Voldigoade
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About
I mostly build tools that give me a good excuse to understand what actually happens under the hood: Rust CLIs, OSINT, firmware, privacy, and systems. I like starting from a concrete behavior, tracing it back to how it really works, testing edge cases, and keeping only what can be verified. The code ends up on GitHub, the research and write-ups live here.
Focus
Rust / CLI
Command-line tools: strict typing, clean error handling, and standalone binaries.
OSINT / Privacy
Public footprint inspection, metadata exposure analysis, and encrypted protocol studies.
Firmware / Reverse
Semantic diffing of extracted firmware rootfs trees, file hierarchy inspection, and artifact extraction.
Local-First
Standalone tools running locally without constant dependencies on external cloud services.
What I Use
Rust
The first language I chose to learn seriously. I use it mostly for CLI tools, systems utilities, and backends where I want control, strict typing, and a standalone binary.
Linux
My daily environment to develop, test, automate, and understand what is actually happening on the machine.
Python
The go-to choice for quick scripts, parsing, data analysis, and small tools where getting a fast result matters more than building a binary.
TypeScript / Next.js
For web apps and interfaces: front-end, data integration, and anything that needs to run cleanly in a browser.
Public Repositories
View on GitHubRust CLI to inspect what a GitHub account or repository exposes publicly: commits, keys, and metadata.
- Distinguishes observed facts from derived values and inference boundaries.
- Embedded HTTP service, structured JSON export, and local SQLite cache.
- Designed to respect GitHub API rate limits and explicitly document query limits.
Rust prototype to compare two extracted Linux firmware rootfs trees and produce clean diff reports.
- Semantic comparison of directory hierarchies and file trees.
- Deterministic plain-text and JSON output formats.
- Experimental open-source project under active development.
Methodical comparison of secure messaging apps evaluated across threat models, metadata exposure, and audits.
- Covers Signal, SimpleX, Session, Olvid, Threema, and Briar.
- Examines network traces, central server architecture, and pseudonymity.
- Backed by primary sources, security advisories, and public audits.