Aman Kumar Pandey
BCA Student Developer · Software, Systems Automation & Security Tooling
Location: India
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Email: paman7647@proton.me
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GitHub: github.com/paman7647
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Portfolio: amanpandey.me
Profile
BCA student developer based in India with practical experience architecting Python automation tools, local-first command-line utilities, and open-source forensics tooling. Focused on understanding systems from the ground up: writing efficient streaming I/O buffers, managing asynchronous event loops, analyzing raw network traffic with tshark/Wireshark, and building software that runs 100% locally without cloud leaks.
Education
Bachelor of Computer Applications (BCA)
Coursework: Data Structures & Algorithms, Object-Oriented Programming, Database Management Systems (DBMS), Operating Systems, Computer Networks
Focusing on core computer science foundations, systems programming, network protocol analysis, and applied software security.
Technical Skills
Languages:
Python 3 (AsyncIO, Multiprocessing, Socket, Re), Bash Shell Scripting, SQL (SQLite WAL Mode), JavaScript (Node.js, ES6+), PowerShell
Systems & OS:
macOS (Apple Silicon / Darwin zsh), Linux (Kali Linux 2026, Debian, Ubuntu), Systemd Daemons, Docker Containers, Termux
Security & DFIR:
SHA-256 Evidence Custody, IOC Defanging & Extraction, STIX 2.1 Threat Bundling, Network Packet Inspection (Wireshark, tshark), Log Parsing, Offline Triage
Tooling & Methods:
Git, GitHub Actions, PyPI Package Publishing, Playwright, Puppeteer, Markdown Documentation, Unit Testing
Verifiable Open-Source Projects
TraceForge — OSINT & Digital Forensics CLI
Python 3.10+ · SQLite WAL · Bash · STIX 2.1 · PyPI: traceforge-osint
Local-first command-line toolkit for digital forensics, OSINT, and incident triage.
- Engineered 64 KB chunked streaming I/O buffers and worker pools to scan large log files and hash directory snapshots without RAM exhaustion.
- Implemented automated indicator extraction with regex defanging (IPs, domains, URLs) to safely prevent accidental network hits.
- Stored evidence logs in an ACID-compliant local SQLite database using Write-Ahead Logging (WAL) for forensic durability.
- Added STIX 2.1 JSON bundle exports and verified compatibility across macOS (Darwin arm64) and Kali Linux.
Astra Engine — Headless WhatsApp Automation
Python 3 · Playwright · AsyncIO · WebSockets · JavaScript Bridge
Asynchronous Python library for WhatsApp Web automation and headless message event dispatching.
- Integrated Playwright to execute headless browser sessions with pairing-code authentication, eliminating the need for an open browser window.
- Engineered an in-browser JavaScript injection bridge to capture incoming message events and dispatch them to Python async callbacks.
- Maintained persistent session states with automated reconnection logic during network drops.
Astra Userbot — Modular Bot Framework
Python 3 · Dynamic Plugins · SQLite · Linux Systemd
Extensible userbot framework built atop Astra Engine for task automation.
- Architected a dynamic plugin discovery system using Python's importlib, allowing custom commands to be added without touching core code.
- Persisted user permissions, configuration flags, and session metadata into local SQLite storage.
- Provided production systemd service configuration templates for headless daemon deployment on Linux.
WhatsApp-X — Containerized Automation Service
Node.js · Puppeteer · MongoDB · Docker · FFmpeg
Server-side automation bot handling media pipelines and persistent chat logs.
- Processed inbound voice notes, stickers, and images through FFmpeg pipelines for format normalization.
- Persisted message records to MongoDB and packaged the entire execution environment into reproducible Docker containers.
Windows Tools & Hardening
PowerShell · Batch Scripting · Windows WMI/CIM · Registry Hardening
Menu-driven system maintenance and workstation privacy hardening utility.
- Automated system cleanup routines, registry telemetry disabling, and background service auditing via native PowerShell cmdlets.
Engineering Principles
Local-First:
Tools should run on the analyst's machine without unnecessary cloud telemetry or third-party query leakage.
Lean Stack:
Avoid dependency bloat. Use standard library modules and proven primitives (multiprocessing, SQLite, Bash) before reaching for heavy frameworks.
Verifiable:
Every project backed by public source code, clear installation documentation, and reproducible test workflows on GitHub.