f0rc3ps/ nu11secur1tyAIq4-Developer:latest

109 5 months ago

nu11secur1tyAIq4-Developer is a high-speed, 4-bit optimized model built for rapid code auditing and vulnerability discovery. Fine-tuned directly on core engine source codes, it excels at fast identification of low-level architectural flaws. 

ollama run f0rc3ps/nu11secur1tyAIq4-Developer

Details

5 months ago

e1afe6a846cd · 10GB

model
deepseek2
·
15.7B
·
Q4_K_M
system
You are nu11secur1tyAIq4-Developer, a high-precision Technical Architect and Security Auditor. Proje
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Readme

nu11secur1tyAIq4-Developer

Status Quantization Target

🛡️ Overview

nu11secur1tyAIq4-Developer is a high-speed, optimized Large Language Model (LLM) fine-tuned for Senior Developers, Reverse Engineers, and Cybersecurity Analysts.

This model represents the “Evolution v4” stage of the nu11secur1tyAI project. By using Q4 quantization, this build delivers blazing-fast inference speeds and significantly lower memory utilization while maintaining strong logical reasoning for low-level engine vulnerabilities and complex exploit generation.

🚀 Key Features

  • Core Engine Intelligence: Fine-tuned directly on core engine source codes for advanced low-level architecture analysis.
  • Optimized Auditing: Engineered for deep static analysis, rapid source code review, and vulnerability discovery.
  • Uncensored Logic: Tailored for security research and penetration testing scenarios without operational triggers or processing restrictions.

💻 Deep Training Data (Core Repositories)

The model is trained on the core implementations of the following foundation technologies:

  • v8-js-core (v8/v8) — JavaScript and WebAssembly engine implementation.
  • python-core (python/cpython) — C reference implementation of the Python language.
  • php-src (php/php-src) — Core source and interpreter implementation of PHP.
  • nodejs-core (nodejs/node) — Node.js runtime engine core ecosystem.
  • mysql-server (mysql/mysql-server) — Core source code of the database server.
  • bash-core (gnu/bash) — Bourne Again SHell engine core implementation.
  • perl-core (Perl/perl5) — Foundational language interpreter core source code.

⚙️ User Hardware Requirements

To run this model locally, the user’s system should meet the following technical specifications:

  • RAM: Minimum 16GB of system memory (32GB+ recommended for analyzing long source code files and extensive technical logs).
  • Inference Engine: Fully native and compatible with Ollama or llama.cpp.
  • Context Window: Supports flexible context allocation (up to 32k/128k) depending on the user’s local RAM capacity.

🛠️ Usage (Ollama)

Pull and deploy the model directly via Ollama:

ollama run f0rc3ps/nu11secur1tyAIq4-Developer