Hello everyone! I’m Karanveer Singh, and welcome to my DevLog! This is my space where I share my journey through the fascinating world of IT, cybersecurity, ethical hacking, Linux, and much more. Ever since I first tinkered with computers, I’ve been captivated by how technology works—from building systems from scratch to understanding the intricate details of digital security. My passion for cybersecurity has driven me to explore ethical hacking and system administration, and now I want to bring you along on that journey. ...
Detailed Guide on Aircrack-ng Suite
Introduction Aircrack-ng is a powerful suite of tools designed for auditing wireless networks. It’s widely used for testing the security of Wi-Fi networks by recovering WEP and WPA/WPA2 keys from captured packets. This guide covers everything from installation to executing attacks for educational and authorized penetration testing purposes. Table of Contents Prerequisites Installation Enabling Monitor Mode Packet Capturing with Airodump-ng Deauthentication Attacks with Aireplay-ng Cracking WPA/WPA2 Handshakes with Aircrack-ng Cracking WEP Networks Additional Tools and Techniques Best Practices & Troubleshooting Additional Resources Prerequisites Operating System: A Linux distribution (Kali Linux is highly recommended). Hardware: A wireless adapter that supports monitor mode and packet injection. Knowledge: Familiarity with Linux terminal commands. Permissions: Legal authorization to test the target network. Installation On Kali Linux (Pre-installed) Kali Linux comes with Aircrack-ng pre-installed. To update or reinstall: ...
GPT-4 API Key For Free
Introduction This guide explains how to obtain a free API key for OpenAI’s GPT-4 through GitHub Marketplace. This allows developers to access GPT-4 for free within the limitations set by GitHub. Steps to Get the API Key 1. Sign in to GitHub Ensure you have a GitHub account. If you don’t have one, create an account at GitHub. 2. Access GitHub Marketplace Go to the GitHub Marketplace. Search for “GPT-4 API” or “OpenAI API.” Click on the model you want 3. Generate a API Key Click on GPT-4 On the right side click on Get API Key to get the api key 4. Generate a github token After clicking on the option, click on Get Developer Key next to the github option. Click on Generate New Token and then click on the Generate New Token (Classic) option. Just specify a Note for the token and then skip rest of the options Finally Click on Generate Token to generate it! Your API key will be displayed and then just copy it! Usage of API Key Once you have the API key, you can use it in your projects or use the given example code with python Limitations & Considerations Usage Limits: Free tiers may have request limits (e.g., X requests per minute) you can check the official github documentation. Terms & Conditions: Always check GitHub Marketplace terms to ensure compliance. Conclusion By following these steps, you can access GPT-4 via GitHub Marketplace without any cost, within the provided limits. Always keep an eye on changes to the free tier offerings. ...
IoT Project
Introduction This project integrates a Programmable Logic Controller (PLC) with ThingsBoard, an open-source IoT platform, to monitor and control industrial processes. The project leverages Python for automation, the ThingsBoard Rule Engine for real-time data processing, and a combination of sensors and actuators for industrial applications. Objectives Establish a reliable connection between a PLC and ThingsBoard. Use ThingsBoard dashboards for real-time monitoring and control. Implement automation using Python and the ThingsBoard Rule Engine. Enable remote accessibility and data visualization. Components Used PLC: For industrial control logic. ThingsBoard: IoT platform for data visualization and processing. Python: For automation and scripting. Networking: MQTT or HTTP for data transmission. Implementation Steps 1. Setting Up the PLC Configure the PLC with necessary input/output modules. Define logic using ladder programming or structured text. 2. Connecting PLC to ThingsBoard Use MQTT or HTTP API to send data from PLC to ThingsBoard. Configure ThingsBoard device and telemetry settings. 3. Creating a Dashboard Design a custom dashboard in ThingsBoard. Add widgets for data visualization (gauges, charts, control buttons). 4. Implementing Automation Use the ThingsBoard Rule Engine to set up alarms, triggers, and automation. Implement Python scripts for data processing and additional automation. 5. Testing and Deployment Verify data transmission from PLC to ThingsBoard. Test remote control features and automation. Deploy the system in an industrial environment. Challenges and Solutions Network Latency: Optimized MQTT settings for stable communication. Data Accuracy: Implemented filtering mechanisms to reduce noise. Security: Used authentication and encryption for secure data transfer. Conclusion This project successfully demonstrated the integration of a PLC with ThingsBoard for industrial IoT applications. The system provides real-time monitoring, automation, and remote accessibility, making it a robust solution for industrial automation needs. ...