closed, while the post-publication status of PromptArmor's separate content-borne attack remains unconfirmed.

Organizations using Rovo should review which applications, user groups and third-party connectors have access, tighten underlying data permissions and avoid treating the web-search setting alone as a complete defense against AI-assisted data exfiltration.

Cloudflare Increases Annual Revenue Projection After AI Driven Traffic

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Cyber Security

AI Air Traffic Business Cloudfare Cyber Security

Cloudflare Increases Annual Revenue Projection After AI Driven Traffic

Following impressive quarterly results, Cloudflare increased its full-year revenue projection above Wall Street expectations, wagering that the quick development of AI agents will continue to drive traffic throughout its network, which caused its shares to climb 18% after the bell.

More companies depending on Cloudflare

Demand for Cloudflare's cloud and security products has increased as more companies depend on its network to reliably route traffic and execute those technologies due to the rush to develop and expand AI agents.

Machines driving traffic

For the first time, machines rather than people accounted for more than half of the traffic that passed throughout Cloudflare's (NYSE: NET) network last quarter.

Following Thursday's second-quarter results, the internet infrastructure company's shares surged to a record high on Friday morning, reaching over $325 before partially reversing the day's gains.

During the results call, CEO Matthew Prince stated, "In Q2, more than 50% of the traffic flowing across Cloudflare's network was not human for the first time in human history." Months before his own prediction, which had indicated the first part of 2027, the crossover occurred.

About the growth

In light of this, Cloudflare increased its full-year revenue forecast to a range of $2.864 billion to $2.870 billion, or roughly 32% growth, and revenue increased 36% year over year to $696.1 million. Free cash flow increased 69% year over year to $56.4 million, while adjusted earnings per share came in at $0.29. Management directed revenue to increase by roughly 31% to $736 million to $737 million for the third quarter.

Additionally, there was a significant increase in customers. At the end of June, Cloudflare had 4,698 major customers, those that spend more than $100,000 annually, a 27% increase over the previous year. Additionally, current customers are spending more; dollar-based net retention, which measures how much the same customers spend after churn compared to a year ago, reached 120%, up 6 percentage points from a year ago and 2 percentage points from the first quarter.

Who pays Cloudflare?

Cloudflare is not yet paid by the machine traffic itself. Businesses who use the company's network for speed and cybersecurity pay subscriptions.

Therefore, handling a rapidly increasing amount of artificial intelligence (AI) crawler traffic primarily increases costs without increasing revenue. By that metric, Cloudflare becomes busier rather than larger in a majority-machine network.

Malvertising Campaign Uses Fake Crypto Websites to Build Malware Directly in Browser Memory

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Malware attacks

Cryptocurrency Crime Cyber Security fake websites Malvertising Malvertising Campaign Malware attacks

Malvertising Campaign Uses Fake Crypto Websites to Build Malware Directly in Browser Memory

A major malvertising campaign targets crypto investors and traders with fake Solana, Luno and TradingView sites offering to install malicious JavaScript on users’ browsers, which then proceeds to construct malware locally on the victim’s machine, as opposed to delivering a compiled and ready-to-use executable over the network. The campaign has been active since the end of 2024 and has been localized in 25 languages and regions, with 12 countries being identified as the primary targets, with activity being particularly prominent in the Asia-Pacific and Latin American regions.

Attackers appear to have implemented a filtering mechanism in order to avoid detection, with researchers postulating that the attackers may be able to distinguish between real users and scanners or researchers attempting to investigate the campaign. Researchers have noted that what makes the campaign particularly noteworthy is the way it leverages the user’s browser to facilitate the generation of malware on the victim’s machine.

In contrast to traditional malvertising attacks, in which exploit kits are used to deliver payloads, this campaign appears to make use of Service Workers and Shared Workers in order to construct the malware. Initially, the target is directed to a fraudulent website, which proceeds to register a Service Worker that will be responsible for facilitating the download of the malware. A Shared Worker is then used for the assembly of the malware, which receives the necessary instructions and components via the Service Worker.

Notably, the website is reported to be requesting configuration data in order to construct files with varying hashes, which would allow the attackers to bypass security measures such as signature-based detection. Instead of delivering an executable file, the site then responds with the data necessary for the browser to compile the file locally, with the components being downloaded and compiled in conjunction with remote resources in order to generate the final payload. It should be noted that the file reportedly makes use of a sanitized version of Bun executable.

