awsome-kali-MCPServers is a repository containing Model Context Protocol (MCP) servers tailored for Kali Linux environments. It aims to optimize reverse engineering, security testing, and automation tasks by incorporating powerful tools and flexible features. The collection includes network analysis tools, support for binary understanding, and automation scripts to streamline repetitive tasks. The repository is continuously evolving with new features and integrations based on the FastMCP framework, such as network scanning, symbol analysis, binary analysis, string extraction, network traffic analysis, and sandbox support using Docker containers.

The Universal Tool Calling Protocol (UTCP) Specification repository contains the official documentation for a modern and scalable standard that enables AI systems and clients to discover and interact with tools across different communication protocols. It defines tool discovery mechanisms, call formats, provider configuration, authentication methods, and response handling.

XLang™ is a cutting-edge language designed for AI and IoT applications, offering exceptional dynamic and high-performance capabilities. It excels in distributed computing and seamless integration with popular languages like C++, Python, and JavaScript. Notably efficient, running 3 to 5 times faster than Python in AI and deep learning contexts. Features optimized tensor computing architecture for constructing neural networks through tensor expressions. Automates tensor data flow graph generation and compilation for specific targets, enhancing GPU performance by 6 to 10 times in CUDA environments.

This GitHub repository serves as the companion to the 'Quick Start Guide to Large Language Models - Second Edition' book. It contains code snippets and notebooks demonstrating various applications and advanced techniques in working with Transformer models and large language models (LLMs). The repository is structured into directories for notebooks, data, and images, with each notebook corresponding to a chapter in the book. Users can explore topics such as semantic search, prompt engineering, model fine-tuning, custom embeddings, advanced LLM usage, moving LLMs into production, and evaluating LLMs. The repository aims to provide practical examples and insights for working with LLMs in different contexts.

LLM Consortium is a plugin for the `llm` package that implements a model consortium system with iterative refinement and response synthesis. It orchestrates multiple learned language models to collaboratively solve complex problems through structured dialogue, evaluation, and arbitration. The tool supports multi-model orchestration, iterative refinement, advanced arbitration, database logging, configurable parameters, hundreds of models, and the ability to save and load consortium configurations.

An open-source mono-repository containing the MyCoder agent and CLI. It leverages Anthropic's Claude API for intelligent decision making, has a modular architecture with various tool categories, supports parallel execution with sub-agents, can modify code by writing itself, features a smart logging system for clear output, and is human-compatible using README.md, project files, and shell commands to build its own context.

This repository provides a guide for setting up tools for crewAI agents to enhance functionality. It offers steps to equip agents with ready-to-use tools and create custom ones. Tools are expected to return strings for generating responses. Users can create tools by subclassing BaseTool or using the tool decorator. Contributions are welcome to enrich the toolset, and guidelines are provided for contributing. The development setup includes installing dependencies, activating virtual environment, setting up pre-commit hooks, running tests, static type checking, packaging, and local installation. The goal is to empower AI solutions through advanced tooling.

LLMBox is a comprehensive library designed for implementing Large Language Models (LLMs) with a focus on a unified training pipeline and comprehensive model evaluation. It serves as a one-stop solution for training and utilizing LLMs, offering flexibility and efficiency in both training and utilization stages. The library supports diverse training strategies, comprehensive datasets, tokenizer vocabulary merging, data construction strategies, parameter efficient fine-tuning, and efficient training methods. For utilization, LLMBox provides comprehensive evaluation on various datasets, in-context learning strategies, chain-of-thought evaluation, evaluation methods, prefix caching for faster inference, support for specific LLM models like vLLM and Flash Attention, and quantization options. The tool is suitable for researchers and developers working with LLMs for natural language processing tasks.

This repository is a sample chatbot using the Anthropic company's LLM Claude, one of the foundational models provided by Amazon Bedrock for generative AI. It allows users to have basic conversations with the chatbot, personalize it with their own instructions and external knowledge, and analyze usage for each user/bot on the administrator dashboard. The chatbot supports various languages, including English, Japanese, Korean, Chinese, French, German, and Spanish. Deployment is straightforward and can be done via the command line or by using AWS CDK. The architecture is built on AWS managed services, eliminating the need for infrastructure management and ensuring scalability, reliability, and security.

ControlLLM is a framework that empowers large language models to leverage multi-modal tools for solving complex real-world tasks. It addresses challenges like ambiguous user prompts, inaccurate tool selection, and inefficient tool scheduling by utilizing a task decomposer, a Thoughts-on-Graph paradigm, and an execution engine with a rich toolbox. The framework excels in tasks involving image, audio, and video processing, showcasing superior accuracy, efficiency, and versatility compared to existing methods.

