PRALab's repositories
secml_malware
Create adversarial attacks against machine learning Windows malware detectors
Fast-Minimum-Norm-FMN-Attack
Foolbox implementation for NeurIPS 2021 Paper: "Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints".
IndicatorsOfAttackFailure
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples
secml-torch
SecML-Torch: A Library for Robustness Evaluation of Deep Learning Models
toucanstrike
Command line tool for launching attacks against Machine Learning Malware detectors.
android-detectors
End-to-end implementation of ML-based Android malware detectors.
modsec-learn
Experiments for paper ModSec-Learn: Boosting ModSecurity with Machine Learning
elsa-cybersecurity
Official repository for the Cybersecurity Use Case of ELSA EU Project
http-traffic-dataset
Dataset used for paper: Boosting ModSecurity with Machine Learning
pandavision
Security evaluation module with onnx, pytorch, and SecML.
counterfit
a CLI that provides a generic automation layer for assessing the security of ML models