Portfolio

Cyber Forensics · Automation · Field Technology

Building practical tools for digital investigation.

I build practical tools and lab workflows for digital forensics, cyber investigation, AI-assisted automation and drone-based field operations.

My focus is on turning real investigative and technical workflows into structured, repeatable and documented systems.

Featured Projects · Tech Stack · Direction · Contact

Profile

I work at the intersection of cybercrime investigation, digital forensics, automation, private lab infrastructure and field technology.

My practical direction is simple:

  • build tools that reduce repetitive investigative work,
  • structure messy technical workflows,
  • document systems clearly,
  • use AI as a development accelerator,
  • keep human investigative judgment in control.

This portfolio intentionally avoids sensitive operational details. It describes skills, systems and tooling direction without exposing private infrastructure or live investigative procedures.

Core Focus

Digital Forensics

Windows triage, acquisition workflows, evidence packaging, hashing, reporting and investigator-focused leads.

Forensic Automation

Python, PowerShell, structured outputs, repeatable collection flows, reports and evidence manifests.

Private Cyber Lab

An anonymized self-hosted lab used for tool development, testing, monitoring, local AI and workflow documentation.

AI-assisted Development

LLMs are used as development copilots for code iteration, refactoring, documentation and testing support.

Drone / Field Technology

A growing field-tech track focused on legal drone operation, flight discipline, documentation habits and future OSINT/forensic use.

Fujin – Rapid Windows Triage Tool

A lightweight Windows triage utility for fast first-look system assessment and investigator orientation.

Value: fast orientation, repeatable checks, readable output, follow-up leads.

Status: work in progress.

Open case study ->

Raijin – Full Forensic Acquisition Assistant

An extended forensic acquisition assistant for structured evidence export, hashing, reporting and evidence packaging.

Value: clean evidence structure, SHA256 manifest, investigator-readable reports.

Status: work in progress.

Open case study ->

Private Cyber-Forensic Lab

An anonymized self-hosted lab used for forensic tooling, local AI, automation, monitoring and remote access workflows.

Value: controlled testing environment, local AI support, repeatable infrastructure.

Open case study ->

Drone Log – Field Technology Track

A structured training log for drone operation, pilot discipline, documentation habits and future field workflows.

Value: training discipline, documented progress, future field-tech foundation.

Mini Project

BICHEZ Importer

A practical automation project for preparing SQL imports for an editorial publishing database.

It reduced a manual workflow from one to two days to approximately ten minutes plus review time.

This project is included as a mini project because it demonstrates the ability to turn a messy real-world workflow into a repeatable automation process.

Open mini case study ->

Lab Model

The lab is documented publicly only at a high level.

Sensitive details such as real IP addresses, private hostnames, exact routing and operational information are intentionally omitted.

General model:

  • Internet-facing edge layer,
  • private VPN backbone,
  • lab server,
  • Windows workstation,
  • local AI node,
  • monitoring and knowledge services.

The lab supports forensic tool testing, automation workflows, local AI-assisted development, documentation and field-technology experiments.

AI-assisted Development Workflow

I use LLMs as development copilots, not as a replacement for technical judgment.

My role in the workflow:

  • define the operational purpose,
  • describe the forensic or automation value,
  • design the expected output,
  • test the tool in real environments,
  • validate whether the result is useful for investigation or operations,
  • document the workflow,
  • identify limitations and next steps.

The AI accelerates implementation, refactoring and documentation.

The investigative logic and final validation remain human-led.

Tech Stack

Investigation and tooling

  • Windows forensics
  • PowerShell
  • Python
  • evidence reports
  • hashing and manifests
  • OSINT workflows
  • SQL automation

Infrastructure

  • Linux
  • Docker
  • Traefik
  • WireGuard
  • Netdata
  • Hugo
  • private lab services
  • self-hosted documentation

AI and automation

  • local AI
  • Ollama
  • LLM-assisted coding
  • workflow design
  • report drafting
  • structured documentation

Field technology

  • drones A1/A3
  • training log
  • field documentation
  • future FPV / DJI workflow
  • possible 3D-printed accessories

Direction

I am developing a profile at the intersection of:

digital forensics, cybercrime investigation, AI-assisted automation, private lab infrastructure and field technology.

The long-term goal is to build practical tools and workflows that help investigators and technical teams collect, structure, understand and document digital evidence more effectively.

What I am looking for

I am interested in roles and projects where I can combine investigation, technical systems, automation and field technology.

The best fit is work connected to:

  • digital forensics,
  • cybercrime investigation,
  • forensic automation,
  • OSINT workflows,
  • Windows artifact collection,
  • AI-assisted technical tooling,
  • private lab and infrastructure operations,
  • drone and field-technology workflows,
  • defense, security or public-safety technology.

I am especially interested in practical work where tools are built for real operational needs.

The direction I want to grow into:

forensic automation specialist / cyber-forensic technologist / field-tech investigator.

I am not trying to become only a traditional software developer.

My strongest position is between investigation and engineering:

  • understanding the operational problem,
  • defining what a tool should collect or produce,
  • testing it in realistic conditions,
  • validating whether the output helps an investigator,
  • documenting the result clearly,
  • using AI and automation to accelerate development.

The long-term goal is to build practical systems that help people collect, understand and document digital evidence faster and more reliably.

Contact

This portfolio is intended as a technical overview for CVs, interviews and professional discussion.

Sensitive operational details are intentionally excluded or anonymized.