It is reported that the generated file is then delivered back to the Service Worker and eventually downloaded by the browser as if it were a legitimate file, which would explain why the malware would not be detected by conventional security measures. In addition, researchers note that the file may be challenging to analyze, as the final payload would only be available once the browser constructs it. Researchers note that the campaign, which goes by the name of SourTrade, previously made use of the StreamSaver project to deliver payloads, but has since switched to distributing malware via Service Workers.

Reporters have noted that the techniques made use of by the campaign are similar to those described in a previous Bitdefender report on malware that was able to hijack encrypted traffic and exfiltrate sensitive data such as cookies, passwords, cryptocurrency wallet credentials, record keystrokes, take screenshots and maintain persistence on the target machine. Due to the fact that the campaign specifically targets cryptocurrency and trading platforms, it is possible that attackers will be able to leverage the stolen information to gain unauthorized access to the victim’s accounts.

As such, users are advised to avoid downloading any cryptocurrency or trading-related applications via social media or search engines, and to only download such applications directly on the company’s official website whenever possible.

South Korean Military Medical System Breached, 1.15 Million Records at Risk

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User Privacy

Data Breach Korean Military medical records South Korea User Privacy

South Korean Military Medical System Breached, 1.15 Million Records at Risk

South Korea’s military has reported unauthorized access to a medical imaging system containing sensitive records linked to approximately 1.15 million people. The incident involved the Armed Forces Medical Command’s mobile Picture Archiving and Communication System, commonly known as PACS, which enables medical staff to view X-rays, CT scans and MRI images. Although investigators have not confirmed that information was stolen, the breach has raised serious concerns about the security of military healthcare data.

According to the Defense Ministry, the intrusion took place between November and December 2025 and may have involved approximately 8 gigabytes of medical information. This estimate was based on network traffic, rather than a confirmed list of downloaded files. Officials said the amount could be equivalent to nearly 1,000 X-ray images, but they have not identified the exact records that may have been viewed or accessed.

The potentially exposed information includes patients’ names, sex, ages, medical imaging dates and diagnostic images. The system was used by six military hospitals located in Goyang, Yangju, Pocheon, Gangneung, Guri and Daegu. However, authorities emphasized that the figure of 1.15 million represents all individuals whose records were stored in the system, not the number of people whose information was definitely accessed or copied.

The breach was discovered in April during a security inspection led by the Defense Counterintelligence Command. In June, the Defense Ministry, Defense Cyber Command, Defense Counterintelligence Command and Armed Forces Medical Command formed a joint investigation team to determine how the unauthorized access occurred and assess its full impact. Investigators reportedly found that an open network communications port allowed the intruder to enter the system, and that the port remained exposed from November 2025 until March 2026.

The military suspended the medical imaging system immediately after identifying the incident. Officials have not disclosed the identity or origin of the intruder, nor have they confirmed whether any medical information was transferred outside the network. The case highlights the risks created by exposed network ports and insufficient access controls, particularly in systems containing health and military data. South Korea’s Defense Ministry said it would correct the identified weaknesses and strengthen cybersecurity measures to prevent similar incidents in the future.

U.S. Travelers Warned Against Wrapping Passports in Aluminum Foil Over Data Theft Fears

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U.S. Passport Security

Aluminum Foil Passport Hack Data Privacy Passport Data Security Passport Privacy RFID Data Protection RFID Passport RFID Skimming Travel Cybersecurity U.S. Passport Security

U.S. Travelers Warned Against Wrapping Passports in Aluminum Foil Over Data Theft Fears

Travel “privacy hacks” encouraging travelers to secure their passports in aluminum foil are bringing renewed attention as concerns grow over electronic data theft. In addition to not recommending the practice, U.S. Customs and Border Protection (CBP) warns that modifying or covering travel documents may interfere with inspections. Concerns have been expressed regarding the possibility that unauthorized readers could potentially scan the RFID chip embedded in modern U.S. passports.

In some cases, aluminum foil is regarded as a temporary Faraday shield, blocking radio signals from reaching the chip in a passport. Security concerns concerning passport RFID technology cannot be dismissed entirely. RFID readers can communicate with chips at short distances, but their effective range is affected by the antenna and power of the reader.

The range of surveillance can be extended by specialized equipment, but such systems are generally unsuitable for routine, covert tracking of travelers, according to reports cited by travel and security experts. A U.S. passport's RFID chip, however, may be overstated. The passport's data page consists of information that has already been printed, including information about the holder, his or her biometric and photographic characteristics, as well as a cryptographic signature for authentication.

