Threat actors are recompiling open source software, specifically the 7zip self-extracting archive stub, to embed a reflective loader that evades detection. The malicious code is inserted into the ExtractArchive function of the 7zip SFX module, making it difficult for analysts to identify since they typically focus on configuration files and embedded executables rather than the decompression stub itself. Samples are validly signed by Animated Productions, LLC and contain legitimate installers like foobar2000. The loader beacons to C2 servers, downloads DLLs, and reflectively loads encrypted payloads. Variants also abuse other open source libraries like the NSIS plugin EmbedHtml. Files feature bloated certificates and suspicious characteristics including installers wrapped within installers, requiring persistent analysis to uncover the hidden malicious functionality.
The article details a sophisticated supply chain attack on Notepad++ that occurred from July to October 2025. Attackers compromised the update infrastructure, deploying various malicious payloads through three distinct infection chains. The attack targeted individuals and organizations in Vietnam, El Salvador, Australia, and the Philippines. The infection methods evolved over time, using NSIS installers, Metasploit downloaders, and Cobalt Strike Beacons. The attackers employed clever techniques to evade detection, including the abuse of legitimate software and the use of multiple C2 servers. The article provides a comprehensive timeline of the attack, describes the different execution chains, and offers guidance on detecting traces of the attack.
The Lumma infostealer is a sophisticated malware distributed as Malware-as-a-Service, targeting Windows systems. It primarily steals sensitive data such as browser credentials, cryptocurrency wallets, and VPN/RDP accounts. Lumma is often used in the initial stages of multi-vector attacks, including ransomware and network breaches. The malware is distributed through phishing sites, disguised as pirated software, and uses complex techniques like NSIS packaging, AutoIt scripts, and process hollowing to evade detection. To combat this threat, organizations should implement behavior-based detection systems and integrate threat intelligence into their security strategies.
This analysis focuses on a new variant of Lumma Stealer, a malware that reemerged after a brief hiatus following a law enforcement operation. The article details the malware's code obfuscation, evasion techniques, and persistence mechanisms. It describes Netskope's machine learning-based detection approach, which utilizes a Cloud Sandbox enhanced with ML models to analyze runtime behavior, process trees, and other features. The specific sample analyzed is an NSIS installer file that abuses AutoIt for malicious purposes. The malware employs various anti-analysis techniques and establishes persistence through the Windows Startup folder. Netskope's multi-layered threat protection system successfully detected this Lumma Stealer variant.
A malware campaign using fake software installers to deliver Winos v4.0, a memory-resident malware, has been tracked throughout 2025. The campaign, dubbed Catena, employs trojanized NSIS installers, reflective DLL loading, and shellcode-embedded INI files to evade detection. It stages payloads entirely in memory, connecting to attacker-controlled servers mainly in Hong Kong. The operation appears focused on Chinese-speaking environments and shows signs of long-term planning by a capable threat group. The infection chain involves multiple stages, including initial NSIS installers, first-stage loaders, and second-stage payloads, ultimately delivering the Winos v4.0 stager. The campaign has evolved over time, adapting its tactics to avoid detection while maintaining core infrastructure and execution logic.
