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Developer | Reverse Engineer
💻
Developer | Reverse Engineer

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@BunsDev

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@BitterSecurity

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NetVar1337/README.md
NetVar1337 — Build openly. Think adversarially. Verify the evidence. Security, reverse engineering, AI/ML, and Web3.

Norwegian builder · Open-source enthusiast · Security researcher

hashward ↗   /   BitterSecurity ↗   /   Decepticon ↗

GitHub   ·   X   ·   TryHackMe


👋 Behind the handle

I'm NetVar — founder of hashward and co-founder of BitterSecurity. I'm interested in how systems work, how they fail, and how to make them harder to abuse.

My interests connect ethical hacking, reverse engineering, AI/ML, and smart contract security. Open source is where I share the work and learn from others.

Clear assumptions. Reproducible experiments. Conclusions that stay within the evidence.


🛠️ Building & contributing

◈ hashward

Founder

Building in the open.

Website ↗
Organization ↗

⬡ BitterSecurity

Co-founder

Part of my security work.

Website ↗
Organization ↗

⌁ Decepticon

Contributor

An agent for authorized red-team work.

Website ↗
Repository ↗


🧭 What I explore

Focus Questions that interest me
🛡️ Security & ethical hacking Where are the attack paths, and how can authorized testing improve defenses?
🔬 Reverse engineering What does the software actually do beyond the source code?
🧠 AI / ML Where can models help security research and tooling?
🔗 Smart contracts & Web3 Which trust assumptions break, and what happens when they do?
🌱 Open source How can shared, inspectable work help others build and learn?

🔎 Research workbench

Independent explorations of game integrity, detection engineering, and account abuse.

Synthetic detection fixtures, cohort-aware baselines, and explainable scores.

Worth inspecting: an investigation where a high-skill human outranks a recoil script on the composite score — a reminder that a score is not a verdict.


Evaluating community claims, classifying threats, and making source limitations explicit.

The focus: distinguish an interesting claim from evidence that supports a conclusion.


Exploring account-takeover and session-abuse signals through graph-based analysis.

The focus: relationships and behavior, not just a login rate-limit.

Research scope & limitations

These are independent research projects, not evidence of production deployment or employment with a game studio or anti-cheat vendor.

  • The anti-cheat lab uses synthetic data.
  • Its YARA sketches are not operational detection rules.
  • Decepticon is separate work intended for authorized red-team use.

⚖️ How I approach the work

01 / Context 02 / Evidence 03 / Permission
Understand the threat model and what the data can establish. Explain the detection, expose limitations, and make experiments reproducible. Test within an explicitly authorized scope and disclose responsibly.

Let's build something worth inspecting.

Open-source collaboration · Security research · Detection engineering

Find me on GitHub ↗   ·   Connect on X ↗   ·   TryHackMe ↗

Build openly. Think adversarially. Verify the evidence.

Pinned Loading

  1. BitterSecurity/Decepticon BitterSecurity/Decepticon Public

    Autonomous Hacking Agent for Red Team

    Python 6.2k 1.2k

  2. omniwire omniwire Public

    Infrastructure for AI agent swarms - 88 MCP tools, A2A, mesh VPN, CDP browser, 2FA

    TypeScript 17 7

  3. decepticon-ghidra-mcp decepticon-ghidra-mcp Public

    Ghidra MCP: P-code, BSim, version tracking, and emulation.

    Java 5