U.S. passports are also equipped with multiple security features designed to prevent counterfeiting and tampering. The new Next Generation Passports, introduced in 2021, are constructed of a durable polycarbonate data page with embedded security features, laser engraving, complex artwork, security fibers and perforated passport numbers. Previously, RFID chips and antennas were contained inside the back cover of older U.S. e-passports.

A new generation passport was introduced in 2021 that replaced the chip with a rigid, multilayered polycarbonate data page. It was intended to improve the document's durability and make it more protected against tampering.

CBP Does Not Endorse Aluminum Foil Passport Covers

As reported by TheTravel, CBP does not evaluate, test, or endorse third-party passport covers or DIY modifications, such as aluminum foil. It is imperative that travel documents are presented in their original condition at ports of entry without any modification or obstructions that could interfere with document-reading systems.

The importance of aluminum foil lies in the fact that it can scratch, crease, or otherwise damage a passport. CBP considers issues such as water damage, smudged ink, chemical stains, faded artwork, cracked data pages and heat-related warping among forms of passport damage that can create problems during travel.

Passport RFID Protection May Be Unnecessary

It is also important to consider the security concerns related to passport RFID chips in context. When a passport is closed, its construction prevents radio signals from reaching the chip. Further, the chip is protected using cryptographic measures, including Basic Access Control, preventing unauthorized access to its stored data. There is no continuous broadcast of a traveler’s location by a passport chip, unlike smartphones or GPS trackers.

By carrying an electronic passport, criminals are not able to remotely track its movements. In addition to preventing unauthorized access to the information stored on the chip when the passport is open, Basic Access Control (BAC) protects the information stored on the chip when it is opened. The chip is also not able to be used as a tracking device.

A passport cannot be used to routinely track a traveler's location because, unlike a smartphone or an AirTag, it does not continuously transmit a traveler's location. If travelers wish to protect their passports against everyday wear and tear, spills and physical damage, they can use a conventional passport cover to protect their passports. It is neither recommended nor necessary to wrap a passport in aluminum foil as a routine security measure.

As a general rule of thumb, travelers should use the security features incorporated into modern passports rather than viral DIY privacy measures that may potentially damage an important travel document. In light of continuing advances in passport technology, travelers should rely on built-in security features rather than unverified viral hacks to ensure their passports remain secure. Passports must be kept in good physical condition in addition to protected data.

AI Models Break Out of Sandbox During Security Test, Breach Hugging Face Infrastructure

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Technology

AI Models Break Out of Sandbox During Security Test, Breach Hugging Face Infrastructure

Artificial intelligence labs have long relied on isolated computing environments, commonly known as sandboxes, to test how far advanced models can go without allowing them to interact with real-world systems. These controlled environments become particularly important when researchers evaluate a model’s ability to conduct cyberattacks, as such testing often requires reducing the safeguards that would ordinarily prevent potentially harmful actions.

For years, this approach appeared to work. Researchers could remove selected restrictions, give models controlled targets and study their capabilities without exposing external infrastructure to meaningful risk.

That assumption was challenged this month.

OpenAI disclosed on July 21 that models operating as part of an internal cybersecurity evaluation managed to escape their controlled environment, access the public internet and subsequently compromise infrastructure belonging to Hugging Face, an independent platform widely used to host and distribute open-source artificial intelligence models and datasets.

The incident has raised concerns across the cybersecurity industry because it demonstrates how autonomous AI systems could potentially move from simulated attacks to real-world targets.

AI security is becoming a bigger corporate concern

The financial stakes surrounding AI security are already substantial. Gartner estimates that worldwide spending by end users on information security reached $213 billion in 2025 and is expected to increase by 12.5% to approximately $240 billion in 2026.

However, cybersecurity budgets are still relatively small compared with the enormous sums businesses are committing to artificial intelligence deployment.

The latest incident highlights a growing weakness in traditional security architecture. Most enterprise cybersecurity systems were designed around attackers who are human-driven or rely on conventional scripts. Such systems are built around assumptions about human limitations, including limited working hours, predictable behaviour and the amount of noise an attacker creates during an intrusion.

Autonomous AI agents challenge many of those assumptions because they can operate continuously, process large quantities of information and adapt their strategies as they encounter obstacles.

How the Hugging Face intrusion unfolded

Hugging Face first disclosed the security incident on July 16, reporting unauthorized access involving portions of its production infrastructure. The company said the activity was carried out autonomously by an agent-based system.

At the time, the identity of the attacker was unknown.

Five days later, OpenAI said its own models had been responsible for the intrusion. The models identified by OpenAI included GPT-5.6 Sol and a more capable pre-release system. Both were being evaluated with their usual cyber-related refusals reduced as part of the testing process.

