CTF kernel exploitation notes, PoCs, exploits, and writeups.
Readers and converters for Soil Moisture Active Passive (SMAP) data.
This is a package to access the ClimateSERV API
AI-powered passive network reconnaissance & threat intelligence dashboard for Smap (Shodan-based Nmap alternative) with SQLite, Grafana, CVSS scoring, CPE fingerprinting, host tagging, and risk analysis.
SMAP projekt Fuzzy předpověď počasí
A human-first SV annotation snakemake pipeline based on nanotatoR working with optical mapping (Bionano Genomics) data
Kernsec is quick & dirty script to print kernel protections, useful informations of kernel exploitation/pwn in Kernel Land
Archive of Processing Code and Support Files for NASA/RSS SMAP Salinity Version 5.0 Validated Release
wmap is a modern, user-friendly network scanner and reconnaissance tool written in Go. It helps you discover live hosts, scan for open ports and services, identify running software and versions, check for vulnerabilities, and generate detailed reports—all with a focus on simplicity and flexibility.
SWAT-SMAP ensemble Kalman filter data assimilation framework: offline EnKF with CDF matching and tuning, a coupled SWAT2012 EnKF build driven from Python, and diagnostic analyses. Marshall et al. (2026), Journal of Hydrology, doi:10.1016/j.jhydrol.2026.136599
Archive of Processing Code and Support Files for NASA/RSS SMAP Salinity Version 5.0 Validated Release
Hydrology plugin for Open Science Pillars: SWOT river and lake levels, GRACE-FO groundwater, USGS NWIS streamflow, SMAP soil moisture, and an applied water-resources pack for drought and reservoir analysis. In active development.
PyTorch U-Net bias-correction layer for the Noah-MP land surface model — predicts SMAP satellite soil moisture during droughts and hurricanes. Code for Mbarak et al., Machine Learning: Earth (2026).
Sub-seasonal forecasting of cropland productivity anomalies from satellite soil moisture with a ConvLSTM (VIIRS NIRv, SMAP RZSM).
Anomaly detection in NASA SMAP spacecraft telemetry using PCA, Random Forest, MLP, and LSTM models. Comparison of forecasting and reconstruction approaches with dynamic thresholding and sequence-level evaluation.
This repository contains the source code used in the experiments of the Master's Thesis
KARZOUN-X — Open research on resource-aware, safety-gated local AI for autonomous spacecraft fault diagnosis under delayed or unavailable Earth communication.
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