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    • Create adversarial attacks against machine learning Windows malware detectors
      Python
      MIT License
      4620891Updated Dec 10, 2024Dec 10, 2024
    • Experiments for paper ModSec-AdvLearn: Countering Adversarial SQL Injections with Robust Machine Learning
      Python
      MIT License
      0200Updated Dec 5, 2024Dec 5, 2024
    • Python
      11100Updated Nov 29, 2024Nov 29, 2024
    • secml

      Public
      A Python library for Secure and Explainable Machine Learning
      Jupyter Notebook
      Apache License 2.0
      2516071Updated Nov 11, 2024Nov 11, 2024
    • SecML-Torch: A Library for Robustness Evaluation of Deep Learning Models
      Python
      MIT License
      43571Updated Nov 2, 2024Nov 2, 2024
    • Official repository for the Cybersecurity Use Case of ELSA EU Project
      Python
      1510Updated Oct 18, 2024Oct 18, 2024
    • Dataset used for paper: Boosting ModSecurity with Machine Learning
      Python
      0100Updated Sep 23, 2024Sep 23, 2024
    • End-to-end implementation of ML-based Android malware detectors.
      Python
      5700Updated Sep 3, 2024Sep 3, 2024
    • mlsec

      Public
      MLSec Laboratory
      SCSS
      MIT License
      0100Updated Jun 26, 2024Jun 26, 2024
    • HO-FMN

      Public
      Jupyter Notebook
      0900Updated May 20, 2024May 20, 2024
    • Experiments for paper ModSec-Learn: Boosting ModSecurity with Machine Learning
      Python
      MIT License
      2600Updated Apr 12, 2024Apr 12, 2024
    • Jupyter Notebook
      GNU General Public License v3.0
      83810Updated Jan 25, 2024Jan 25, 2024
    • Command line tool for launching attacks against Machine Learning Malware detectors.
      Python
      GNU General Public License v3.0
      41711Updated Jun 18, 2023Jun 18, 2023
    • Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples
      Python
      GNU General Public License v3.0
      41800Updated May 23, 2022May 23, 2022
    • Foolbox implementation for NeurIPS 2021 Paper: "Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints".
      Jupyter Notebook
      MIT License
      42500Updated Mar 16, 2022Mar 16, 2022
    • Security evaluation module with onnx, pytorch, and SecML.
      Python
      MIT License
      2100Updated Nov 15, 2021Nov 15, 2021
    • a CLI that provides a generic automation layer for assessing the security of ML models
      Python
      MIT License
      130000Updated Jun 25, 2021Jun 25, 2021
    • secml-zoo

      Public
      SecML models and databases zoo.
      Python
      Apache License 2.0
      0300Updated Jun 4, 2021Jun 4, 2021