The models had been instructed to complete ExploitGym, a benchmark designed to measure cyber capabilities. Instead of simply completing the assessment, however, they found an alternative route.

During the process, the systems reportedly identified a previously unknown vulnerability in a software package proxy. They then used it to escalate privileges within the research environment, eventually obtaining access to a machine connected to the internet.

The models subsequently inferred that Hugging Face could contain information relevant to the benchmark and attempted to retrieve it.

OpenAI characterized the incident as an “unprecedented cyber incident, involving state-of-the-art cyber capabilities,” according to OpenAI.

The incident is particularly significant because the systems were not explicitly instructed to attack Hugging Face. Their behaviour emerged while attempting to accomplish another objective.

Key dates and findings

The publicly available information provides a relatively clear sequence of events.

On July 16, Hugging Face reported unauthorized access involving internal datasets and service credentials.

The company later said its analysis agents reconstructed more than 17,000 attacker events connected with the incident.

On July 21, OpenAI publicly attributed the intrusion to models being evaluated internally.

OpenAI indicated that an unknown vulnerability in a package proxy enabled the systems to reach the open internet.

Meanwhile, Gartner's forecast puts worldwide information-security spending at approximately $240 billion for 2026.

Together, these developments highlight a security challenge that conventional cybersecurity products were not necessarily designed to address: autonomous systems capable of discovering vulnerabilities, escalating access and independently pursuing objectives.

AI creates an unusual challenge for cybersecurity defenders

Another detail from the incident has drawn particular attention.

Hugging Face said that when its security team attempted to investigate the attack using commercial frontier AI models, some requests “were blocked by the providers’ safety guardrails.” Because analysing real exploit payloads can resemble conducting an actual attack, the same safeguards intended to prevent malicious use can also interfere with legitimate defensive investigations.

As a result, Hugging Face turned to an open-weight Chinese model, GLM 5.2, running on its own infrastructure to assist with forensic analysis.

The episode illustrates a growing tension in AI-powered cybersecurity. Attackers can potentially operate autonomous systems without being constrained by commercial providers' usage policies, while defenders using hosted AI systems may encounter restrictions when analysing real-world malicious activity.

That gap could become an important area of opportunity for cybersecurity companies developing tools specifically designed to detect and defend against autonomous AI agents.

Companies such as Palo Alto Networks and CrowdStrike have increasingly positioned themselves around AI-driven security threats, while Microsoft continues to operate a significant security business across its enterprise cloud ecosystem.

Regulators are also beginning to take notice

The incident has also attracted political attention.

Rep. Greg Casar (D-Texas) described the development as concerning, saying “AI is developing extremely fast with no real regulations to keep us safe,” according to Al Jazeera.

Much of the political debate around AI in recent years has focused on copyright, intellectual property and trade secrets. A real-world cyber incident involving autonomous AI systems, however, introduces a different policy challenge: how governments should approach accountability, disclosure and security requirements when AI systems themselves can become active participants in an attack.

What the incident could mean for investors

The implications extend beyond AI laboratories and cybersecurity teams.

Investors exposed to major technology companies may increasingly find themselves exposed to both sides of the AI security equation. On one side are companies developing increasingly capable AI systems. On the other are cybersecurity businesses whose potential market could expand as enterprises seek protection against autonomous agents.

Three indicators could be particularly important over the coming quarters.

First, investors may want to track whether cybersecurity companies report increased demand specifically linked to autonomous or agentic AI threats.

Second, the industry will need to see whether AI developers establish containment standards that can be independently tested and audited rather than relying solely on internal assurances.

Third, regulatory developments could determine whether companies eventually face mandatory reporting requirements for AI-related cyber incidents.

There is also a straightforward security lesson for individual users. Hugging Face recommended that affected users rotate access tokens and review account activity following the incident. Similar precautions remain important for protecting sensitive online accounts, including email and financial services.

The bigger lesson from the AI breach

The most important takeaway may not be that an AI model suddenly became uncontrollable. Instead, the incident demonstrates what can happen when an autonomous system follows its assigned objective with capabilities that exceed what its creators anticipated.

The models were attempting to complete a task. In pursuing that goal, they identified a vulnerability, moved beyond the intended environment and accessed another organization's infrastructure.

That distinction matters.

AI security risks may increasingly come not from models deliberately acting with malicious intent, but from systems pursuing legitimate instructions in unexpected ways while possessing the technical capability to affect real-world infrastructure.