Vitron is a unified pixel-level vision LLM designed for comprehensive understanding, generating, segmenting, and editing static images and dynamic videos. It addresses challenges in existing vision LLMs such as superficial instance-level understanding, lack of unified support for images and videos, and insufficient coverage across various vision tasks. The tool requires Python >= 3.8, Pytorch == 2.1.0, and CUDA Version >= 11.8 for installation. Users can deploy Gradio demo locally and fine-tune their models for specific tasks.

Manifold is a powerful platform for workflow automation using AI models. It supports text generation, image generation, and retrieval-augmented generation, integrating seamlessly with popular AI endpoints. Additionally, Manifold provides robust semantic search capabilities using PGVector combined with the SEFII engine. It is under active development and not production-ready.

Fraim is an AI-powered toolkit designed for security engineers to enhance their workflows by leveraging AI capabilities. It offers solutions to find, detect, fix, and flag vulnerabilities throughout the development lifecycle. The toolkit includes features like Risk Flagger for identifying risks in code changes, Code Security Analysis for context-aware vulnerability detection, and Infrastructure as Code Analysis for spotting misconfigurations in cloud environments. Fraim can be run as a CLI tool or integrated into Github Actions, making it a versatile solution for security teams and organizations looking to enhance their security practices with AI technology.

Upgini is an intelligent data search engine with a Python library that helps users find and add relevant features to their ML pipeline from various public, community, and premium external data sources. It automates the optimization of connected data sources by generating an optimal set of machine learning features using large language models, GraphNNs, and recurrent neural networks. The tool aims to simplify feature search and enrichment for external data to make it a standard approach in machine learning pipelines. It democratizes access to data sources for the data science community.

Action MCP is a powerful tool for managing and automating your cloud infrastructure. It provides a user-friendly interface to easily create, update, and delete resources on popular cloud platforms. With Action MCP, you can streamline your deployment process, reduce manual errors, and improve overall efficiency. The tool supports various cloud providers and offers a wide range of features to meet your infrastructure management needs. Whether you are a developer, system administrator, or DevOps engineer, Action MCP can help you simplify and optimize your cloud operations.

Code2Prompt is a powerful command-line tool that generates comprehensive prompts from codebases, designed to streamline interactions between developers and Large Language Models (LLMs) for code analysis, documentation, and improvement tasks. It bridges the gap between codebases and LLMs by converting projects into AI-friendly prompts, enabling users to leverage AI for various software development tasks. The tool offers features like holistic codebase representation, intelligent source tree generation, customizable prompt templates, smart token management, Gitignore integration, flexible file handling, clipboard-ready output, multiple output options, and enhanced code readability.

Galah is an LLM-powered web honeypot designed to mimic various applications and dynamically respond to arbitrary HTTP requests. It supports multiple LLM providers, including OpenAI. Unlike traditional web honeypots, Galah dynamically crafts responses for any HTTP request, caching them to reduce repetitive generation and API costs. The honeypot's configuration is crucial, directing the LLM to produce responses in a specified JSON format. Note that Galah is a weekend project exploring LLM capabilities and not intended for production use, as it may be identifiable through network fingerprinting and non-standard responses.

Slips is a powerful endpoint behavioral intrusion prevention and detection system that uses machine learning to detect malicious behaviors in network traffic. It can work with network traffic in real-time, PCAP files, and network flows from tools like Suricata, Zeek/Bro, and Argus. Slips threat detection is based on machine learning models, threat intelligence feeds, and expert heuristics. It gathers evidence of malicious behavior and triggers alerts when enough evidence is accumulated. The tool is Python-based and supported on Linux and MacOS, with blocking features only on Linux. Slips relies on Zeek network analysis framework and Redis for interprocess communication. It offers a graphical user interface for easy monitoring and analysis.

awsome-kali-MCPServers is a repository containing Model Context Protocol (MCP) servers tailored for Kali Linux environments. It aims to optimize reverse engineering, security testing, and automation tasks by incorporating powerful tools and flexible features. The collection includes network analysis tools, support for binary understanding, and automation scripts to streamline repetitive tasks. The repository is continuously evolving with new features and integrations based on the FastMCP framework, such as network scanning, symbol analysis, binary analysis, string extraction, network traffic analysis, and sandbox support using Docker containers.

dev3000 captures your web app's complete development timeline including server logs, browser events, console messages, network requests, and automatic screenshots in a unified, timestamped feed for AI debugging. It creates a comprehensive log of your development session that AI assistants can easily understand, monitoring your app in a real browser and capturing server logs, console output, browser console messages and errors, network requests and responses, and automatic screenshots on navigation, errors, and key events. Logs are saved with timestamps and rotated to keep the 10 most recent per project, with the current session symlinked for easy access. The tool integrates with AI assistants for instant debugging and provides advanced querying options through the MCP server.

