PYTHONPRIMARY
Python
Main application language across the strongest repositories, including TraceForge and Astra Engine.
CLI applications · async automation · packaging · analysis workflows
01 / TECHNOLOGY STACK
Tools I actually use to build things.
A project-backed view of my stack. Rather than percentage bars, this page shows languages, runtimes, data systems and engineering tools where there is public repository evidence behind them.
02 / QUICK INDEX
Find the layer you care about.
03 / LANGUAGES
The languages behind the projects.
Not a scorecard. A practical map of where each language has a role.
GOSYSTEMS
Go
Used for focused compiled paths where compute- and I/O-heavy work benefits from native binaries.
hashing · filesystem scanning · streaming extraction
BASHSYSTEMS
Bash
Used for setup, dependency installation, platform detection and system-level workflows.
bootstrap scripts · platform tooling · release helpers
JAVASCRIPTAUTOMATION
JavaScript / Node.js
Present in the WhatsApp automation side of the project set and used for browser/media-oriented integrations.
event-driven automation · media bridge · web runtime
04 / RUNTIME & AUTOMATION
Where the code meets a real runtime.
Tools selected because they solve concrete project problems, not because they look good on a badge wall.
PLAYWRIGHTBROWSER
Playwright
Astra Engine drives a real browser for WhatsApp Web automation rather than a reimplemented protocol.
browser automation · async workflows · Chromium
ASYNCIOPYTHON
Async Python
Astra is typed around asynchronous messaging and event-driven workflows.
event loop · async handlers · typed APIs
CLIWORKFLOWS
Command-line tooling
TraceForge is structured as a local CLI with cases, modules, exports and diagnostics.
commands · case workspaces · diagnostics · reporting
05 / DATA
Data systems used where they fit.
Storage choices are project-driven: embedded storage for local tools, document data where flexibility matters.
SQLITELOCAL
SQLite
Used as a lightweight local data layer where an embedded database makes sense.
local persistence · zero-service setup
MONGODBDOCUMENT
MongoDB
Used in automation projects where session/state data benefits from document storage.
sessions · persistent state · cloud URI support
SQLFUNDAMENTAL
SQL
Relational querying remains part of the broader data toolkit where structured storage is appropriate.
queries · relational thinking · local databases
AIOSQLITEASYNC
Async SQLite
Astra lists aiosqlite as a dependency for asynchronous SQLite access.
async data access · Python
06 / ENGINEERING TOOLING
The boring tools that keep projects maintainable.
Packaging, tests, linting, documentation and release workflows are part of the stack too.
TOOLROLEPROJECT EVIDENCE
Git / GitHubsource control · issues · releasespublic repositories
pytesttestingTraceForge / Astra development configs
Rufflinting / formattingAstra development tooling
mypystatic typingAstra development tooling
setuptoolsPython packagingTraceForge / Astra package metadata
PyPIpackage publishingTraceForge package
Sphinx / ReadTheDocsdocumentationTraceForge / Astra docs
build / twinerelease workflowPython package development
openpyxl / python-docxreporting exportsTraceForge optional reporting deps
07 / SECURITY & INVESTIGATION
The part of the stack I’m pushing deeper.
Security is represented through real tooling and project direction rather than expertise percentages.
TRACEFORGEFLAGSHIP
OSINT / DFIR / security tooling
Local investigative workflows around IOC extraction, evidence hashing, timeline processing, filesystem baselines, case management and structured exports.
IOC extractionevidence hashingtimeline processing
filesystem baselinescase managementSTIX / MISP
Inspect TraceForge ↗
DIRECTION 01Build first
Projects are how concepts become durable skills.
DIRECTION 02Stay specific
Use evidence from the repository instead of inflated skill claims.
DIRECTION 03Keep learning
The stack should change as the cybersecurity focus gets deeper.
08 / PRACTICE
How the stack is actually chosen.
A compact explanation of the engineering choices behind the projects.
Fit the problem
Python handles application logic and workflows; Go is reserved for focused native fast paths.
Prefer local-first
Security and utility workflows should keep data local whenever the problem allows it.
Document the work
README files, package metadata and documentation are part of the project, not an afterthought.
Keep the stack replaceable
A technology is useful because it solves a real problem, not because it is fashionable.