Google dismantled a 1.3 million-device botnet allegedly built by Android TV box maker Videostrong to enable ad fraud and proxy abuse. Google and its partners dismantled a backdoor called XCPE that had enrolled more than 1.3 million set-top boxes in a botnet. The result of the investigation into the malware operation is the striking part: Videostrong Technology Co., an Android device maker, built and ran the botnet for money. Google says it is highly confident that Videostrong deliberately created, spread and operated the backdoor. The company reportedly sold access to criminal groups and installed their malware on infected devices. The malware was used for ad fraud, secretly added devices to residential proxy networks and installed other malicious software. Google says this was not the work of a rogue employee or a simple coding mistake. The backdoor was found in many device models and brands over several years. Its operation involved dedicated infrastructure and regularly changing configurations. “We assess with high confidence that the backdoor and botnet were intentionally developed, deployed, and operated for financial gain by Videostrong Technology Co., an Android Original Equipment Manufacturer (OEM) and Original Design Manufacturer (ODM).” Google states. “Videostrong monetized the backdoor by selling access to criminal affiliates and loading those affiliates’ malware modules onto infected devices. “ Google has now cut all ties with Videostrong. The company is banned from making devices with pre-installed Google apps. The ban also covers any future subsidiaries or business partners, and Videostrong can no longer supply software to other certified device makers. Videostrong got around Google’s compatibility and security tests with code obfuscation. The malicious code loaded after a device’s first boot, which the tests didn’t catch. Google has changed its review process and is improving how it checks firmware on certified Android TV devices. Google also took legal action against the domains and servers Videostrong used to control the botnet, and against the control domains of over a dozen malware families loaded through the backdoor. Those affiliates spread their modules through other channels too, so Google expects the takedown to cut access to at least 10 million more compromised devices. Japan’s National Police Agency, Lumen, HUMAN Security, Plume, Synthient and TrendAI worked on the operation. The malware has three stages. The primary backdoor, x.cpe (called com.oemservice in some builds), is preloaded in the firmware and runs with system privileges. If a user uninstalls it, it reinstalls itself from the /oem/ partition at the next reboot. It handles communication with the control server and passes work to a loader called com.abc.nexus, which carries its own anti-analysis tricks and sets up the money-making modules. These modules are supplied by other criminals working as affiliates. They can arrive as programs built into the backdoor, software packages added to its loader, or extra apps downloaded later. Many turn the device into a residential proxy, allowing other people to use the victim’s home internet connection to hide their online activity. Others commit ad fraud or install additional backdoors. In other words, a set-top box becomes a proxy server without its owner’s knowledge. The backdoor uses two steps to control infected devices. First, the box sends an HTTP request to download settings, location data and network information. It then maintains a live connection through MQTT, a lightweight messaging protocol, to receive commands from the operators. Google found that all analyzed samples used the same MQTT server to communicate with infected devices. “Additional monetization modules as well as various shell scripts and legitimate applications are hosted remotely and downloaded by infected devices upon command from the operator via the MQTT broker.” continues the report. “A significant majority of these files are hosted as Github releases on operator-owned Github pages. Other files are hosted on operator-controlled servers and file hosting sites.” Through this connection, attackers could secretly install apps, run commands and scripts, take screenshots, record keystrokes and map the victim’s network. They could also disable Google Play Protect’s app verification to install software without the user’s knowledge. Google observed operators taking screenshots, recording keystrokes, collecting account and device information, stealing app lists and system logs, and opening remote command-line sessions. However, most of their activity involved installing, removing and managing malware modules. The malicious files came from several sources. The attackers mainly used GitHub releases hosted on their own accounts, the Filemail file-sharing service and two servers under their control. Network traffic analysis also suggests that the operators managed the command infrastructure through remote interfaces and an EMQX web console, connecting from IP addresses outside the infected device network. Most infected devices are Android TV set-top boxes, but Google also found telehealth devices, karaoke machines and