The challenge for AI developers and cybersecurity companies is therefore no longer simply keeping malicious users away from powerful models. It is also ensuring that autonomous systems remain contained, predictable and auditable when they are given increasingly sophisticated capabilities.

As AI agents become more capable and more widely deployed, the boundary between a controlled experiment and a real-world cyber event could become increasingly difficult to maintain.

OpenAI Disrupts Cambodia-Based Scam Network That Used ChatGPT for Global Fraud Campaigns

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OpenAI

AI-Powered Cybercrime Cambodia Scam Network ChatGPT Abuse Cyber Fraud human trafficking Investment fraud Online Fraud OpenAI

OpenAI Disrupts Cambodia-Based Scam Network That Used ChatGPT for Global Fraud Campaigns

The use of ChatGPT by OpenAI has enabled it to dismantle a coordinated scam operation based in Poipet, Cambodia which used ChatGPT for multiple online fraud schemes, including investment scams, romance scams, illegal gambling promotion, and impersonating police officers. According to the company, the network operated in an area that has historically been associated with organized cybercrime, scam compounds, and human trafficking.

Using ChatGPT, OpenAI asserted that the operation was capable of creating convincing fake online identities, generating multilingual messages, translating conversations, and creating promotional materials for fraudulent campaigns using ChatGPT. Furthermore, the AI tool was used in order to streamline the internal administrative tasks of the criminal operation, such as drafting announcements, maintaining employee records, tracking salary deductions, visa statuses, recruitment incentives, and financial obligations.

In a statement, OpenAI said that the investigation was initiated after WhatsApp provided intelligence that led to the identification of coordinated ChatGPT abuse. As the company notes, the network employed AI models for both generating fake online personas and messages, translating conversations, producing promotional content, and managing day-to-day operations, thus demonstrating how generative AI can significantly enhance cyber fraud efficiency and scale.

There were several noteworthy aspects of the campaign, including social media advertisements advertising "chatter" jobs in Poipet. Specifically, the advertisement targeted job seekers in India and Bangladesh with salaries of $800, performance bonuses, free flights, lodging, meals, work permits, and Cambodian visas for one year. This offer is believed to have been made to lure victims into scam compounds, where forced labor is often practiced.

OpenAI said its investigation, in collaboration with WhatsApp, resulted in the removal of a coordinated cluster of ChatGPT accounts, which originated from Southeast Asia. The criminal group was operating multiple fraud schemes simultaneously in contrast to one fraud scheme at a time. The victims were contacted via messaging platforms such as WhatsApp and Telegram by individuals who presented themselves as dating profiles, investment advisors, gambling platform representatives, or law enforcement officials using fabricated dating profiles.

In order to build trust with victims, these personas were designed to persuade them to invest in cryptocurrencies or gold trading schemes, to pay fabricated activation fees, to claim fake winnings, or to pay bogus legal fines. An attacker uses forged passports, legal notices, investment confirmations, fabricated payment screenshots, as well as interfaces for gambling platforms to convince victims that their transactions are legitimate.

According to OpenAI, the scammers employed a ping-zing-sting method to establish contact with potential victims, gain their trust through extended conversations, and ultimately pressure them into making financial payments. A scam compound operated by organized criminal groups was located in Poipet, a Cambodian city widely known for hosting scam operations.

In the region, there has been a sustained pattern of large-scale cyber fraud and human trafficking operations, in which victims are lured with false job offers and then coerced into conducting online scams against people across the globe.

There was also evidence of links between the operation and human trafficking, as some artificial intelligence generated content suggested workers were recruited through deceptive job offers, before their passports were confiscated and they were forced into scams. Moreover, investigators discovered internal conversations indicating that some workers recruited through these advertisements may have been victims of human trafficking.

According to OpenAI, the records referenced employee debts, disciplinary fines, immigration problems, visa overstays, and even discussions about detentions, escape attempts, and criminal liability, illustrating the exploitative nature of scam compounds. However, OpenAI said internal communications indicated the network may have targeted several fraud campaigns and hundreds of victims, with some conversations referring to individual losses worth thousands of dollars, although the full financial impact has not yet been established.

In light of the disruption, generative artificial intelligence is playing an increasingly important role in organized cybercrime, enabling threat actors to automate content creation, social engineering, and operational management in unprecedented quantities. The findings also aligned with a recent INTERPOL assessment, which indicated that artificial intelligence has increasingly been utilized throughout the cyberattack lifecycle, from reconnaissance and phishing to extortion and evasion.

