driver-analysis

Semantic analysis engine for detecting vulnerability fixes in Windows kernel driver patches — 58 YAML rules, Ghidra decompilation, reachability tracing, and scoring

Type-2 Intel x86-64 hypervisor for Windows focused on tracing control-flow transitions out of obfuscated or virtualized kernel drivers at runtime with EPT

A comprehensive tool for analyzing windows driver vulnerabilities using IDA Pro plugins, C# GUI, and Python analysis Core Engine™

Scalable Windows kernel driver vulnerability analysis pipeline — Karton + MWDB + Ghidra, with dashboards, alerting, and driver monitoring

A tool that can help you develop and analyze Windows drivers.

Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python

Data Science Case Study: To help X Education select the most promising leads (Hot Leads), i.e. the leads that are most likely to convert into paying customers.

A simple writeup of an driver found in the LOLDrivers repository.

DriverSignal — open survey driver analysis. Scale reliability (Cronbach's alpha with bootstrap), robust standardized regression, LMG importance for correlated predictors, cross-validated diagnostics. Streamlit, local-first.

In the AI era, junior engineers may understand code line by line yet lack hands-on engineering intuition. `explain-c-module` explains embedded C/C++ modules, RTOS, drivers, interrupts, DMA, low-power flows, and call graphs, generating practical Markdown/HTML documentation with Claude Code and optional Codex Hook support.

Static-Analysis notes for the Android ARM64 kernel rootkit (mem_tool driver) -- IDA Pro walkthrough, ioctl map, stealth primitives, self-extracting loader dissection, and a from-source audit rebuild. Security research only -- not affiliated with the original author.

Tech Challenge of the Postgraduate in Data Analytics, from FIAP, analyzing Brent Oil price data, in comparison with historical, economic and societal data, integrating correlation and causality analyzes of items with prices, as well as developing a model forecast and an importance analysis through information gain from a forest model (XGBoost)

Helix is a hybrid predictive and driver intelligence engine that forecasts future business KPIs and explains why they will move. It combines statistical forecasting, machine-learning driver analysis, SHAP-based interpretability.

Leverage data analytics to identify "Hot Leads" and sculpt personalized strategies for maximum conversion potential, propelling X Education to new heights of success.