digital signage. One device can run several modules at once, up to three residential proxy kits. That shows Videostrong wants to squeeze every infected device as hard as it can. The proxy and bandwidth-sharing kits named in the report include Linkfog, AppSalt, GaGaNode, BWM, Traffmonetizer, EarnFM and NetNut. Some of those kits enroll devices without asking. AppSalt’s SDK, owned by Honeygain, calls an opt-in function without showing any consent screen, and it stops running if the app came from the official Google Play Store. Ad-fraud modules such as Fission and HiddenView fire off fake ad impressions in the background, and HiddenView also uses hidden browser windows to simulate clicks and scrolling. The configuration shows a well-run operation. MQTT messages carry resource limits for each module, download links per processor type, and priority weights. Devices are assigned to one of six timezone-based pools on ott.szbboys[.]com. Devices report their bandwidth use and alarms back, so the modules stay within set limits. Google says the underlying market is resilient. Backdoor operators, ad-fraud rings and residential proxy providers work as an interconnected supply chain, and when one part gets disrupted they quickly switch to new loaders or rival kits. Lasting change, it says, needs accountability across hardware makers, the residential proxy industry and the broader technology sector. Google wants retailers and distributors to require independent security audits from device manufacturers and to delist any implicated in supply-chain abuse. It says proxy providers’ claims of ethical sourcing need transparent, auditable proof of user consent, and that in its analysis these providers asked for consent only when platform policy forced them to. Silent opt-in remains the most common way devices become exit nodes. For consumers, Google advises caution with apps that pay you for “unused bandwidth” or “sharing your internet”, which are a main way illicit proxy networks grow. Stick to app stores you trust, review permissions for third-party VPNs and proxies, and keep Google Play Protect on. Buy connected devices like set-top boxes only from reputable manufacturers, and check the partner list on Google’s Android TV website. Google also urges mobile platforms, ISPs, online marketplaces and other tech platforms to keep sharing intelligence. “A device manufacturer intentionally infecting their users with malware is an unacceptable breach of trust. By turning everyday hardware into persistent beachheads for criminal affiliates, Videostrong prioritized illicit post-sale recurring revenue over the safety and privacy of its users.” concludes the report. “Downstream hardware brands, white-label resellers, telecommunications providers, and online e-commerce marketplaces also share responsibility for closing this vector.” Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, newsletter)
NIS2 Article 20 makes management bodies answerable for the access controls they approve, and boards are starting to ask for proof that those controls work. NIS2 board accountability gives directors a more direct role in cybersecurity. Under Article 20, the management bodies of essential and important entities must approve the cybersecurity risk-management measures required by the directive, oversee their implementation, and can be held liable for infringements, subject to national law. That obligation is live across most of the EU, with four member states going to the Court of Justice in July for failing to notify full transposition. Access control is one of the required measures. Directors are not expected to decide who gets administrator rights or review individual user accounts. They do, however, need to know that access is being controlled, that someone has responsibility for managing the risk, and that problems are being addressed. An estimated 160,000 entities fall within the scope of NIS2 across the EU. Approval is only part of the job Article 20 requires management bodies to both approve cybersecurity risk-management measures and oversee their implementation. It also requires the members of those bodies to undergo cybersecurity training, and to offer comparable training to employees on a regular basis. The measures themselves are set out in Article 21. They include access control policies and asset management, along with the use of multi-factor authentication or continuous authentication solutions where appropriate. Many organizations have traditionally left these decisions to security and IT teams. Under NIS2, the board still needs to know whether the measures it approved are being implemented. Day-to-day responsibility can remain with the CISO and IT teams. The difficulty comes when the person responsible for a risk does not control the budget, systems, or people needed to address it. Greece’s implementation goes further in defining who carries that responsibility. Its NIS2 law requires essential and important entities to appoint a suitably qualified member of their organization as an Information and Communication Systems Security Officer. The officer coordinates compliance, must have the resources needed to do the job, and operates independently