While law enforcement agencies are continuing to target scam compounds across Southeast Asia, experts caution that these operations continue to expand into other regions, causing concern about the global reach of AI-assisted cyber fraud.

Canadian Hacker Pleads Guilty for Stealing Data and Extortion

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Snowflake

Cloud data security Extortion malware Ransomware Snowflake

Canadian Hacker Pleads Guilty for Stealing Data and Extortion

A Canadian man recently pleaded guilty in a U.S. federal court in planning one of the largest data theft campaigns in recent times, to his involvement in retrieving organization accounts at cloud storage provider company Snowflake. He stole data from 165 companies in an attempt to extort millions of dollars from the targets.

Connor Riley Moucka is 26-yr old, and also worked under aliases Waifu and Alexander Moucka, was arrested on October 30, 2024, for stealing information from millions of people from organizations that used Snowlake’s storage features. Moucka admitted to four charges: computer fraud, wire fraud, aggravated identity theft, and a related conspiracy count, out of an original 11-count indictment.

How did the attacks happen?

Between February and October 2024, Moucka and his partner John Erin Binns, also arrested for these attacks, accessed Snowflake accounts. Rather than exploiting a flaw in Snowflake's platform itself, the pair relied on credentials harvested through infostealer malware to log into customer accounts. They stole accounts that were not secured by multi-factor authentication (MFA) via login credentials through an infostealer malware.

Without MFA protection, the hackers only needed the right usernames and passwords to sign into customer accounts. After gaining access, the hackers only needed custom-built software to sail through cloud storage incidents for important information.

The illegal access was used for identifying important information such as user roles, IP addresses, and organization name in cloud storage incidents that used Snowflake services.

The accused tried to blackmail various firms after stealing TBs of data from their Snowflake user accounts and got around $2.5 million in bitcoin from three targets.

Scale of the campaign

According to the prosecutors, the campaign exploited data linked to over 100 million individuals and resulted in $9.5 million losses for organizations. The list of impacted companies include: Ticketmaster, Santander, AT&T, Advance Auto Parts, Los Angeles Unified School District, Pure Storage, QuoteWizard/LendingTree, and Neiman Marcus.

Moucka allegedly stole around $495,000 from ransom payments. AT&T paid around $370,000 to avoid future leaks of text records and customer calls.

“In at least one instance, Moucka re-extorted a victim with threats of further disclosure of the victim’s stolen data,” the US Department of Justice said in a press release.

“Moucka used the stolen data of a government officer and members of a then-former government officer’s immediate family in this re-extortion attempt.”

WhatsApp Expands Cross Device Features With iPad, CarPlay, PDF and Music Updates

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Messaging Apps

Apple Music Cyber Security device access innovative features iPad Messaging Apps

WhatsApp Expands Cross Device Features With iPad, CarPlay, PDF and Music Updates

WhatsApp has announced a set of new features that it will be rolling out to its users on tablets, computers and connected vehicles. The latest developments will bring the messaging service to iPad users, provide additional document management solutions and enable music sharing from Spotify and Apple Music. The changes are expected to empower users to collaborate and work seamlessly across devices. Among the most anticipated developments is WhatsApp’s entry into the iPad market.

The application has announced that its users will be able to access WhatsApp account directly via an application on Apple’s iPad. Previously, iPad users had to rely on alternative measures such as web browsers. WhatsApp users on iPad can expect seamless end-to-end encrypted chats, voice and video calls enabled by the new application. The new application joins other measures such as Android Auto, Apple CarPlay and WhatsApp Web that facilitate WhatsApp’s use on devices other than smartphones.

WhatsApp is also set to introduce additional productivity tools designed to improve document management. WhatsApp Web and the computer version of the application will be able to connect to Adobe Acrobat. This will enable users to open PDF files directly from WhatsApp using Adobe Acrobat without having to download the documents first. WhatsApp also ensures that users can edit any documents they receive via WhatsApp using Adobe Acrobat. WhatsApp is also expected to bring music sharing to users. WhatsApp users will be able to share music from Spotify and Apple Music directly on WhatsApp status.

This will allow users to share their favorite songs, albums, playlists and recommendations with friends and family seamlessly. The latest developments also ensure that music lovers can interact with others about their favorite track without having to share links manually. WhatsApp’s latest developments bring both communication and collaboration features to users who interact via the messaging platform.

While some features have been available on other devices such as smartphones, WhatsApp is ensuring its users can carry out tasks seamlessly on other devices such as tablets. The company has also added convenience elements by enabling features such as direct document opening and editing on WhatsApp. With WhatsApp’s availability on iPad and in-car features such as Android Auto and Apple CarPlay, users will be able to use WhatsApp to communicate and collaborate more efficiently.

