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language:
  - en
  - es
license: apache-2.0
base_model: unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit
tags:
  - bug-bounty
  - security
  - pentesting
  - exploit-generation
  - waf-bypass
  - cybersecurity
  - hacking
model-index:
  - name: BugTraceAI-CORE-v1
    results: []

🛡️ BugTraceAI-CORE v1.0

BugTraceAI-CORE is a specialized Large Language Model (LLM) fine-tuned for high-performance, private, and local cybersecurity operations. Developed specifically for bug hunters, pentesters, and security researchers, it bridges the gap between general-purpose coding assistants and offensive security experts.

🚀 Key Features

Offensive Security Expertise: Fine-tuned on real-world exploit chains, WAF bypasses, and security methodologies.
Local-First Architecture: Designed to run on consumer-grade GPUs (RTX 3060+) with a high-availability fallback for dual-Xeon CPU environments.
2025/2026 Ready: Trained on recent vulnerability write-ups and disclosed reports to ensure relevance against modern 2025/2026 defense systems.
Zero-Downtime MLOps: Integrated with a secondary CPU fallback using llama.cpp for 24/7 availability during re-training cycles.

🧠 Training & Methodology

The model was built using the Unsloth library for optimized QLoRA training on a single RTX 3060 (12GB VRAM).

Datasets (The Hacker's Brain)

WAF Evasion & Injection: Trained on darkknight25/WAF_DETECTION_DATASET for generating payloads that bypass modern Web Application Firewalls.
Security Methodology: Trained on AYI-NEDJIMI/bug-bounty-pentest-en to master the logical structure of pentesting logs and methodology.
Real-World Experience: Augmented with HackerOne Disclosed Reports (scraped from Hacktivity) and curated GitHub Writeups (2025-2026) to learn successful exploit chains.
Architectural Foundation: Follows the implementation principles of Sebastian Raschka's "LLMs from scratch".

Technical Specs

Base Model: Qwen2.5-Coder-7B-Instruct
Fine-Tuning: QLoRA (Rank 64, Alpha 64)
Context Window: 4096 Tokens
Precision: bfloat16 (Optimized for NVIDIA Ampere architecture)

🛠️ Usage (BugTraceAI-CLI Integration)

BugTraceAI-CORE is designed to work as a plug-and-play replacement for external APIs.

# Example environment configuration
export OPENROUTER_BASE_URL="http://your-local-core:8000/v1"
export OPENROUTER_API_KEY="sk-bugtrace-local-core"

System Architecture

Port 8000: Gateway (FastAPI) - Intelligent router that directs traffic.
Port 8001: GPU Node (vLLM) - High-speed primary inference.
Port 8002: CPU Node (Llama.cpp) - Reliable fallback for the Dual Xeon.

⚠️ Disclaimer

BugTraceAI-CORE is intended for legal ethical hacking and educational purposes only. The creators are not responsible for any misuse of this tool. Always ensure you have explicit permission before testing any system.

Created as part of the BugTraceAI Ecosystem. Building a more secure web, one report at a time.