There are 18 repositories under defense topic.
🔒 A compiled checklist of 300+ tips for protecting digital security and privacy in 2024
HardeningKitty and Windows Hardening Settings
HardeningKitty - Checks and hardens your Windows configuration
ESB, SOA, REST, APIs and Cloud Integrations in Python
A pytorch adversarial library for attack and defense methods on images and graphs
A curated collection of adversarial attack and defense on graph data.
Production-ready detection & response queries for osquery
The OWASP Java Encoder is a Java 1.5+ simple-to-use drop-in high-performance encoder class with no dependencies and little baggage. This project will help Java web developers defend against Cross Site Scripting!
Adversarial attacks and defenses on Graph Neural Networks.
💡 Adversarial attacks on explanations and how to defend them
Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"
A certifiable defense against adversarial examples by training neural networks to be provably robust
Kernel Security driver used to block past, current and future process injection techniques on Windows Operating System.
Emulate and Dissect MSF and *other* attacks
一个针对防御 log4j2 CVE-2021-44228 漏洞的 RASP 工具。 A Runtime Application Self-Protection module specifically designed for log4j2 RCE (CVE-2021-44228) defense.
This repository contains the implementation of three adversarial example attack methods FGSM, IFGSM, MI-FGSM and one Distillation as defense against all attacks using MNIST dataset.
The ngx_dynamic_limit_req_module module is used to dynamically lock IP and release it periodically.
List of state of the art papers, code, and other resources
Collection of PowerShell functinos and scripts a Blue Teamer might use
SHIELD: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression
:skull: A collection of methods to fool the deep neural network :skull:
Feature Scattering Adversarial Training (NeurIPS19)
This is the official pytorch implementation for paper: IF-Defense: 3D Adversarial Point Cloud Defense via Implicit Function based Restoration
GAMECHANGER aspires to be the Department’s trusted solution for evidence-based, data-driven decision-making across the universe of DoD requirements
[ICML 2019] ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
This repository contains a collection of PowerShell tools that can be utilized to protect and defend an environment based on the recommendations of multiple cyber security researchers at Microsoft. These tools were created with a small to medium size enterprise environment in mind as smaller organizations do not always have the type of funding available to overly spend on security. The goal of this project is to help add value to an smaller organizations security by creating more visibility for the average IT Administrator. Organizations with 1,000’s of devices may find that this entire suite does not apply to them.
A novel approach to improve the safety of large language models, enabling them to transition effectively from unsafe to safe state.
FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning [ICLR‘23, Best Paper Award at ECCV’22 AROW Workshop]
Deauthalyzer is a script designed to monitor WiFi networks and detect deauthentication attacks. It utilizes packet sniffing and analysis techniques to identify deauthentication attack packets and provide relevant information about the attack.