BTCPay Server, a self-hosted, open-source cryptocurrency payment processor, has urged users to install the latest version of its software in response to reports of Bitcoin and Litecoin being stolen from hot wallets on instances running older versions. "Our investigation found that these attacks targeted servers running BTCPay Server 2.4.1 (released on 23 July 2026) or earlier," BTCPay Server
Attackers remotely changed the settings on refrigeration controls at supermarkets in Belgium, Sweden, Estonia and other European countries overnight into Monday, November 2, warming fridges and freezers. No chain reported more than several dozen affected stores, and some had to throw away chilled and frozen food or take it off the shelf. Danfoss, a Danish maker of refrigeration controls,&nbsp
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
Unit 42 details recent threat intelligence, highlighting cyberespionage, financial extortion, and the rapid adoption of AI across offensive workflows. The post Unit 42 Threat Intelligence Highlights - Nov. 2, 2026 appeared first on Unit 42.
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.
A cyberattack on refrigeration systems has disrupted stores run by multiple supermarket chains across several European countries after hackers remotely changed temperature settings on freezers and cooling systems. In some cases, hackers shut down refrigerators or activated defrosting systems, causing temperatures to rise, resulting in significant product losses and forcing store managers to intervene early in the morning. Refrigeration failures were identified at dozens of supermarkets, but it is unclear whether they were hit in a coordinated attack or targeted individually. More than 115 stores in Belgium, the Netherlands, Sweden, Luxembourg, Ireland, and Estonia have been affected. Spokespersons for multiple chains confirmed the issues in statements for BleepingComputer. Supermarket chains that acknowledged refrigeration issues include:
Microsoft has resolved a known issue that prevented some users from activating the Smart App Control security feature after installing the October 2026 KB5127648 Windows 11 security update. Smart App Control uses Microsoft's code integrity features and app intelligence services, and it works alongside SmartScreen and Microsoft Defender to block potentially harmful apps or binaries. As the company explained when it acknowledged the issue last month, the Smart App Control option is grayed out and cannot be toggled on affected devices running Windows 11 24H2 and later. "After installing this update, some devices might be unable to turn on Smart App Control in the Windows Security app if it has been turned off. On affected devices, the option to turn on Smart App Control might be grayed out," Microsoft said in the KB5127648 advisory. "Devices where Smart App Control is already turned on are not affected and remain protected."
Over 1,000 Internet-exposed GitLab servers are still unpatched against a maximum-severity flaw actively exploited in remote code execution attacks. Tracked as CVE-2026-97229, this vulnerability stems from an integer overflow weakness and was discovered in the CI/CD Regular Expression Compiler, which parses and evaluates regular expressions in pipeline configuration files. "GitLab has remediated an issue that, under certain conditions, could have allowed an unauthenticated user to execute arbitrary code on the GitLab server via a specially crafted regular expression in a CI/CD configuration, due to insufficient regular expression validation," the company explained on October 12 when it released security patches to address the security issue in GitLab Community Edition (CE) and Enterprise Edition (EE) versions 19.4.2, 19.3.5, and 19.2.8.
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