Description

A sophisticated social-engineering campaign is targeting cryptocurrency traders and gamblers through AI-generated YouTube narrators, fake engagement networks, and manipulated reputation signals to distribute a Rust-based clipboard hijacker. The operation revolves around a WordPress phishing hub operated under the handle ‘@JoseCmanXD’, promoting fraudulent sniper bots, crash-game predictors, and crypto tools promising unfair trading advantages. Victims are directed through GitHub, SourceForge, Telegram, crypto forums, and YouTube channels containing inflated stars, forks, downloads, likes, and coordinated comments generated through Ghost Networks. The campaign also abused legitimate news websites and BitcoinTalk posts to create false legitimacy and encourage malware downloads. The infection chain begins when victims download ZIP archives from phishing pages, GitHub repositories, or SourceForge projects. On Windows, the archive contains a .NET loader launching a Rust-compiled clipboard hijacker that installs itself within ‘%APPDATA%\silke’ and creates Startup folder persistence. The malware registers clipboard listeners using Windows APIs and continuously scans clipboard text using regular expressions for cryptocurrency wallet formats including Bitcoin, Ethereum, Litecoin, Tron, XRP, Cardano, Monero, and Dogecoin. Detected wallet addresses are silently replaced with attacker-controlled wallets selected from an embedded list containing approximately 15,500 cryptocurrency addresses. The macOS variant arrives as a malicious .app bundle accompanied by an unlocker script instructing users to bypass Gatekeeper protections using xattr commands. Once executed, the malware monitors the macOS pasteboard, replaces wallet addresses, and establishes persistence through LaunchAgent plists and launchd KeepAlive mechanisms. AI-generated YouTube tutorials, suspicious view spikes, coordinated comments, and manipulated VirusTotal votes further reinforce trust while lowering user suspicion. This campaign highlights how attackers combine simple malware with AI-generated content and reputation manipulation to bypass skepticism and security defenses. Users should isolate downloads in sandboxed environments, validate binaries against trusted signatures, monitor clipboard activity, avoid bypassing operating system protections, and treat unusually positive engagement metrics with heightened scrutiny during software installations.