README.md

---
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)