aviation-security

Python scripts for pentesting, red teaming, and protocol analysis of OT / IoT / ICS systems - ADS-B, AIS, BACnet, ARINC 429, MIL-STD-1553, SCADA, PLC, GNSS, and more.

EursiaAero AD/CN Explorer – EASA Airworthiness Directives & Consignes de Navigabilité

Controlled, RF-isolated GPS/GNSS spoofing demonstration using HackRF One, GPS-SDR-SIM & NASA ephemeris — analyzing aviation security risks (ADS-B, FMS) and anti-spoofing countermeasures. For education & defensive research only.

Real-time ADS-B/AIS spoofing, anomaly & GPS-jamming detection dashboard

Exploratory detection engineering project using timing analysis to investigate anomaly signals in decoded ACARS/VDL2 data.

Config files for my GitHub profile.

Rule-based UEBA pipeline for aviation insider threat detection. Generates ~180K synthetic logs, scores risk per employee with compound event detection, runs Sigma rules, and visualises everything on a live Streamlit dashboard. No SIEM required.

Real-time aircraft tracking by passively receiving and decoding 1090 MHz ADS-B / Mode S Extended Squitter with HackRF One — on PC (SDRangel/DragonOS) and standalone on a PortaPack H2+ (Mayhem), including by-hand DF17 frame + CPR position decoding. Receive-only.

Cross-layer threat model of GNSS-independent LEO multilateration for air traffic surveillance: 55-threat catalogue, 78-source evidence atlas, blind 4-LLM review panel, and reproducible analysis code.

Can I Carry This On Board? AI-powered airport self-service kiosk using Azure OpenAI GPT-5.4 to check if items are allowed in cabin baggage based on ICAO rules. Built with FastAPI.

Reveal Imaging — independent third-party profile of a public API surface, by API Evangelist. Reveal Imaging (Reveal Imaging Technologies) is a security-screening hardware company known for CT-based explosives-detection and checkpoint screening systems for aviation and critical infrastructure. Founded around 2002 and backed by General Catalyst since

Analyzing US flight disruption data to identify operational risk patterns in aviation

A hybrid IDS for aircraft is proposed using Random Forests, Isolation Forests, YARA rules, and import hashing within a zero-trust architecture. Evaluated in a virtualized multi-zone testbed, it achieves high accuracy across six aviation datasets with low resource use, enabling practical onboard cybersecurity.