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malware-visualization

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HelixCipher / malware-detection

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Unsupervised malware detection: anomaly scoring trained on benign software only (autoencoder + frozen DINOv2/Mahalanobis), applied to reversible byteplot images that reassemble into hash-verified executables. Step-by-step notebook + converter.

python machine-learning computer-vision deep-learning jupyter-notebook pytorch cybersecurity autoencoder malware-analysis transfer-learning unsupervised-learning anomaly-detection malware-detection threat-detection malware-visualization byteplot dinov2
  • Updated Nov 3, 2026
  • Jupyter Notebook

tildeeine / AIGIS

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This is a research prototype for visualizing dynamic malware behavior, developed as part of a master's thesis.        The platform is aimed at exploring how different visualizations can support investigation of Windows executables. It includes a custom frontend for process trees, timelines, event graphs, based on sandboxed malware execution data.

malware-analysis malware-visualization
  • Updated Jun 13, 2025
  • Svelte

HelixCipher / malware-classification

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An educational implementation of image-based malware family classification, encompassing a convolutional neural network trained from scratch and transfer learning with ResNet-50, ResNeXt-50 and Inception-v3 on the malimg dataset.

python machine-learning computer-vision deep-learning scikit-learn malware jupyter-notebook cnn pytorch cybersecurity neural-networks image-classification infosec resnet malware-analysis transfer-learning malware-classification manim malware-visualization
  • Updated Oct 5, 2026
  • Jupyter Notebook

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