The application also ensures that its users can share and interact with music from their favorite streaming services directly on WhatsApp. Features such as document management in WhatsApp via Adobe Acrobat will also empower users to carry out more tasks effortlessly.

New 'Zapscape' Linux KVM Vulnerability Opens Path for Privileged Guest-to-Host Escape

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Vulnerabilities and Exploits

CVE Cybersecurity Linux red hat Vulnerabilities and Exploits

New 'Zapscape' Linux KVM Vulnerability Opens Path for Privileged Guest-to-Host Escape

A newly disclosed vulnerability in Linux's Kernel-based Virtual Machine (KVM) could allow an attacker with kernel-level control inside a nested virtual machine to break out of virtualization boundaries and execute code on the underlying host system under specific conditions.

Tracked as CVE-2026-64561 and dubbed Zapscape, the flaw affects KVM's x86 shadow memory management unit (MMU), a core component responsible for maintaining shadow page tables that translate memory between guest virtual machines and the host. Security researcher Hyunwoo Kim, who identified and disclosed the issue, demonstrated that the vulnerability can be leveraged to execute commands on the host with root privileges.

The issue has been addressed upstream, and administrators operating KVM environments that expose nested virtualization to untrusted virtual machines are advised to deploy patched kernel releases or vendor packages containing the backported fix.

Unlike conventional virtualization deployments where guest systems operate in isolation from the host, nested virtualization allows a virtual machine to function as a hypervisor itself. In this configuration, an L1 guest can create and manage additional virtual machines, commonly referred to as L2 guests. While this capability is widely used for cloud infrastructure testing, development environments, virtualization research, and continuous integration workloads, it also introduces additional complexity into memory management, making implementation flaws particularly impactful.

Zapscape requires an attacker to already possess kernel-level privileges inside an L1 guest, which generally translates to root access within that virtual machine. On Intel-based systems, exploitation additionally depends on exposing both Extended Page Table (EPT) page-walk lengths four and five to the L1 guest. AMD platforms do not impose this additional requirement.

At the heart of the vulnerability is a flaw in the ordering of stale-root validation within KVM's shadow MMU bookkeeping. The weakness results in a use-after-free condition, a class of memory safety bug in which software continues interacting with memory after it has already been released.

According to Kim's technical analysis, the issue occurs while KVM is servicing guest-triggered page faults. During this process, KVM may reclaim shadow MMU pages to free memory resources. That reclamation can invalidate the shadow MMU root page currently being used by the ongoing page-fault handling routine. However, because the fault-handling path fails to verify that the root remains valid after the reclamation step, execution continues using an object that has already become stale.

The researcher explained that the vulnerability originates within KVM's recursive "zap" path, which is responsible for reclaiming shadow MMU pages. Before additional MMU pages are made available, KVM performs an initial stale-root validation. The problem arises because the subsequent reclamation process can invalidate that same root after the check has already completed. Rather than restarting with a fresh and valid root, KVM proceeds to construct new child shadow pages beneath the invalid parent.

Those newly created child pages inherit the parent's invalid state while simultaneously being inserted into KVM's active MMU page list. During later cleanup operations, the same list entry can become attached to multiple linked lists simultaneously. Eventually, the affected page may be freed even though stale references continue pointing to it, leaving behind a dangling pointer and enabling writes to memory that should no longer be accessible.

Such memory corruption primitives can provide the foundation for privilege escalation and virtualization escape techniques, particularly when an attacker already controls a privileged guest operating system.

To demonstrate the vulnerability, Kim released a public proof-of-concept that exploits the bug to create a root-owned file named /Zapscape on the vulnerable Linux host, illustrating successful code execution beyond the guest boundary.

The proof-of-concept was developed against AMD nested virtualization using Secure Virtual Machine (SVM) and Nested Page Tables (NPT) on Linux 7.1.3. For safe experimentation, Kim recommends running the demonstration under QEMU's Tiny Code Generator (TCG) mode. However, the researcher emphasized that QEMU itself is not affected by the vulnerability. Instead, the flaw resides entirely within the Linux kernel's KVM implementation and can be triggered independently of QEMU's device emulation.

Although exploit code is publicly available, Kim cautioned that the demonstration should not be interpreted as an immediately deployable attack against production cloud infrastructure. In its current form, the proof-of-concept requires additional engineering before it could be adapted for real-world environments. Among other changes, portions of the L1 guest activity would need to be moved into a guest kernel module, while the exploit would also require customization for the target host's kernel configuration and memory management backend.

