Network packet sniffer and analyzer with ML classification, real-time GUI, and intrusion detection capabilities
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Updated
Jul 13, 2025 - Python
Network packet sniffer and analyzer with ML classification, real-time GUI, and intrusion detection capabilities
Machine learning-enhanced DNS tunneling detection system achieving 100% accuracy across multiple tunneling tools
Self-hosted honeypot and threat-intelligence platform. Native sensors score attackers across your WAN IPs, so an IP that hits more of them weighs more. Only on operator approval are confirmed-real sources reported to abuse vendors and published as a firewall blocklist. Rust, PostgreSQL, event-sourced. Single node or cluster.
Passive IDS/SIEM-lite lab (Suricata) on real Cisco/Fortinet/Proxmox hardware — Suricata detecting live EICAR transfers and port scans
UNSW-NB15 network traffic classification using a CART decision tree built from scratch. NumPy, no scikit-learn. Coursework companion to my SOC lab.
An original firewall built on real math — provably consistent rules and a tunable, proven bound on false positives.
AI-Powered Network Intrusion Detection System (NIDS) - An unsupervised ML approach to detecting DDoS attacks, port scans, and network anomalies using Isolation Forest.
Real-time network intrusion detection system built in Python using Scapy. Detects port scanning, traffic spikes, and ICMP floods.
A lightweight, high-performance host-based intrusion detection agent (HIDS) built in Go with real-time monitoring and HMAC-secured baselining.
Clean-room Python reimplementation of PARD-SSM (arXiv 2604.02299): attacks as regimes, not anomalies. Regime-switching state-space intrusion detection with KL-gated kill-chain alerts, a reproduction harness, and pre-registered acceptance bands. The paper's code link is a 404.
Packet analyzer in C (libpcap) that decodes Ethernet, IPv4, TCP, UDP and ICMP by hand, verified field-by-field against Wireshark. Growing into a lightweight network intrusion detector.
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