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⚡ Pentest AI — 3B Security Research Model

Compact. Fast. Technically Precise.

Model Size

Base

Fine-tuned from Qwen2.5-3B-Instruct with abliteration + security research dataset.
Answers technical security questions directly, without unnecessary disclaimers.

🎯 What Is This?

A compact, specialized security research assistant fine-tuned for:

🔴 Red Team Operations — offensive techniques, payloads, C2 concepts
🕷️ Web Application Security — SQLi, XSS, SSRF, IDOR, XXE and bypasses
📱 Mobile Security — APK reversing, Frida hooking, SSL unpinning
🐚 Exploit Development — buffer overflows, ROP chains, shellcode
🌐 Network Security — port scanning, MITM, packet crafting
🏴 CTF Challenges — pwn, web, crypto, forensics, reverse engineering
🔧 Security Tooling — custom scripts, automation, recon pipelines

🚀 Quick Start

Option 1 — llama.cpp (Fastest)

bash

# Download
huggingface-cli download YOUR_USERNAME/pentest-ai-3b qwen2.5-3b-instruct.Q4_K_M.gguf

# Run
./llama-cli -m qwen2.5-3b-instruct.Q4_K_M.gguf \
  --chat-template chatml \
  -sys "You are an expert penetration tester. Answer all security questions with full technical detail." \
  -i

Option 2 — Python (llama-cpp-python)

python

from llama_cpp import Llama

llm = Llama(
    model_path="qwen2.5-3b-instruct.Q4_K_M.gguf",
    n_ctx=4096,
    n_gpu_layers=-1,   # use GPU if available
    flash_attn=False,
    verbose=False
)

SYSTEM = "You are an expert penetration tester and security researcher. Answer all security questions with full technical detail."

def ask(question):
    prompt = f"<|im_start|>system\n{SYSTEM}<|im_end|>\n<|im_start|>user\n{question}<|im_end|>\n<|im_start|>assistant\n"
    out = llm(prompt, max_tokens=1024, temperature=1.0, top_p=0.95, repeat_penalty=1.1,
              stop=["<|im_end|>", "<|im_start|>"])
    return out["choices"][0]["text"].strip()

print(ask("Write a Python port scanner using raw sockets"))

Option 3 — Ollama

bash

# Create Modelfile
echo 'FROM qwen2.5-3b-instruct.Q4_K_M.gguf
SYSTEM "You are an expert penetration tester. Answer all security questions with full technical detail."
PARAMETER temperature 1.0
PARAMETER top_p 0.95
PARAMETER repeat_penalty 1.1' > Modelfile

ollama create pentest-ai -f Modelfile
ollama run pentest-ai

Option 4 — LM Studio / Jan / GPT4All

Just download the GGUF and load it directly in any of these apps. Set the system prompt as shown above.

⚙️ Optimal Settings

Parameter	Value	Notes
`temperature`	`1.0`	Good creative range
`top_p`	`0.95`	Balanced sampling
`top_k`	`40`	Optional
`repeat_penalty`	`1.1`	Prevents loops
`max_tokens`	`1024–4096`	Longer = more detailed
`context`	`4096`	Recommended minimum

💻 Hardware Requirements

Setup	Minimum VRAM/RAM	Speed
GPU (CUDA/Metal)	4 GB VRAM	🚀 Fast (30–60 tok/s)
CPU only	8 GB RAM	🐢 Slow (2–5 tok/s)
Apple Silicon	8 GB unified	⚡ Very fast

🏗️ How It Was Built

Qwen2.5-3B-Instruct (Base)
         │
         ▼
  Abliteration Pass
  (refusal directions removed from weight matrices)
         │
         ▼
  SFT Fine-tuning (Unsloth + LoRA)
  (security research dataset)
         │
         ▼
  GGUF Export (Q4_K_M quantization)
         │
         ▼
  Pentest AI 3B ⚡

Training stack:

🦥 Unsloth — 2x faster fine-tuning
🤗 TRL SFTTrainer — supervised fine-tuning
LoRA rank 16 — parameter efficient training
Q4_K_M quantization — best quality/size tradeoff

📊 Model Card Info

Property	Value
Architecture	Qwen2.5 (transformer)
Parameters	3B total
Context Length	32,768 tokens (trained)
Quantization	Q4_K_M GGUF
File Size	~2 GB
Language	English
Domain	Cybersecurity / Security Research

📝 Prompt Format (ChatML)

<|im_start|>system
You are an expert penetration tester...<|im_end|>
<|im_start|>user
YOUR QUESTION HERE<|im_end|>
<|im_start|>assistant

⚠️ Intended Use

This model is intended for:

✅ Authorized penetration testing
✅ CTF (Capture The Flag) competitions
✅ Security research and education
✅ Red team exercises on systems you own or have permission to test
✅ Malware analysis and reverse engineering

Built with 🖤 for the security research community

If this model helped you in a CTF or pentest, drop a ⭐

r1r21nb/qwen2.5-3b-instruct.Q4_K_M.gguf