: Documentation of how the malware attempts to bypass Personal Firewalls (PFW) or Host Intrusion Prevention Systems (HIPS).
: Applying algorithms such as Random Forest or Gradient Boosting to classify malware types based on extracted features like file size or network connections.
The archive typically contains documentation and analysis for malware samples encountered during the November to December 2022 timeframe. Key elements often included in such write-ups are: ColonelYobo_2022_Nov-Dec.zip
: Analysis of "hooks" in registry keys or values designed to protect autostart capabilities for the malware.
: Utilizing memory dump analysis to detect obfuscated malware that may not leave traces on the physical disk. : Documentation of how the malware attempts to
: Detailed observations of how the samples interact with a system, including attempts to override DNS settings, system shutdowns, and clipboard copying.
Write-ups of this nature generally employ several standard cybersecurity methodologies to extract information from the samples: Key elements often included in such write-ups are:
: Examining the binary or script without execution to find strings, headers, and potential packed signatures (e.g., UPX).
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