Malware Analysis – Virut’s NTDLL Hooking and Process Infection, Part 2

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You Should Know:

Virut Malware Analysis Key Techniques

1. x64dbg Scripting

  • Automate debugging tasks with scripts:
    from x64dbgpy import<br />
    while True: 
    if reg.get("eip") == 0x401000: 
    log("Reached target address!") 
    break 
    step_over() 
    

2. Conditional Breakpoints

  • Set breakpoints that trigger only under specific conditions:
    bp 0x401000, "ecx == 0x1234" 
    

3. Import Table Resolving

  • Rebuild corrupted import tables using tools like Scylla:
    scylla -p <PID> -I <infected.exe> 
    

4. Fixing Control Flow

  • Use IDA Pro or Ghidra to reconstruct obfuscated execution paths.

5. Marking Hook Code

  • Identify NTDLL hooks via memory comparison:
    windbg> !dh ntdll 
    windbg> u ntdll!ZwCreateFile 
    

Practical Commands for Malware Analysis

  • Dump Process Memory (Windows):
    procdump -ma <malware.exe> 
    

  • Check API Hooks (Linux):

    ltrace -e malloc -e free ./malware 
    

  • Extract Strings (Cross-Platform):

    strings -n 8 malware.bin | grep "http" 
    

  • Analyze Network Traffic:

    tcpdump -i any -w virut_traffic.pcap 
    

What Undercode Say:

Virut remains a classic example of polymorphic file infectors, blending obfuscation with aggressive hooking techniques. Modern malware inherits these traits but with added layers like API unhooking (e.g., SysWhispers3). Analysts must master:

  • Dynamic Analysis: Use Frida for runtime hook detection:
    Interceptor.attach(Module.getExportByName("ntdll.dll", "ZwCreateFile"), { 
    onEnter: function(args) { console.log("ZwCreateFile called!"); } 
    }); 
    

  • Static Analysis: Ghidra’s decompiler helps untangle Virut’s logic.

  • YARA Rules: Detect Virut variants:

    rule Virut_Hook { 
    strings: $hook_code = { 68 ?? ?? ?? ?? E9 } 
    condition: $hook_code 
    } 
    

Expected Output:

A detailed report with:

  • Reconstructed import tables.
  • Identified NTDLL hooks.
  • Cleaned binaries via de-infection scripts.

Prediction:

Polymorphic malware will increasingly leverage AI-driven obfuscation, requiring analysts to adopt machine learning-aided reverse engineering tools.

Note: If the original post lacked a title, “How Hack: Analyzing Virut’s Polymorphic Hooking Techniques” would be suggested.

IT/Security Reporter URL:

Reported By: Karsten Hahn – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

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