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Sabarish
Sabarish

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Black God Linux

#linux #security #showdev #tools

Hey everyone! 👋

I'm Sabarish ( Grade 12 cbse student )

I'm a security enthusiast and developer, and over the past few weeks, I’ve been building my own penetration testing distribution called Black God Linux.

It’s built directly on Kali Linux Rolling and the Debian core, but engineered specifically to solve two major frustrations I ran into constantly:

  1. The Apple Silicon Struggle: Running standard x86 Kali Linux on modern M-series MacBooks under QEMU software emulation is notoriously slow, with display lag, high CPU usage, and 60+ second boot times.
  2. Recon Fatigue: In everyday CTFs and pentesting engagements, running initial target discovery usually means opening 5 different terminal tabs and manually running dig, whois, nmap, whatweb, and gobuster, then copying everything into notes manually.

So, I decided to build a dedicated distro from source to automate these bottlenecks and give it a custom dark cyber aesthetic.

⚡ What Makes Black God Linux Different?

1. Native Apple Silicon (ARM64) Acceleration

Instead of relying on slow CPU translation, I set up cloud compilation on native ARM64 GitHub runners. When booted in UTM under Virtualize mode using Apple's Hypervisor Framework (-accel hvf):

  • Boot time: Drops from ~45–90s down to 3.2 seconds flat.
  • Display: Smooth 60–75 FPS with RedHat VirtIO GPU acceleration.
  • (Note: There is also a dedicated amd64 / x86_64 ISO release for Intel/AMD PC laptops).

2. The blackgod-recon Automated Engine

I wrote a custom Bash orchestrator placed directly in /usr/local/bin. Running a single command:
blackgod-recon target.com
Sequentially executes 5 full phases:

  • Phase 1 (DNS): host lookups and dig ANY
  • Phase 2 (WHOIS): Registrar and IP block intelligence
  • Phase 3 (Nmap): Multi-threaded port scan & service detection (-sV -sC -T4)
  • Phase 4 (Web Fingerprinting): WhatWeb CMS detection and Wafw00f firewall analysis
  • Phase 5 (Directory Fuzzing): Gobuster dir scan with common.txt It automatically parses and exports 9 structured reports into a timestamped directory in your home folder. In testing, this reduced initial time-to-target from ~18 minutes down to 3.4 minutes (a 5.4x speed gain).

3. Streamlined Memory Footprint (~650 MB Idle)

By stripping default background bloat and configuring a lean XFCE4 desktop with LightDM, idle RAM consumption sits at just ~650 MB – 720 MB. This means it flies on modern hardware and can effortlessly revive 15-year-old laptops with only 4 GB of RAM.

4. Additional Tactical Binaries

  • blackgod-wifi: Kills interfering network processes (airmon-ng check kill) and puts compatible wireless adapters into monitor mode with one command.
  • blackgod-update: An atomic sync command that updates Debian packages, reinitializes the Metasploit payload database (msfdb), and updates the offline Exploit-DB archive for searchsploit.

5. Custom Golden Skull Cyber Theme

I wanted the OS to feel like a modern offensive terminal. It features a custom 4K cybernetic Golden Skull wallpaper, a pre-configured Kali-Dark / Flat-Remix theme, and a dual-tone red & gold ASCII welcome banner on terminal startup.

🛠️ How It Was Engineered (Under the Hood)

  • Build Engine: Created using Debian live-build. All branding, configuration overrides, and custom orchestrators are injected via the includes.chroot/ filesystem overlay.
  • Cloud CI/CD: The entire compilation runs through automated GitHub Actions workflows (build-arm64-iso.yml and build-iso.yml).
  • Overcoming GitHub's 2GB Limit: Since GitHub Releases caps single file uploads at 2GB and the ISOs are ~4.8GB – 5.6GB, I automated split-binary chunking in GitHub Actions so users can download the pieces and recombine them with a simple cat command.

📊 Benchmark Summary vs. Vanilla Kali:

  • Recon Time-to-Deliverable: ~3.4 min vs ~18.5 min (5.4x faster)
  • Apple Silicon Boot Latency: 3.2s vs ~45s+
  • Idle Memory: ~650 MB vs ~1.4 GB
  • Tool Readiness: 300+ Kali security packages pre-installed

🔗 Project Links:

I'm actively maintaining and expanding this project. I would really appreciate any feedback, bug reports, or tool recommendations you'd like to see automated next!

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