of the company’s data protection officer. Access problems also need to reach the board in terms that it can act on. If an MFA rollout has failed or administrators have more access than they need, the board needs to understand the risk of leaving it unresolved. The CISO may be responsible for the risk without controlling the budget or teams needed to fix it. The board needs evidence Board reports often show what the access control policy requires, rather than whether it is being followed. For example, a company policy will likely require MFA and the removal of accounts when employees leave. However, the board also needs to know about the exceptions, including old accounts that remain active, excessive privileges, MFA exemptions that have never been reviewed, and suppliers whose access has outlasted their contracts. The board needs information about how the controls are working in practice. In a NIS2 access management report from European password and secrets manager Passwork, regulators from two national cybersecurity authorities and independent security leaders describe boards that have absorbed the liability change and now ask for proof that controls work, where they once accepted a summary of the policy. Organizations should be able to show who can access critical systems, why that access was granted, who approved it, how long it is valid, and when it was changed or revoked. The board needs to know whether that evidence exists and what it says about material access risk. Personal liability raises the stakes Implementation is still catching up in parts of Europe. In July 2026, the European Commission referred Ireland, Spain, France, and the Netherlands to the Court of Justice of the European Union for failing to notify full transposition of NIS2 into national law. The Commission also asked the Court to impose financial sanctions. For organizations in countries where NIS2 has been transposed, regulators have significant enforcement powers. For essential entities, member states must set a maximum fine of at least €10,000,000 or 2% of the global annual turnover, whichever is higher. Important entities are subject to a lower maximum threshold, of at least €7,000,000 or 1.4% of their global annual turnover, in a similar capacity. Article 32 also allows competent authorities, in specific circumstances, to seek the temporary prohibition of someone at CEO or legal representative level from exercising managerial functions in an essential entity. This can happen where enforcement action has failed to produce the required response. It is not an automatic consequence of a cyber incident. Article 20 separately requires member states to ensure that management bodies can be held liable for infringements of Article 21, subject to the applicable rules under national law. Approving the policy is not the end of the board’s involvement. It also needs information on whether the policy is being followed and what is happening with known problems. Verizon’s 2026 Data Breach Investigations Report found credential abuse somewhere in the chain of 39% of breaches, more than any other vector. Stolen credentials also circulate at scale, as the exposed database of 24 billion credential records reported in June showed. Directors should expect an answer on which accounts and credentials reach critical systems, who is responsible for them, and whether that access is being controlled. Give access risk an owner with authority CISOs briefing their boards should be able to say who owns access-control risk and whether that person has the authority to address it. The board also needs evidence of what is happening. When an access problem is identified, someone needs to be responsible for getting it fixed. That might mean removing unnecessary privileges or dealing with an MFA exception that has remained in place. If the fix depends on another team’s budget or resources, the board needs to know. Board reporting should show whether the controls it approved are working, flag significant exceptions that remain unresolved, and who is accountable for closing them. Author the author: Kirsten Doyle has spent 27 years writing about technology and has covered the industry through some of its most significant shifts. Her focus areas include cybersecurity, cloud, channel, enterprise IT, and data centre operations. She works across many formats: news, features, white papers, eBooks, and thought leadership. Kirsten has many years of experience in journalism and editing for both print and digital media, and has supported plenty of go-to-market and PR programmes with technically grounded writing that holds up to scrutiny. She is also a regular writer at Bora. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, NIS2)
Customers of the mSecure password manager are being urged to act now to protect the confidential information they store in it, possibly by changing passwords, resetting two-factor authentication (2FA), and removing passkeys. The warning came in an email sent on November 3 in the name of developer mSeven Software. It says the company recently learned of suspicious activity linked to the app but
