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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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Atomic macOS (AMOS) Stealer Activity
Unit 42 details an August 2026 AMOS macOS stealer infection delivered via fake 'macOS toolkit' pages and Terminal paste commands, exfiltrating credentials to C2.
Unit 42 analyzed an AMOS (Atomic macOS Stealer) infection from August 5, 2026, initiated via a page at getmacouscloud[.]com instructing users to paste a command into Terminal. The command fetched a Zsh script from ferncore13[.]com that delivered a Mach-O installer to /tmp/helper and supporting files under /Library/Application Support/.com.apple.accountsd/ and .com.apple.metadata.mds/. AMOS collected browser data, credentials, cryptocurrency wallets (Binance, TonKeeper), Telegram data, and FileGrabber content such as AWS and gcloud files, uploading it via HTTP POST to C2 server 161.35.146[.]120. AMOS has been advertised on Telegram since April 2024 and distributed via ClickFix campaigns, malicious ads, and cracked-software sites.
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HVNC Backdoor Targets LATAM Organizations with Fake Tax and DocuSign Lures
A custom HVNC backdoor is targeting Latin American financial organizations via fake DocuSign and NFe tax-document lures, giving attackers hidden persistent remote access.
ANY.RUN researchers analyzed a multi-stage phishing campaign delivering a custom HVNC backdoor to banking and financial organizations in Latin America. The chain starts with fake DocuSign and NFe tax-document pages that serve per-visitor ZIP archives, followed by an LNK dropper, an NSIS loader, and a 64-bit backdoor masquerading as Windows Update Assistant. The implant provides hidden remote desktop control, keystroke monitoring, Firefox data theft, Startup-folder persistence, and EDR-aware behavior, communicating over TCP/27015.
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Analysis of Smoke Loader in New Tsunami Campaign
Fake Japanese Meteorological Agency tsunami warning emails delivered Smoke Loader and AzoRult malware to steal credentials from targets in Japan.
A fake tsunami warning email impersonating Japan's Meteorological Agency asked recipients to click a link on a registered fake agency domain, delivering the commodity loader Smoke Loader to targets in Japan. Smoke Loader, active since 2011, is modular, and its payloads have included banking trojans, ransomware, cryptominers, password stealers, and PoS malware; the campaign later also deployed AzoRult. New samples add junk-jump obfuscation, encrypted network traffic and payload files, a unique machine ID used for tracking and encryption, and PROPagate injection into explorer.exe, with persistence via a Startup folder shortcut and RC4-encrypted C2 communication.
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Tracking OceanLotus’ new Downloader, KerrDown
Unit 42 identifies KerrDown, a new OceanLotus (APT32) downloader active since 2018 targeting Vietnamese speakers via malicious macros and DLL side-loading.
Unit 42 tracks KerrDown, a previously undocumented downloader family used by OceanLotus (APT32) since at least early 2018, primarily targeting Vietnam or Vietnamese-speaking individuals. Delivery uses macro-laced Microsoft Office documents embedding base64-encoded 32-bit and 64-bit DLLs, and RAR archives containing a legitimate program abused for DLL side-loading. KerrDown is dropped as main_background.png, downloads a DES-encrypted payload from a URL, and executes it directly in memory. Researchers used Jaccard-index similarity analysis to identify the new family, connect campaign samples, and infer patterns in the group's working hours and days.
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