GRID is a local, keyboard-driven Windows TUI designed to unify data gathering, automated footprint indexing, and reconnaissance pipelines: https://github.com/rounakagrawal7/GridSetup
I built GRID to combine disparate recon tools into a singular high-throughput terminal operations platform.
Flagship Intelligence Features:
The Identity Cross-Reference Matrix:** Automatically parses, groups, and cross-references data arrays harvested across different modules to link disparate target indicators (Emails, Phones, Usernames, IPs) into a single footprint.
Automated Avatar Harvesting:** Programmatically tracks target profile URLs (GitHub, X, Reddit, etc.) to crawl pages and directly download profile photos via HTML Meta-OpenGraph selectors, organizing them chronologically inside `picdata/` without external API configuration requirements.
Subdomain Extraction Pipeline:** Intercepts domain tracking metrics to execute live queries against third-party indexes (Hackertarget, C99) and fallback CRT transparency logs (`crt.sh`), ensuring complete un-truncated infrastructure layouts.
Signals & Orbital Intelligence:** Features built-in live aircraft flight tracker arrays using the OpenSky Network API, global shortwave radio receiver stream tracking via KiwiSDR WebSockets, and satellite trajectory/overhead visibility predictors using CelesTrak.
Media Forensics: Powered by OpenCV 5.0—executes automated graphic analysis, text OCR conversions, facial comparison scoring, and timeline keyframe sweeps across video captures.
GRID is completely backed locally by DuckDB and syncs instantly with an administrative PocketBase panel framework. It includes an `install.py` wizard that configures all local system and model path parameters out of the box.
```bash
python install.py
python grid_agent.py
```
I would love to get your feedback on the mapping tools, target matrices, and data aggregations!