🗝️ The Voidweaver's Trail: Season 1 Investigation Reports for Echo Response. Uncovering hidden identities and securing the Nullform Key across the Cyber Realm via advanced forensics and cryptanalysis.

Analysis and Visualization of network traffic from data centres based on trace.pcap file.

C2 Framework Fingerprinter: identifies Cobalt Strike, Metasploit, Sliver, Havoc, Covenant, Brute Ratel from PCAP traffic using beacon analysis, URI patterns, JA3, and HTTP headers

AirSentinel is a Python-based cross-platform tool with a PyQt5 GUI for live Wi-Fi scanning and offline PCAP analysis. It detects network details, assigns risk levels, and exports results in JSON, Markdown, or PDF, making it valuable for cybersecurity research and testing.

Python network forensics tool that detects C2 beaconing, port scans, data exfiltration, DNS tunneling, and 20+ threat patterns in PCAP files. Behavioral analysis for the encrypted traffic era. Every finding maps to MITRE ATT&CK.

A comprehensive web application for replaying network packet capture (PCAP) files using tcpreplay. Built with React frontend, Flask backend, and fully containerized with Docker.

Sniffing network traffic with Python for real-time or PCAP analysis.

A command-line companion for in-depth network traffic analysis, enabling security insights and statistical overview from PCAP files.

A lightweight Python tool for sniffing and analyzing embedded network traffic, featuring signature-based anomaly detection for MQTT and Modbus TCP protocols.

Machine learning-enhanced DNS tunneling detection system achieving 100% accuracy across multiple tunneling tools

AEGIS-Omega is a high-performance, hybrid multi-layer Intrusion Detection System (IDS). It features a 4-layer detection strategy—Signature Analysis, Autoencoder Anomaly Detection, BiLSTM Deep Learning, and Ensemble Fusion—to identify attack types with 95% F1-score. Includes a FastAPI backend, React dashboard, and PCAP,Netflow analysis.

Professional VoIP diagnostic tool - Analyzes PCAP files and detects one-way audio, NAT issues, call quality problems

AI-Powered Anomaly Detection System for Network Security. Features a real-time data pipeline for raw PCAP traffic and ML models (Decision Tree, Random Forest, TensorFlow MLP) for detecting attacks.

Análisis de tráfico de red usando Wireshark y K-means en Python. Clasificación de paquetes en clusters y generación de informes automatizados.

ShadowParse is a high-fidelity PCAP forensics engine designed for automated deep packet inspection and cryptographic discovery. Developed to streamline CTF investigations and network traffic analysis, it features the DeepRead Integration for recursive decoding of obfuscated payloads.

Analyze pcap file for specified SSIDs and report PMF status

Localhost cybersecurity project simulating Port Scan & Brute Force attacks with automated PCAP detection and SOC-style reporting.

Personal learning project for mastering vulnerability testing, network security analysis, and DevOps automation using Breaking Point, Python, AWS, and Terraform

Network Analysis Tool developed as part of the CAC-H topic under SRI's CHALO project

A real-time network intrusion detection system with GUI built using Python, Flet, and Scapy. Features advanced threat detection including ICMP/DNS tunneling, protocol anomalies, blacklisted entities, and suspicious traffic patterns. Supports live packet capture and PCAP file analysis with interactive filtering and flow visualization.