GitHub Trends

#other#cti#cyberhunter#darkweb#deepweb#threat_intelligence deepdarkCTI is a free project that collects and shares cyber threat intelligence (CTI) from the deep and dark web, helping you stay aware of hidden cyber threats like stolen data, ransomware, and hacker activities. It gathers information from places like Telegram, Discord, hacker forums, and ransomware sites to provide useful indicators and patterns of cyber attacks. You can join their Telegram group to discuss and suggest new sources or support the project with donations. Using deepdarkCTI helps you detect threats early, improve your cybersecurity decisions, and protect your organization from cyber attacks more effectively. https://github.com/fastfire/deepdarkCTI

#other This collection of leaked GPT prompts offers a wide range of tools and ideas for interacting with AI models. It includes prompts for tasks like writing, coding, humor, and education, which can help users understand how GPT models work and improve their interactions with AI. By using these prompts, users can create more effective and personalized AI experiences, benefiting from the diverse contributions and insights shared by the community. This resource is valuable for both developers and users looking to enhance their AI interactions. https://github.com/linexjlin/GPTs

#other You can use a set of markdown files to guide AI coding assistants step-by-step in building software features. This method breaks down your feature idea into a clear Product Requirement Document (PRD), then into detailed tasks, and finally lets the AI work on each task one at a time while you review and approve progress. This structured workflow helps you keep control, avoid errors, and track progress visually, making AI-assisted development more reliable and manageable. It works with many AI tools and improves the quality and clarity of AI-generated code, saving you time and reducing frustration during complex feature development. https://github.com/snarktank/ai-dev-tasks

#other#ai#anthropic_claude#awesome#context#mcp#model_context_protocol#servers#tool_use#tools Model Context Protocol (MCP) is an open standard that lets AI models securely connect to various data sources and tools, like files, databases, APIs, and cloud services, to get real-time, relevant information. This helps AI give more accurate, up-to-date, and context-aware answers, reducing repeated data processing and improving efficiency. MCP also supports automation of complex workflows and integration with many platforms, making AI more powerful and flexible. However, running MCP servers requires careful security measures to avoid risks like unauthorized code execution. Using MCP can save time, reduce costs, and enhance AI capabilities for tasks like chatbots, data analysis, and system control. https://github.com/appcypher/awesome-mcp-servers

#other Cognitive load is the mental effort needed to understand and work with code. Since our brain can only hold about four pieces of information at once, complex code with many conditions, deep inheritance, or too many small modules increases this load, making it harder to understand and maintain. To reduce cognitive load, use clear, meaningful variable names, prefer composition over inheritance, avoid too many tiny modules, and keep interfaces simple. Also, avoid excessive abstractions, tight coupling with frameworks, and overly complex architectures. Lower cognitive load helps you and your team understand code faster, reduce bugs, and be more productive. https://github.com/zakirullin/cognitive-load

#other This guide helps you prepare for software engineering technical interviews by covering key topics like good coding practices (SOLID principles, DRY, Clean Code, Clean Architecture), algorithms and data structures, design patterns, system design, databases, version control, CI/CD, containers, and AI tools. It offers practical resources and examples for many programming languages and frameworks, plus common interview questions for frontend and backend roles. Using this guide improves your coding skills, helps you understand important concepts, and boosts your confidence to perform well in interviews and real projects. It saves you time by gathering essential knowledge and practice materials in one place. https://github.com/DevCaress/guia-entrevistas-de-programacion

#other#automation#automation_templates#integration#n8n#n8n_automation#n8n_template#no_code_ai#no_code_automation#workflow_automation You can use a large collection of ready-made automation templates for n8n, an open-source, low-code workflow automation tool that connects over 350 apps. These templates help automate tasks like email labeling, social media posting, document processing, chatbots, and data analysis without needing to build workflows from scratch. This saves you time and effort by letting you quickly implement smart automations for business, marketing, support, and more. n8n’s visual editor and AI integrations make it easy to customize workflows, improving your productivity and operational efficiency with minimal coding. https://github.com/enescingoz/awesome-n8n-templates

#other The FFmpeg School of Assembly Language teaches you how assembly code is written in FFmpeg, helping you understand what happens inside your computer. To join, you should know C programming (especially pointers) and basic high school math. The lessons include assignments and a Discord server for questions. By completing them, you can contribute to FFmpeg, a powerful video processing tool that uses assembly to speed up tasks dramatically—sometimes up to 94 times faster with special instructions like AVX-512. Learning this helps you write highly efficient code for video and multimedia processing, improving performance in real-world applications. https://github.com/FFmpeg/asm-lessons

#other#agent#ai#artificial_intelligence#autogpt#autonomous_agents#awesome#babyagi#copilot#gpt#gpt_4#gpt_engineer#openai#python Codeium is a free AI-powered coding assistant that helps you write code faster and better by providing real-time autocomplete suggestions, generating code from natural language, explaining code, and assisting with refactoring. It supports over 70 programming languages and integrates with many popular IDEs like Visual Studio Code. Codeium learns from your coding style and project context to offer relevant suggestions, saving you time and reducing errors. It also includes a chat feature to answer coding questions instantly, so you don’t need to switch to a browser for help. This boosts your productivity and code quality efficiently. https://github.com/e2b-dev/awesome-ai-agents

#other#awesome#awesome_list#flipper_zero#flipperzero The Flipper Zero is a small, portable device that can read, copy, and emulate many types of access controls like RFID, NFC, radio remotes, and iButtons without needing a computer or phone. It has built-in tools like a Sub-1 GHz transceiver, infrared module, and GPIO pins, letting you control smart home devices, test security systems, and automate tasks. You can expand its functions with apps, custom firmware, and plugins. This makes it useful for learning electronics, hacking ethically, and managing IoT devices, giving you a versatile tool for tech projects and security testing[2][3][4][1]. https://github.com/djsime1/awesome-flipperzero

#other#bluetooth#bt#coding#cybersecurity#diy#electronics#esp32#flashing#hacker#hacking#jammer#nrf24#programming The ESP32-BlueJammer is a device that disrupts all wireless signals operating on the 2.4 GHz frequency, including Bluetooth, BLE, WiFi, RC drones, and many smart gadgets. It uses an ESP32 chip combined with nRF24 modules to create noise and send unnecessary packets, effectively jamming these signals within a range of over 30 meters, which can be extended with better antennas or amplifiers. This jammer is intended strictly for educational and security testing purposes to help understand and improve wireless security. It is illegal to use for malicious purposes, so it should be handled responsibly and legally[1][2][3]. https://github.com/EmenstaNougat/ESP32-BlueJammer

#other#ai_agents#genai You can explore a large collection of AI agent projects and use cases across many industries like healthcare, finance, education, customer service, and more. These AI agents automate tasks such as medical diagnosis, stock trading, personalized tutoring, customer support, product recommendations, and supply chain optimization. The projects include open-source code and frameworks like CrewAI, Autogen, Agno, and Langgraph, which help build, manage, and collaborate AI agents for tasks like coding, multi-agent teamwork, data analysis, and workflow automation. Using these resources can save you time, improve efficiency, and inspire you to create AI solutions tailored to your needs. https://github.com/ashishpatel26/500-AI-Agents-Projects