--- base_model: Qwen/Qwen2.5-Coder-3B tags: - gguf - llama.cpp - pentesting - cybersecurity - jetson - quantized --- # Qwen2.5-Coder-3B Pentest - GGUF GGUF quantizations of [fawazo/qwen2.5-coder-3b-pentest](https://huggingface.co/fawazo/qwen2.5-coder-3b-pentest) optimized for **Jetson Orin Nano (8GB)**. ## Model Description An AI pentesting assistant fine-tuned on 150K+ cybersecurity examples covering: - OWASP Top 10 vulnerabilities - MITRE ATT&CK framework - API security testing - Web application penetration testing **Output Format:** JSON for automation ## Quantizations | File | Size | RAM Needed | Recommended For | |------|------|------------|-----------------| | `qwen2.5-coder-3b-pentest-q4_k_m.gguf` | ~1.8GB | ~3GB | **Jetson Orin Nano 8GB** | | `qwen2.5-coder-3b-pentest-q5_k_m.gguf` | ~2.1GB | ~4GB | Better quality | | `qwen2.5-coder-3b-pentest-q8_0.gguf` | ~3.4GB | ~5GB | Best quality | | `qwen2.5-coder-3b-pentest-f16.gguf` | ~6GB | ~8GB | Full precision | ## Usage on Jetson ### With Ollama ```bash # Download Q4_K_M (recommended for 8GB) huggingface-cli download fawazo/qwen2.5-coder-3b-pentest-gguf qwen2.5-coder-3b-pentest-q4_k_m.gguf # Create Modelfile cat > Modelfile << 'EOF' FROM ./qwen2.5-coder-3b-pentest-q4_k_m.gguf SYSTEM """You are an expert penetration testing AI assistant. Analyze web traffic and respond with JSON: {"action": "report|request|command|complete", ...}""" PARAMETER temperature 0.3 PARAMETER num_ctx 2048 EOF # Create and run ollama create pentest-agent -f Modelfile ollama run pentest-agent ``` ### With llama.cpp ```bash ./llama-cli -m qwen2.5-coder-3b-pentest-q4_k_m.gguf -ngl 99 -c 2048 -p "Analyze this request..." ``` ## Example Usage **Input:** ``` Analyze this HTTP exchange: REQUEST: GET /api/users?id=1 RESPONSE: {"user": "admin", "role": "administrator"} ``` **Output:** ```json { "action": "request", "method": "GET", "path": "/api/users?id=2", "reasoning": "Testing for IDOR - checking if user IDs are enumerable" } ``` ## Training Details - **Base:** Qwen/Qwen2.5-Coder-3B - **Method:** SFT with LoRA (r=32) - **Dataset:** 150K+ combined examples from Trendyol, Fenrir v2.0, pentest-agent - **Frameworks:** OWASP, MITRE ATT&CK, NIST CSF ## License Apache 2.0 (inherits from base model and training datasets)