Beelzebub is an advanced honeypot framework designed to provide a highly secure environment for detecting and analyzing cyber attacks. It offers a low code approach for easy implementation and utilizes virtualization techniques powered by OpenAI Generative Pre-trained Transformer. Key features include OpenAI Generative Pre-trained Transformer acting as Linux virtualization, SSH Honeypot, HTTP Honeypot, TCP Honeypot, Prometheus openmetrics integration, Docker integration, RabbitMQ integration, and kubernetes support. Beelzebub allows easy configuration for different services and ports, enabling users to create custom honeypot scenarios. The roadmap includes developing Beelzebub into a robust PaaS platform. The project welcomes contributions and encourages adherence to the Code of Conduct for a supportive and respectful community.

Agentic Security is an open-source vulnerability scanner designed for safety scanning, offering customizable rule sets and agent-based attacks. It provides comprehensive fuzzing for any LLMs, LLM API integration, and stress testing with a wide range of fuzzing and attack techniques. The tool is not a foolproof solution but aims to enhance security measures against potential threats. It offers installation via pip and supports quick start commands for easy setup. Users can utilize the tool for LLM integration, adding custom datasets, running CI checks, extending dataset collections, and dynamic datasets with mutations. The tool also includes a probe endpoint for integration testing. The roadmap includes expanding dataset variety, introducing new attack vectors, developing an attacker LLM, and integrating OWASP Top 10 classification.

Gemini-OpenAI-Proxy is a proxy software designed to convert OpenAI API protocol calls into Google Gemini Pro protocol, allowing software using OpenAI protocol to utilize Gemini Pro models seamlessly. It provides an easy integration of Gemini Pro's powerful features without the need for complex development work.

The StepChat Free service provides high-speed streaming output, multi-turn dialogue support, online search support, long document interpretation, and image parsing. It offers zero-configuration deployment, multi-token support, and automatic session trace cleaning. It is fully compatible with the ChatGPT interface. Additionally, it provides seven other free APIs for various services. The repository includes a disclaimer about using reverse APIs and encourages users to avoid commercial use to prevent service pressure on the official platform. It offers online testing links, showcases different demos, and provides deployment guides for Docker, Docker-compose, Render, Vercel, and native deployments. The repository also includes information on using multiple accounts, optimizing Nginx reverse proxy, and checking the liveliness of refresh tokens.

Lego AI Parser is an open-source application that uses OpenAI to parse visible text of HTML elements. It is built on top of FastAPI, ready to set up as a server, and make calls from any language. It supports preset parsers for Google Local Results, Amazon Listings, Etsy Listings, Wayfair Listings, BestBuy Listings, Costco Listings, Macy's Listings, and Nordstrom Listings. Users can also design custom parsers by providing prompts, examples, and details about the OpenAI model under the classifier key.

Spark AI Free 服务 provides high-speed streaming output, multi-turn dialogue support, AI drawing support, long document interpretation, and image parsing. It offers zero-configuration deployment, multi-token support, and automatic session trace cleaning. It is fully compatible with the ChatGPT interface. The repository includes multiple free-api projects for various AI services. Users can access the API for tasks such as chat completions, AI drawing, document interpretation, image analysis, and ssoSessionId live checking. The project also provides guidelines for deployment using Docker, Docker-compose, Render, Vercel, and native deployment methods. It recommends using custom clients for faster and simpler access to the free-api series projects.

Qwen AI Free service supports high-speed streaming output, multi-turn dialogue, watermark-free AI drawing, long document interpretation, image parsing, zero-configuration deployment, multi-token support, automatic session trace cleaning. It is fully compatible with the ChatGPT interface. The repository provides various free APIs for different AI services. Users can access the service through different deployment methods like Docker, Docker-compose, Render, Vercel, and native deployment. It offers interfaces for chat completions, AI drawing, document interpretation, image parsing, and token checking. Users need to provide 'login_tongyi_ticket' for authorization. The project emphasizes research, learning, and personal use only, discouraging commercial use to avoid service pressure on the official platform.

Functionary is a language model that interprets and executes functions/plugins. It determines when to execute functions, whether in parallel or serially, and understands their outputs. Function definitions are given as JSON Schema Objects, similar to OpenAI GPT function calls. It offers documentation and examples on functionary.meetkai.com. The newest model, meetkai/functionary-medium-v3.1, is ranked 2nd in the Berkeley Function-Calling Leaderboard. Functionary supports models with different context lengths and capabilities for function calling and code interpretation. It also provides grammar sampling for accurate function and parameter names. Users can deploy Functionary models serverlessly using Modal.com.

GLM AI Free 服务 provides high-speed streaming output, multi-turn dialogue support, intelligent agent dialogue support, AI drawing support, online search support, long document interpretation support, image parsing support. It offers zero-configuration deployment, multi-token support, and automatic session trace cleaning. It is fully compatible with the ChatGPT interface. The repository also includes six other free APIs for various services like Moonshot AI, StepChat, Qwen, Metaso, Spark, and Emohaa. The tool supports tasks such as chat completions, AI drawing, document interpretation, image parsing, and refresh token survival check.

Senparc.AI is an AI extension package for the Senparc ecosystem, focusing on LLM (Large Language Models) interaction. It provides modules for standard interfaces and basic functionalities, as well as interfaces using SemanticKernel for plug-and-play capabilities. The package also includes a library for supporting the 'PromptRange' ecosystem, compatible with various systems and frameworks. Users can configure different AI platforms and models, define AI interface parameters, and run AI functions easily. The package offers examples and commands for dialogue, embedding, and DallE drawing operations.

