[Suggestions] Malware Detection Analysis Using Machine Learning

This page summarizes the projects mentioned and recommended in the original post on /r/MalwareResearch

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  • WorkOS - The modern identity platform for B2B SaaS
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  • StratosphereLinuxIPS

    Slips, a free software behavioral Python intrusion prevention system (IDS/IPS) that uses machine learning to detect malicious behaviors in the network traffic. Stratosphere Laboratory, AIC, FEL, CVUT in Prague.

  • ember

    Elastic Malware Benchmark for Empowering Researchers

  • Check out ember: https://github.com/elastic/ember

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • MalConv-keras

    This is the implementation of MalConv proposed in [Malware Detection by Eating a Whole EXE](https://arxiv.org/abs/1710.09435) and its adversarial sample crafting.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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