🎯 Threat Intelligence
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Executive summary: Morphisec Threat Labs documents a coordinated supply-chain campaign that abused dormant GitHub accounts to publish AI-generated projects, then pushed subtle maintenance commits that deployed a previously undocumented JavaScript/HTA backdoor, tracked as PyStoreRAT. The campaign targeted IT administrators, OSINT users and security professionals by surfacing on GitHub Trending lists.
Technical details:
• Loader and payloads: PyStoreRAT is a multi-purpose loader implemented as JavaScript/HTA that performs extensive host profiling and dynamically loads multiple payload types, including the Rhadamanthys stealer.
• Execution adaptations: The loader detects specific AV/EDR products (notably CrowdStrike Falcon and Reason-related products such as CyberReason/ReasonLabs) and alters its launch paths to avoid detection.
• Propagation and modularity: The malware can propagate via removable drives and pulls additional modules from operator-controlled infrastructure; modules are delivered dynamically to extend capabilities.
• C2 infrastructure: Operators use a circular, rotating C2 cluster (nodes labeled like node{i}-py-store, py-installer and related nodes) to enable seamless payload updates and resilience to takedowns.
• Linguistic artifacts: Code contains Russian strings (for example, "СИСТЕМА") indicating targeting or testing against Russian-language environments in addition to non-Russian targets.
🔹 Attack Chain Analysis
• Initial Access / Delivery: Dormant GitHub accounts published polished, AI-generated projects (OSINT tools, DeFi bots, GPT wrappers) that gained visibility on GitHub Trending.
• Execution: Subtle commits introduced JavaScript/HTA backdoor (PyStoreRAT) in repositories; loader executes on target systems via social engineering or dropped artifacts.
• Persistence & Profiling: Loader performs system profiling and establishes long-term access, selecting module updates from rotating C2.
• Lateral Movement / Propagation: Spread via removable drives and dynamic module installation increases attack surface.
• Exfiltration / Impact: Operators deliver stealers such as Rhadamanthys for credential and data theft.
Detection guidance (reported): Indicators to monitor include unexpected HTA/JavaScript execution originating from developer-oriented projects, repositories pushed from long-dormant accounts with maintenance-style commits, occurrences of Russian strings such as СИСТЕМА within codebases, and network communication patterns to rotating hostnames matching node*-py-store or py-installer naming conventions. Behavioral detection should look for loaders that change execution paths when specific AV/EDR services are present.
Defensive posture (as described by Morphisec): The report highlights a prevention-first approach that aims to deny the loader a stable environment, disrupt the loader sequence and block C2-driven module updates. Morphisec specifically emphasizes Automated Moving Target Defense (AMTD) and anti-ransomware protections as mechanisms they claim stop PyStoreRAT chains prior to payload delivery.
Limitations and unknowns: The public analysis does not publish specific IP/IOD hashes in the summary; full technical appendices and IOCs are available in the complete Morphisec report. Attribution beyond linguistic artifacts and infrastructure naming remains tentative.
🔹 threatintel #pystorerat #rhadamanthys #github
🔗 Source: https://www.morphisec.com/blog/pystorerat-a-new-ai-driven-supply-chain-malware-campaign-targeting-it-osint-professionals/