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Shastra- Security Vulnerability Scanner
SHASTRA is a lightweight and efficient security scanner focused on helping developers and security teams detect vulnerabilities early. Designed with simplicity and precision, SHASTRA offers the following core features: 🔹 Source Code Analysis: SHASTRA scans through source code to identify common security flaws such as SQL Injection, Cross-Site Scripting (XSS), and Sensitive Data Exposure using carefully crafted regex patterns. It inspects code for risky constructs, insecure coding practices, and sensitive information leaks. 🔹 Server Log Analysis: Beyond static code review, SHASTRA analyzes server log files to detect suspicious behaviors, unauthorized access patterns, error leaks, and exposure of critical information that may compromise the system’s integrity. 🔹 Regex-Based Vulnerability Detection: SHASTRA uses powerful regular expressions to quickly detect vulnerabilities without needing heavy or resource-intensive engines. This allows fast, targeted scanning with minimal setup or overhead. 🔹 User-Friendly Streamlit Interface: The tool is powered by Streamlit, offering a clean and interactive web-based dashboard. Users can easily upload files, trigger scans, and view results in an organized and visual format without dealing with complex command-line operations. 🔹 Detailed Reporting: After scanning, SHASTRA generates detailed and easy-to-understand reports highlighting vulnerabilities, their potential impact, and code snippets/log entries where issues were detected, aiding faster debugging and patching. 🔹 Lightweight and Fast: Designed to be minimalistic, SHASTRA delivers quick scanning without bloating your development environment. Its lightweight architecture ensures that security checks can be easily integrated into any workflow. 🔹 Extensible and Maintainable: SHASTRA’s pattern-matching engine is modular, allowing developers to extend the tool by adding new regex patterns or rules as new vulnerabilities emerge or project-specific needs arise.
1 May 2025
AI-Powered Network Guardian
Our project, AI-Powered Network Guardian, is a prototype designed to enhance the scalability and sustainability of public sector networks. It leverages AI and automation to provide predictive maintenance, real-time monitoring, and cost optimization for network infrastructure. Using machine learning models, it can detect anomalies, predict potential failures, and recommend proactive solutions to minimize downtime and reduce operational costs. We have integrated Streamlit for an interactive dashboard that visualizes network health, alerts, and optimization insights. Currently, this is a prototype running on simulated data, demonstrating the feasibility of AI-driven network management. Future iterations can incorporate real-time data, advanced AI models, and broader integrations to support large-scale public sector infrastructure.
2 Mar 2025
