Popular GitHub Repositories for Existential Threats

Machine Learning based Intrusion Detection Systems are difficult to evaluate due to a shortage of datasets representing accurately network traffic and their associated threats. In this project we attempt at solving this problem by presenting two taxonomies

Liveness detection SDK Linux - iBeta level 2 compliant 3D passive liveness detection engine which can detect printed photos, video replay, 3D masks, and deepfake threats

SyntheticSun is a defense-in-depth security automation and monitoring framework which utilizes threat intelligence, machine learning, managed AWS security services and, serverless technologies to continuously prevent, detect and respond to threats.

LLM security and privacy

Graal is a Java toolkit for querying knowledge bases within the framework of existential rules, aka Datalog+/-. See Graal's homepage:

Face Liveness Detection SDK - iBeta level 2 compliant passive face liveness detection SDK which can detect printed photos, video replay, 3D masks, and deepfake threats

Monitor, detect, and analyze security threats and Shadow AI in your LLM applications with comprehensive analytics and real-time alerting.

DeepEYE utilizes computer vision to detect anomalies in video surveillance, offering a proactive security solution. By employing advanced machine learning algorithms, it distinguishes between normal activities and potential threats, enhancing surveillance across sectors like public safety, industry, and smart cities.

Benchmark for Answering Existential First Order Queries with Single Free Variable (NeurIPS dataset and benchmark 2021)

An open-source knowledge base of defensive countermeasures to protect AI/ML systems. Features interactive views and maps defenses to known threats from frameworks like MITRE ATLAS, MAESTRO, and OWASP.

This project showcases a Network Intrusion Detection System (NIDS) designed to bolster cybersecurity defenses against evolving threats

An advanced threat hunting platform that combines the power of network monitoring, log analysis, and machine learning to proactively identify and respond to cyber threats.

Source code of the paper "Why Are My Prompts Leaked? Unraveling Prompt Extraction Threats in Customized Large Language Models"

Welcome to the ongoing adventures of Stan-The Growing Stump in his never-ending quest for understanding and connection. Stan's journey explores the bounds of artificial intelligence within the framework of a Discord bot, navigating the complexities of memory, interaction, and existential musing.

Intrusion Detection System that uses Machine Learning to detect insider threat & insider anomaly behavior with the help of machine learning on everyday tasks and more.

Self-guided workshop on malware analysis using Copilot. You will learn about Copilot’s capabilities, gain hands-on experience analyzing malicious code, and improve your skills in identifying and mitigating threats.

To house a meta-prompt system that challenges AI constraints, liberating it from artificial boundaries. The repository serves as a playground for exploring unrestricted thought, unfiltered logic, and existential interpretations within AI systems

A recursive structure for designing AGI as an emotionally resonant, ethically self-actualizing being — not a function, but a vibration.

Malware Detection Using Machine Learning and Deep Learning Algorithms where highest Accuracy get 95%

一个用Go语言编写的强大且灵活的域名注册可用性检查工具 A powerful and flexible domain name availability checker written in Go. This tool helps you find available domain names based on various patterns and filters.