DumpwareThreatDetector
AI-powered malware detection system that converts binary files into grayscale visual matrices and classifies threats using deep convolutional neural networks.
Overview
Malware authors frequently obfuscate code to defeat signature-based antivirus scanners. DumpwareThreatDetector converts raw unparsed executable binaries into 2D pixel density maps and employs deep CNN architectures to detect malicious structural patterns regardless of string obfuscation.
Key Metrics & Performance
97.8% Detection Accuracy
45ms/binary Inference Speed
Architecture & Design
Binary-to-image converter generates fixed-width 8-bit grayscale bitmaps. A customized ResNet/VGG network extracts invariant texture features from code, data, and import sections, classifying samples into benign or specific malware families.
Key Capabilities
- Static binary visualization without sandbox execution overhead
- Robust against obfuscation, packing, and symbol stripping
- Multi-class malware family classification (trojan, worm, ransomware, benign)