SecML Malware
A Python library for creating adversarial attacks against Windows malware detectors to evaluate their robustness.
What is SecML Malware?
SecML Malware is a Python library for generating adversarial attacks against machine learning-based Windows malware detectors. It provides a suite of state-of-the-art evasion techniques to test and improve the robustness of malware classifiers. The library includes a pre-trained MalConv model and supports both white-box and black-box attack scenarios.
Security researchers, malware analysts, and machine learning practitioners focused on adversarial robustness and cybersecurity. It is particularly useful for those evaluating or developing malware detection systems.
Developers choose SecML Malware for its comprehensive collection of implemented attacks, reproducibility, and ease of integration with existing malware detection pipelines. Its focus on Windows malware and inclusion of a pre-trained model accelerates research and testing.
Overview
Create adversarial attacks against machine learning Windows malware detectors
Use Cases
Best For
- Evaluating the robustness of machine learning-based malware classifiers
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