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TuxBot v3: Inside an IoT Botnet Framework With LLM
Unit 42 uncovers TuxBot v3, an LLM-assisted IoT botnet framework with 17-architecture builds, Telnet brute-forcing, and DDoS capabilities.
Palo Alto Unit 42 identified TuxBot v3 Evolution, a modular IoT botnet framework derived from AISURU, Wuhan-lineage botnets, and MHDDoS. The C-based bot brute-forces Telnet with 1,496 credential pairs, targets over 30 IoT device families, and communicates with a Go-based C2 over encrypted TCP with multiple fallback mechanisms including DGA, P2P, and DNS TXT. LLM-assisted development left hallucinated crypto implementations and broken exploit modules in the analyzed samples, though roughly 70% of core functionality works. Researchers warn polished production builds likely exist, raising the threat potential.
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Inside Knight Office, a New M365 AiTM Phishing Kit
Huntress details Knight Office, a new AiTM phishing kit stealing Microsoft 365 session tokens and registering attacker-controlled devices.
Huntress investigated an August 18, 2026 adversary-in-the-middle attack using the Knight Office phishing kit, which captured Microsoft 365 session tokens via a DocuSign-style lure routed through a Monday.com tracking link and a compromised Joomla site. After token capture, the actor enrolled an unauthorized host in Microsoft Entra ID and bound a Windows Hello for Business key credential to the account. The kit's operator console, found at IP 104.37.188.94, is built on Python Flask and hosts at least 25 .vu phishing domains. Telemetry links the kit to at least nine token-replay logins in two weeks and roughly 700 reported lure emails since April.
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When scanners miss the attack: how Cloudflare Client-Side Security protects storefronts
Cloudflare's Page Shield ML uncovered four malicious JavaScript campaigns on storefronts, including affiliate fraud and a remote-backdoor script, that VirusTotal and URLScan missed.
Cloudflare's Page Shield ML detected four client-side JavaScript operations (eight payloads) in live traffic on online storefronts, enabling affiliate commission hijacking, clickless affiliate theft via hidden iframes, user tracking with a remote-code backdoor, and cloaking of paid mobile visitors. Seven of the eight payloads were absent from VirusTotal and URLScan returned no malicious verdict for any, including a Lnkr-family payload indexed unclassified for roughly 2.5 years. Detection relies on a graph neural network over JavaScript syntax trees, an LLM second opinion on Workers AI, and a frontier-model ensemble voting across benign, magecart, other malware, and cryptomining labels.
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