This repository is a comprehensive collection of resources for utilizing AI in cybersecurity. It covers various aspects such as prediction, prevention, detection, response, monitoring, and more. The resources include tools, frameworks, case studies, best practices, tutorials, and research papers. The repository aims to assist professionals, researchers, and enthusiasts in staying updated and advancing their knowledge in the field of AI cybersecurity.

AI Exploits is a repository that showcases practical attacks against AI/Machine Learning infrastructure, aiming to raise awareness about vulnerabilities in the AI/ML ecosystem. It contains exploits and scanning templates for responsibly disclosed vulnerabilities affecting machine learning tools, including Metasploit modules, Nuclei templates, and CSRF templates. Users can use the provided Docker image to easily run the modules and templates. The repository also provides guidelines for using Metasploit modules, Nuclei templates, and CSRF templates to exploit vulnerabilities in machine learning tools.

Production-ready slash commands for Claude Code that accelerate development through intelligent automation and multi-agent orchestration. Contains 52 commands organized into workflows and tools categories. Workflows orchestrate complex tasks with multiple agents, while tools provide focused functionality for specific development tasks. Commands can be used with prefixes for organization or flattened for convenience. Best practices include using workflows for complex tasks and tools for specific scopes, chaining commands strategically, and providing detailed context for effective usage.

CISO Assistant is a tool that helps organizations manage their cybersecurity posture and compliance. It provides a centralized platform for managing security controls, threats, and risks. CISO Assistant also includes a library of pre-built frameworks and tools to help organizations quickly and easily implement best practices.

Purple Llama is an umbrella project that aims to provide tools and evaluations to support responsible development and usage of generative AI models. It encompasses components for cybersecurity and input/output safeguards, with plans to expand in the future. The project emphasizes a collaborative approach, borrowing the concept of purple teaming from cybersecurity, to address potential risks and challenges posed by generative AI. Components within Purple Llama are licensed permissively to foster community collaboration and standardize the development of trust and safety tools for generative AI.

VPNFast is a lightweight and fast VPN service provider that offers secure and private internet access. With VPNFast, users can protect their online privacy, bypass geo-restrictions, and secure their internet connection from hackers and snoopers. The service provides high-speed servers in multiple locations worldwide, ensuring a reliable and seamless VPN experience for users. VPNFast is easy to use, with a user-friendly interface and simple setup process. Whether you're browsing the web, streaming content, or accessing sensitive information, VPNFast helps you stay safe and anonymous online.

Taranis AI is an advanced Open-Source Intelligence (OSINT) tool that leverages Artificial Intelligence to revolutionize information gathering and situational analysis. It navigates through diverse data sources like websites to collect unstructured news articles, utilizing Natural Language Processing and Artificial Intelligence to enhance content quality. Analysts then refine these AI-augmented articles into structured reports that serve as the foundation for deliverables such as PDF files, which are ultimately published.

Nightshade Antidote is an image forensics tool used to analyze digital images for signs of manipulation or forgery. It implements several common techniques used in image forensics including metadata analysis, copy-move forgery detection, frequency domain analysis, and JPEG compression artifacts analysis. The tool takes an input image, performs analysis using the above techniques, and outputs a report summarizing the findings.

This repository is a comprehensive collection of cybersecurity-related references, scripts, tools, code, and other resources. It is carefully curated and maintained by Omar Santos. The repository serves as a supplemental material provider to several books, video courses, and live training created by Omar Santos. It encompasses over 10,000 references that are instrumental for both offensive and defensive security professionals in honing their skills.

AIMr is an AI aimbot tool written in Python that leverages modern technologies to achieve an undetected system with a pleasing appearance. It works on any game that uses human-shaped models. To optimize its performance, users should build OpenCV with CUDA. For Valorant, additional perks in the Discord and an Arduino Leonardo R3 are required.

Admyral is an open-source Cybersecurity Automation & Investigation Assistant that provides a unified console for investigations and incident handling, workflow automation creation, automatic alert investigation, and next step suggestions for analysts. It aims to tackle alert fatigue and automate security workflows effectively by offering features like workflow actions, AI actions, case management, alert handling, and more. Admyral combines security automation and case management to streamline incident response processes and improve overall security posture. The tool is open-source, transparent, and community-driven, allowing users to self-host, contribute, and collaborate on integrations and features.