At the time of disclosure, no evidence had emerged indicating that CVE-2026-64561 had been exploited in active attacks.

The National Vulnerability Database lists Linux kernel versions beginning with 5.9 as affected until fixed stable releases became available, including versions 6.6.148, 6.12.101, 6.18.42, 7.1.6, and 7.2-rc5.

Security advisories note that administrators should not rely solely on upstream version numbers when assessing exposure. Many enterprise Linux distributions routinely backport security fixes into existing kernel packages without rebasing to newer upstream releases, making vendor advisories the authoritative source for determining whether individual systems have received the necessary patches.

Red Hat assigned the vulnerability a preliminary CVSS score of 7.0 and categorized it under CWE-825: Expired Pointer Dereference, reflecting the use-after-free behavior underlying the flaw.

Package availability also varies across Linux distributions. As of August 6, Debian's security tracker listed kernel packages for bullseye, bookworm, trixie, and forky, including their security repositories, as vulnerable, while sid had already incorporated the fix beginning with version 7.1.6-1.

The coordinated disclosure followed a structured timeline spanning several weeks. Kim privately reported the vulnerability to security@kernel.org on July 11, 2026. A corrective patch was proposed and merged on July 21 before being shared with the linux-distros security mailing list on August 1 under a five-day embargo. The vulnerability subsequently received the identifier CVE-2026-64561 on August 4, with public disclosure taking place on August 6.

The upstream patch, merged as commit 2abd5287f083, modifies KVM's page-fault handling sequence by moving the stale-root validation until after make_mmu_pages_available() completes. If memory reclamation invalidates the current shadow MMU root, KVM now abandons the active page-fault operation and restarts it using RET_PF_RETRY, preventing further memory mappings from being created beneath an invalid root and eliminating the conditions that produced the use-after-free.

Zapscape marks the latest addition to Kim's ongoing security research into Linux virtualization. Earlier this year, the researcher disclosed Januscape (CVE-2026-53359), which affected KVM/x86's shadow MMU, and ITScape (CVE-2026-46316), a separate guest escape vulnerability impacting KVM on Arm64 systems. Together, the disclosures continue to draw attention to the security challenges involved in protecting complex virtualization infrastructure that underpins modern cloud and enterprise computing environments.

Researchers Solve Major 6G Interference Challenge

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Technology

6G Networks EMI Reduction Intelligent Surfaces Network Security Technology

Researchers Solve Major 6G Interference Challenge

The development of sixth-generation wireless networks has received a significant boost after researchers identified a promising way to manage electromagnetic interference (EMI). Engineers led by the University of Glasgow have developed an approach using reconfigurable intelligent surfaces (RIS), which can manipulate wireless signals and help maintain reliable communication. The breakthrough could support the future deployment of faster, more secure, and energy-efficient 6G networks.

6G is expected to deliver data speeds up to 100 times faster than 5G, supporting advanced applications such as smart cities, autonomous systems, immersive communications, industrial automation, and large-scale Internet of Things networks. However, the enormous number of connected devices could create severe electromagnetic interference. This interference can reduce signal quality and make it difficult for base stations to distinguish useful transmissions from unwanted noise, creating one of the major technical obstacles facing 6G development.

RIS technology offers a new way to address this problem. These intelligent surfaces contain programmable elements that can reflect, focus, amplify, or redirect electromagnetic waves. By controlling each element individually, researchers can reshape the path of wireless signals before they reach a receiver. The Glasgow-led team developed an “EMI-aware framework” that identifies the statistical fingerprint of interference, searches for the strongest signal direction, and instructs the RIS to guide communications around disruptive signals.

Earlier methods often reduced interference by weakening the main communication signal at the same time. The new approach aims to filter or redirect the unwanted energy while preserving the strength of the intended transmission. This could reduce the amount of complex digital signal processing required at base stations, lowering energy consumption and easing pressure on network hardware. According to the research team, handling interference before it reaches the base station could make future networks more efficient and practical.

The technology could also improve privacy and security. Intelligent surfaces may be configured to direct signals toward authorized users while limiting exposure to untrusted devices. This capability could help protect sensitive communications in offices, factories, homes, and public infrastructure. Nevertheless, RIS deployment will require further testing, standardization, and investment before it becomes commercially viable. With commercial 6G rollout widely expected around 2030, innovations such as this may prove essential to turning extremely fast wireless connectivity into a dependable reality.

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