From RAR to Root: Inside the New Linux Malware Hiding in Archive Filenames

From RAR to Root: Inside the New Linux Malware Hiding in Archive Filenames

Security researchers have identified a new Linux-based malware campaign that hides its payload inside a RAR archive filename. The malicious name contains a Base64-encoded string that, when listed by an insecure shell script, is piped directly into Bash. This tactic bypasses traditional file-based scanning. The executed payload retrieves a Linux ELF binary from a remote server and deploys the VShell backdoor into memory. VShell supports reverse shells, file access, process control, encrypted command-and-control, and targets a wide range of architectures including x86_64, i386, i686, armv7l, and aarch64. For penetration testers,check how automation scripts handle filenames. Simulate is or for  loops with unquoted filenames to detect injection risks. Prevent execution by ensuring proper filename sanitation. Limit or block RAR archive handling on production Linux systems unless verified by sandbox or AV tools.

PS1Bot-Malvertising and In-Memory PowerShell Modules

A widespread campaign delivers the PS1Bot malware via malvertising. The payload executes entirely in memory using PowerShell, leaving minimal disk traces. After initial execution, PS1Bot pulls down modules from a remote server to:

  • Detect and report installed antivirus software

  • Capture screen contents and clipboard data

  • Steal browser credentials and crypto wallets

  • Log keystrokes

  • Persist using autorun PowerShell scripts

This modular, memory-only architecture evades most traditional endpoint protection.

Penetration tester takeaway:
Deploy controlled browser-based malvertising simulations. Monitor for PowerShell execution in memory using Sysmon, AMSI logging, and EDR tools. Watch for child processes spawned by browsers or Office applications that match PowerShell execution behavior.

Supply-Chain Attack in npm and PyPI-The GlueStack Incident

Threat actors inserted malicious code into 16 open-source npm packages within the GlueStack ecosystem, affecting roughly one million users weekly. These packages prompt users for Instagram credentials, store them locally in credentials.txt, and exfiltrate them to attacker-controlled infrastructure.,

This represents a growing threat vector: supply-chain compromise via trusted open-source software.

Pen-testing note:
Audit package dependencies for tampering. Use npm audit, pip-audit , or SCA tools to flag suspicious modules. Test whether dev environments can be tricked into entering credentials and simulate credential harvesting through fake prompts in your assessments. 

Qilin Ransomware and Netxloader Loader Campaign

The Qilin ransomware group, also known as Agenda, recently topped the charts for global ransomware disclosures. They deploy ransomware via a .NET-based loader called NETXLOADER, which uses advanced evasion tactics like Just-In-Time (JIT) hooking and control flow obfuscation. The loader resides only in memory and delivers SmokeLoader and Agenda ransomware to infected hosts.

Actionable testing:
Simulate obfuscated .NET execution in lab environments. Use tools like dnSpy to examine JIT-modified assemblies. Evaluate memory-only detection rules and response capabilities. Test against lateral movement techniques common in ransomware escalation paths.

Matanbuchus 3.0 -Malware-as-a-Service via Microsoft Teams

Matanbuchus 3.0, a loader for Malware-as-a-Service (MaaS), now spreads through social engineering on Microsoft Teams. Attackers impersonate help-desk staff and convince employees to launch Quick Assist and a malicious PowerShell script.

The loader supports in-memory payload delivery via:

  • PowerShell or CMD reverse shells

  • regsvr32, rundll32, and msiexec for binary execution

  • Scheduled tasks via COM

  • WMI reconnaissance

  • Shellcode injection for lateral movement

Pen-tester recommendation:
Simulate social engineering via collaboration tools. Recreate help-desk impersonation attacks. Monitor or block Quick Assist usage in enterprise networks. Validate logging and detection of LOLBins like regsvr32 and msiexec under suspicious contexts.

AI-Driven Malware and Cyber Warfare

AI integration in malware development is now a reality. Malicious actors use large language models (LLMs) to generate polymorphic code, mimic legitimate logic, and automate the creation of novel payloads. Simultaneously, state-sponsored cyber threats are increasing, with adversaries targeting embedded systems, IoT hardware, and telecom infrastructure. AI-driven reconnaissance and attack automation reduce time-to-compromise significantly.

Pen-testing strategies:
Emulate fuzzing and logic attacks using AI-generated scripts. Test AI-assisted applications for injection bugs and insecure logic flow. Map critical embedded systems and simulate tampering scenarios. Treat LLM-generated output as untrusted by default.

Key Threat Trends

  • Memory-only malware is bypassing most EDR and antivirus tools.

  • Modular loaders are being sold as services and updated regularly.

  • Open-source software is now a primary target for long-term persistence.

  • Ransomware operations are increasingly professionalized and stealth-driven.

  • AI tools are being used by attackers to scale and adapt malicious campaigns.

  • Nation-state actors are embedding malware in infrastructure devices and telecom systems.

Practical Pen-Testing Strategies

1. Filename Injection Testing
Scripts that use for file in or eval with unquoted file names are vulnerable. Use fuzzed filenames with command injection payloads during assessments.

2. Monitor PowerShell in Memory
Use tools like:

  • PowerShell Transcription logging

  • Event Tracing for Windows (ETW)

  • Sysmon (memory image loads, parent-child process chains)for file in * or eval

  • Any sandbox that can monitor memory-based execution

3. Simulate Malvertising Campaigns
Deliver simulated .ps1 droppers via browser ads and monitor whether endpoints execute without user awareness.

4. Supply Chain Risk Audits
Regularly scan packages in your software ecosystem. Require code reviews on any external dependency updates.

5. Obfuscation Awareness
Use behavioral testing on binaries. Flag sudden spikes in CPU, memory allocation, or suspicious DLL loading. Scan .NET binaries for control flow flattening and modified entry points.

6. Phishing via Collaboration Tools
Simulate attacks using Teams, Slack, Zoom, or Google Chat. Test employee responses to urgent IT messages that request script execution or remote desktop access.

7. AI-Crafted Exploits and Logic Bombs
Fuzz test AI-integrated systems using input data generated by LLMs. Validate sanitization, rate-limiting, and logic boundary protection.

Thought Leadership from Digital Warfare

James Knight, Senior Principal at Digital Warfare, stated: “Penetration testing inspired by real-world case studies like ours at Digital Warfare, including our IoT and embedded systems analysis, drives better detection of supply-chain and device-level threats.”

Final Word -Stay Ahead, Stay Informed

In today’s cybersecurity climate, offensive simulations must be faster, more realistic, and deeply aligned with current attacker playbooks. Stay ahead by:

  • Reading daily cybersecurity briefs

  • Recreating current malware behavior in safe labs

  • Attending capture-the-flag and red team events

  • Practicing safe code review with AI-generated content

  • Sharing discoveries in community forums or write-ups

The landscape is moving fast. Penetration testing isn’t just a service-it’s a mindset. Adopt it.

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