Barracuda has disclosed details of two vulnerabilities affecting its products that, if chained together, could allow an attacker to bypass authorization controls and gain root access to a susceptible device. The vulnerabilities, a pre-authentication authorization bypass vulnerability and a command injection vulnerability, have been assigned the CVE identifiers CVE-2026-116606 (CVSS score: 9.3)
Google on Monday warned that threat actors are hijacking enterprise access to Large Language Models (LLMs) to fraudulently leverage expensive computing resources and AI services. The tactic is called LLMjacking, a form of resource hijacking adapted for the LLM era, where an attacker obtains an API key through phishing, source code leaks, misconfigured environments, or exposed client-side code
A maximum-severity security flaw impacting Siemens SIMATIC IoT2050 Advanced devices has come under active exploitation, VulnCheck has revealed. The vulnerability, tracked as CVE-2026-58115 (CVSS score: 10.0), is a case of missing authentication for a critical function that could be exploited by an unauthenticated remote attacker to run arbitrary code. "SIMATIC IoT2050 Advanced devices running
Threat actors are attempting to exploit an unpatched maximum-severity security vulnerability in the CryptoPayment Gateway WordPress plugin, according to findings from Defused Cyber. The vulnerability in question is CVE-2026-81648, which carries a CVSS score of 10.0. Successful exploitation of the flaw could permit unauthenticated users to delete arbitrary files on the server and extract
Chinese hackers used ARTEX, an open-source, multi-agent AI penetration-testing framework, in attacks against more than 200 organizations across 14 countries. The operation began on October 17 and targeted government ministries, telecommunications providers, and organizations in the pharmaceutical, semiconductor, defense, nuclear, and financial sectors. The threat actor compromised at least nine organizations and carried out password spraying attacks and credential scanning activity against at least 12 other high-value targets. According to researchers at CrowdStrike, the "campaign marks an escalation in China-nexus use of AI agents, from single intrusions to multiple simultaneous engagements directed by a human operator." Confirmed victims include telecommunications providers in the United States and Belgium, government organizations in Greece, the Middle East, and Latin America, and pharmaceutical firms in the U.S.
VOLTA is an AI-powered infostealer that steals personal data, then uses LLMs to assess victims’ value and rank targets for attackers. Cisco Talos has analyzed a new Windows infostealer called VOLTA, which calls itself VOLTA-AUTODOXER. It steals the usual data, then hands the loot to a large language model that ranks what the victim is worth. Ryan Fetterman laid it out in a Talos report, after the malware turned up through the CAIRN research effort. “There is a new idea in the cybercrime world — cast a wide net, steal everything, and let AI sort out the specifics. A new malware self-named “VOLTA-AUTODOXER,” surfaced through the CAIRN research effort, is a self-deleting Windows infostealer that augments its post-theft workflow with an LLM-powered victim-profiling stage.” reads the report published by Talos. The malware deletes itself after running and does not use servers controlled by the attacker. Instead, it uses third-party systems to carry out its activities. The malicious code supports data-stealing features are advanced. It collects browser passwords, cookies and saved payment card details from Chromium browsers, as well as data from Firefox, Thunderbird and Outlook. It also steals Slack workspace information and login sessions from Discord, Telegram, Steam, Battle.net and Roblox. The malware also collects Microsoft OAuth tokens, SSH keys, cloud service credentials, screenshots and all saved Wi-Fi passwords. For crypto wallets, it tries to crack the wallet password directly on the infected device and saves the results in its report. To steal some browser tokens, it must bypass Chrome’s App-Bound Encryption. But VOLTA goes further. It also builds a detailed profile of the victim. This includes their location and home address, employer and company domain, estimated year of birth, the last four digits of payment cards, Slack workspaces and information about who created documents. It also looks for signs of iPhone backups and checks the current value of the victim’s Roblox account. “After harvesting the standard stealer haul, including browser passwords; cookies; payment cards; cryptocurrency wallet seed phrases; Discord, Telegram, Steam, and Roblox sessions; Microsoft OAuth tokens; SSH and cloud-provider keys; Wi-Fi profiles; and screenshots, VOLTA builds a structured evidence bundle about the person behind the machine.” states the report. It uses the victim’s own logged-in sessions to fill the gaps. It searches Gmail for receipts from Amazon, DoorDash, Uber Eats, Grubhub, Walmart and PayPal to confirm a home address, pulls order histories from Uber Eats and DoorDash, and adds detail to the victim’s Discord profile. Even a takeout history can now count as evidence. The bundle goes to OpenRouter, a