AI-Automated Threat Hunting Brings GhostPenguin Out of the Shadows


Hunting high-impact, advanced malware is a difficult task. It becomes even harder and more time-consuming when defenders focus on low-detection or zero-detection samples. Every day, a huge number of files are sent to platforms like VirusTotal, and the relevant ones often get lost in all that noise. Identifying malware with low or no detections is a particularly challenging process, especially when the malware is new, undocumented, and built largely from scratch.

When threat actors avoid publicly available libraries, known GitHub code, or code borrowed from other malware families, they create previously unseen samples that can evade detection and make hunting them significantly harder. In these cases, the threat actors carefully craft both the code and the network communication to minimize noise and keep the malware as inconspicuous as possible.

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Source: Trend Micro


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