E2M is a Python library that can parse and convert various file types into Markdown format. It supports the conversion of multiple file formats, including doc, docx, epub, html, htm, url, pdf, ppt, pptx, mp3, and m4a. The ultimate goal of the E2M project is to provide high-quality data for Retrieval-Augmented Generation (RAG) and model training or fine-tuning. The core architecture consists of a Parser responsible for parsing various file types into text or image data, and a Converter responsible for converting text or image data into Markdown format.

Groq2API is a REST API wrapper around the Groq2 model, a large language model trained by Google. The API allows you to send text prompts to the model and receive generated text responses. The API is easy to use and can be integrated into a variety of applications.

DeepSeek Free API is a high-speed streaming output tool that supports multi-turn conversations and zero-configuration deployment. It is compatible with the ChatGPT interface and offers multiple token support. The tool provides eight free APIs for various AI interfaces. Users can access the tool online, prepare for integration, deploy using Docker, Docker-compose, Render, Vercel, or native deployment methods. It also offers client recommendations for faster integration and supports dialogue completion and userToken live checks. The tool comes with important considerations for Nginx reverse proxy optimization and token statistics.

Gensokyo-llm is a tool designed for Gensokyo and Onebotv11, providing a one-click solution for large models. It supports various Onebotv11 standard frameworks, HTTP-API, and reverse WS. The tool is lightweight, with built-in SQLite for context maintenance and proxy support. It allows easy integration with the Gensokyo framework by configuring reverse HTTP and forward HTTP addresses. Users can set system settings, role cards, and context length. Additionally, it offers an openai original flavor API with automatic context. The tool can be used as an API or integrated with QQ channel robots. It supports converting GPT's SSE type and ensures memory safety in concurrent SSE environments. The tool also supports multiple users simultaneously transmitting SSE bidirectionally.

Emohaa AI Free API is a free API that allows you to access the Emohaa AI chatbot. Emohaa AI is a powerful chatbot that can understand and respond to a wide range of natural language queries. It can be used for a variety of purposes, such as customer service, information retrieval, and language translation. The Emohaa AI Free API is easy to use and can be integrated into any application. It is a great way to add AI capabilities to your projects without having to build your own chatbot from scratch.

Pro React Admin is a comprehensive React admin template that includes features such as theme switching, custom component theming, nested routing, webpack optimization, TypeScript support, multi-tabs, internationalization, code styling, commit message configuration, error handling, code splitting, component documentation generation, and more. It also provides tools for mock server implementation, deployment, linting, formatting, and continuous code review. The template supports various technologies like React, React Router, Webpack, Babel, Ant Design, TypeScript, and Vite, making it suitable for building efficient and scalable React admin applications.

Beelzebub is an advanced honeypot framework designed to provide a highly secure environment for detecting and analyzing cyber attacks. It offers a low code approach for easy implementation and utilizes virtualization techniques powered by OpenAI Generative Pre-trained Transformer. Key features include OpenAI Generative Pre-trained Transformer acting as Linux virtualization, SSH Honeypot, HTTP Honeypot, TCP Honeypot, Prometheus openmetrics integration, Docker integration, RabbitMQ integration, and kubernetes support. Beelzebub allows easy configuration for different services and ports, enabling users to create custom honeypot scenarios. The roadmap includes developing Beelzebub into a robust PaaS platform. The project welcomes contributions and encourages adherence to the Code of Conduct for a supportive and respectful community.

Microsoft Copilot for Security is a generative AI-powered assistant for daily operations in security and IT that empowers teams to protect at the speed and scale of AI.

AIL framework is a modular framework to analyze potential information leaks from unstructured data sources like pastes from Pastebin or similar services or unstructured data streams. AIL framework is flexible and can be extended to support other functionalities to mine or process sensitive information (e.g. data leak prevention).

Beelzebub is an advanced honeypot framework designed to provide a highly secure environment for detecting and analyzing cyber attacks. It offers a low code approach for easy implementation and utilizes virtualization techniques powered by OpenAI Generative Pre-trained Transformer. Key features include OpenAI Generative Pre-trained Transformer acting as Linux virtualization, SSH Honeypot, HTTP Honeypot, TCP Honeypot, Prometheus openmetrics integration, Docker integration, RabbitMQ integration, and kubernetes support. Beelzebub allows easy configuration for different services and ports, enabling users to create custom honeypot scenarios. The roadmap includes developing Beelzebub into a robust PaaS platform. The project welcomes contributions and encourages adherence to the Code of Conduct for a supportive and respectful community.

hackingBuddyGPT is a framework for testing LLM-based agents for security testing. It aims to create common ground truth by creating common security testbeds and benchmarks, evaluating multiple LLMs and techniques against those, and publishing prototypes and findings as open-source/open-access reports. The initial focus is on evaluating the efficiency of LLMs for Linux privilege escalation attacks, but the framework is being expanded to evaluate the use of LLMs for web penetration-testing and web API testing. hackingBuddyGPT is released as open-source to level the playing field for blue teams against APTs that have access to more sophisticated resources.

Tracecat is an open-source automation platform for security teams. It's designed to be simple but powerful, with a focus on AI features and a practitioner-obsessed UI/UX. Tracecat can be used to automate a variety of tasks, including phishing email investigation, evidence collection, and remediation plan generation.

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.

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.

HaE is a framework project in the field of network security (data security) that combines artificial intelligence (AI) large models to achieve highlighting and information extraction of HTTP messages (including WebSocket). It aims to reduce testing time, focus on valuable and meaningful messages, and improve vulnerability discovery efficiency. The project provides a clear and visual interface design, simple interface interaction, and centralized data panel for querying and extracting information. It also features built-in color upgrade algorithm, one-click export/import of data, and integration of AI large models API for optimized data processing.