routing service for AI models, with a system prompt that tells the model to act as a forensic intelligence analyst drafting a target assessment. “The required output includes a section titled “WHAT THEY’RE WORTH” with valuables ranked by monetization with a low/medium/high tier, and a section on “THEIR OPSEC” containing an assessment of the victim’s security posture and password hygiene.” states the report. “The model is the operator’s triage analyst; it turns a raw credential log into a prioritized and citation-backed dossier of the victim and their monetizable assets.” It also needs a section called “THEIR OPSEC”, rating the victim’s security habits and password hygiene. In short, it’s a performance review for the person it just robbed. The prompt asks for something agents do well: connecting scattered facts. It pushes the model to link names, addresses or universities to patterns in the victim’s passwords. The model isn’t hunting for new data, only stretching what the malware already took. The operator wants a short, blunt assessment with a trail of citations. By default VOLTA calls Anthropic’s Claude Opus 4.6. If the model refuses, which VOLTA spots by scanning replies for phrases like “I can’t” or “I’m not able”, it moves on to Moonshot AI’s Kimi K2 and then Google’s Gemini 2.5 Flash. A low temperature setting of 0.2 keeps the output consistent. The requests are hand-built JSON with no software kit, and the malware still runs without the AI stage if no API key is present. Talos sees the fallback system as evidence that the malware’s author expected security protections and designed ways to bypass them. The AI analysis runs directly on the victim’s computer, using their own internet connection, before any data is sent out. The malware creates a file called Identity_Report.txt, receives the AI’s response in AI_Analysis.txt, and sends both files together in a ZIP archive called volta_dox.zip. The stolen data can be sent to the attacker in up to three stages. The first archive, volta_log.zip, contains the information collected by the malware. The second, volta_dox.zip, contains the AI analysis. A third archive, volta_doxnet.zip, is created if the malware finds additional network information. The attacker receives everything through a Telegram channel. The malware also has six configurable fields that can be changed when it is built. This suggests that its author may offer a builder service, allowing customers to create their own customised versions. The credentials stored in these fields are encrypted, but the encryption is weak because the key is stored inside the malware itself. Anyone who analyses the file can recover them. If VOLTA is sold as a commercial product, its AI feature could allow even inexperienced criminals to identify valuable victims and receive detailed, ranked profiles directly through Telegram. For defense, Talos suggests an application control policy that restricts which processes can launch Chrome with the –headless flag, which would block the App-Bound Encryption bypass. At minimum, alert when Chrome starts with –headless from any process outside a known developer set. Storing credentials in hardware-backed stores also helps. If you’re compromised, the main program may have deleted itself, but try to keep %APPDATA%\volta_debug.txt. It’s a timestamped log of what was collected and whether the AI call worked. Revoke any exposed tokens and change passwords. If a wallet’s seed phrase sat in plaintext on disk, treat the wallet as fully compromised and move the funds to a new wallet whose seed was generated on an air-gapped device. “VOLTA is a mature stealer with a late-stage AI layer added for one purpose: relieving the operator of analytical work. The axis of AI improvement here is not speed or scale but effort displacement; the same logic visible in CLOSEDQUORUM, though applied to a different phase.” concludes the post. “These implants reflect the same underlying logic: Identify the step that requires the most sustained human attention and replace it with a model call. The question for defenders is not whether this pattern will appear elsewhere, but which phase it touches next.” Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs – hacking, malware)
The maintainer of BTCPay Server, an open-source cryptocurrency payment processor, has urged users to install the latest version as hackers have been draining “hot wallets” on instances running older versions. Operators were initially advised to shut down their servers pending a full investigation into the unauthorized Bitcoin and Litecoin payments. The BTCPay Server project provides businesses with a self-hosted payment processing solution that allows them to accept Bitcoin and other digital assets directly into their own wallets, eliminating payment intermediaries or paying platform processing fees. It handles checkout invoices and payment verification, including payments over the Lightning Network. Early Monday, the maintainer said it had “identified an attack vector targeting instances running version 2.4.1 (July 23, 2026) or earlier” and strongly urged users to update to version 2.4.7.
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