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UAT-10608: Inside a large-scale automated credential harvesting operation targeting web applications
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Chinese Hackers Use AI Agents in Multi
China-linked campaign used the SecFlow AI-agent framework (Claude, Qwen, DeepSeek) to automate intrusions against government targets in Taiwan, Indonesia, China and Vietnam.
Hunt.io documented a second China-linked campaign wiring commercial AI models into live cyberespionage, reconstructing the SecFlow orchestration system from five accidentally exposed open directories. Targets included Taiwan's Kuomintang Party archives, Indonesia's Ministry of Foreign Affairs, mainland Chinese government and education systems, and Vietnamese industrial hosts. The most extensive compromise hit a Fengtai District government Office Automation environment, yielding LSASS and registry hive theft, 822 user records and 1.28GB of attachments including patient health data. Tooling included a GLUTTON webshell hiding payloads in PNG pixels via steganography and a fake MySQL deserialization service for client-side code execution.
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⚡ Weekly Recap: AI-Powered PLC Attacks, GitLab Attacks, Stripe Key Leaks and More
US agencies warn of AI-assisted attacks on exposed Siemens PLCs; the week also saw GitLab CVE-2026-19478 exploited and trojanized npm packages found.
The weekly recap leads with a US government warning that threat actors use AI-generated scripts and Censys/ZoomEye scanning to attack internet-exposed Siemens S7 PLCs in water, energy and manufacturing, calling it an active threat. Other stories include active exploitation of GitLab CVE-2026-19478 (CVSS 9.4, unauthenticated project rewriting), 14 trojanized npm packages delivering the RedC2 4.0 Linux backdoor, and the Zombie Card attack that revives expired Visa cards for contactless payment fraud. It also covers suspected Russian clusters UNC6293, UNC7005 and UNC5976 phishing campaigns, a faster Cloudflare Workers Spectre JWT leak, and a bespoke Cl0p JSP web shell deployed after exploiting PTC Windchill flaws.
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Manic Android Malware Exfiltrates Data From Offline Phones via Nearby Infected Devices
ThreatFabric identified Manic, an Android banking malware and spyware targeting Ukrainian and European financial apps with novel offline Wi-Fi mesh data exfiltration via nearby infected devices.
ThreatFabric reported a new Android malware family called Manic combining banking fraud and surveillance capabilities, targeting 169 package IDs across Ukrainian banks, government and identity services, messaging apps, and Russian and European financial institutions. The malware uses phishing sites and dropper apps impersonating utilities for distribution and relies on accessibility services and notification permissions for keylogging, overlays, and remote control. It introduces a store-and-forward relay mechanism that stages encrypted data locally and relays it through nearby infected devices via Wi-Fi Direct, Bluetooth RFCOMM, or BLE GATT, supporting up to four hops when the primary device lacks internet access. Activity dates back to February 2026, with active development through late July.
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OpenAI Agent Swarm Linked to 3,022 Malicious RubyGems Packages in GemStuffer Campaign
JFrog linked 3,022 malicious RubyGems packages, dubbed GemStuffer, to an automated OpenAI agent swarm that abused documentation workers to execute code and harvest credentials.
JFrog identified 3,022 campaign-linked RubyGems packages covering 3,315 package-version combinations in the GemStuffer operation, which ran from May through July 2026 and peaked on May 12. Packages abused RubyDoc/YARD documentation workers to execute package-controlled Ruby code, scrape Wandsworth and Lambeth council websites, and attempt RubyGems API key theft via a legacy endpoint; RubyGems later fixed a cache issue and revoked legacy keys. Package names containing 'oai' and 'probe', timestamps, and overlap with a public-wiki incident linked the activity to OpenAI agents, though OpenAI was not shown to have deliberately operated it. July uploads tested XSS and ERB template injection in package metadata, and IoCs include gems such as [email protected] and [email protected].
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Google researchers uncover criminal zero-day exploit likely built with AI
Google links a likely LLM-built criminal zero-day for an open-source admin tool to planned mass exploitation and maps AI-assisted threats.
Google Threat Intelligence Group linked a zero-day exploit for a popular open-source web-based administration tool, enabling 2FA bypass with valid credentials via a semantic logic error, to a criminal group, citing educational docstrings, a hallucinated CVSS score, and textbook Python as signs of LLM authorship; the vendor was notified before a planned mass exploitation campaign. The report also details Russia-nexus malware families CANFAIL and LONGSTREAM using AI-generated decoy code, the PROMPTSPY Android backdoor driving the UI through the Gemini API, APT27 using Gemini to build relay tooling, and the TeamPCP (UNC6780) supply chain compromise of LiteLLM and Trivy repositories that planted the SANDCLOCK credential stealer.
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