cridin1/malware-classification-CNN
This GitHub repository contains an implementation of a malware classification/detection system using Convolutional Neural Networks (CNNs).
This project helps cybersecurity analysts and incident responders automatically detect and classify different types of malicious software. It takes executable files, converts them into image representations, and outputs a prediction of the malware family or if it's benign. This helps security professionals quickly identify threats without needing deep manual analysis of every suspicious file.
No commits in the last 6 months.
Use this if you need an automated way to categorize unknown executable files into known malware types or distinguish them from legitimate software.
Not ideal if you need to analyze the specific behaviors or attack vectors of a malware sample, as this focuses on classification rather than dynamic analysis.
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Last pushed
Jul 19, 2023
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