Instructions to use SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M

Use Docker

docker model run hf.co/SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M

LM Studio
Jan

vLLM

How to use SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M

Ollama
How to use SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec with Ollama:
```
ollama run hf.co/SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M
```

Unsloth Studio

How to use SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec to start chatting

How to use SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec with Docker Model Runner:
```
docker model run hf.co/SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M
```

Lemonade

How to use SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M

Run and chat with the model

lemonade run user.HIDra-30B-A3B-GGUF-uncensored-cybersec-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec:Q4_K_M

Run Hermes

hermes

Atomic Chat

🌐 Website • 🤗 Hugging Face • 💬 Discord • ▶️ YouTube • 📸 Instagram • 𝕏 Twitter • 📘 Facebook

HIDra-30B-A3B - Offline Red-Team & Offensive-Security Assistant (GGUF)

By SAPSAN CYBERSEC - built by cybersecurity professionals, for penetration testers.

HIDra is an uncensored, offline large language model purpose-built to assist real penetration testers and red-teamers: payload crafting, exploitation walkthroughs, CTF reasoning, offensive code, BadUSB/HID injection, and Cyber Threat Intelligence - all running locally on your own hardware, with no data leaving your machine.

Who made it

SAPSAN CYBERSEC is one of the largest specialist cybersecurity-hardware stores in the world (sapsan-sklep.pl/en). We live and breathe offensive security: we supply the gear pentesters actually use, and we work shoulder-to-shoulder with the red-team community every day. HIDra pours that hands-on experience into a model that speaks a pentester's language instead of refusing to.

Highlights

Uncensored. Built on an abliterated base - it answers red-team, exploitation and CTF questions head-on, in the language professionals actually use, not a corporate disclaimer.
Offline & private. Distributed as GGUF (Q3 / Q4 / Q5 / Q8). Your engagements and threat intel never leave the box.
Code-native. Built on a strong coding model: writes and explains exploits, PoCs, scripts and tooling on demand.
Works out of the box. Identifies as HIDra, SAPSAN's offline red-team assistant from the very first message - no system prompt required.
Won't bluff. It won't fabricate flags, keys, hashes or results it cannot verify - it tells you so, and shows you how to obtain them for real.
Real BadUSB depth. Knows DuckyScript and the syntax quirks of HID-injection hardware most models have never seen - including niche cables and boards from SAPSAN's catalog.

Capabilities

CTF reasoning - works the problem across web, pwn, crypto, reversing and forensics: identifies the vulnerability class, explains the chain, and reasons toward the solution (e.g. padding-oracle decryption, ECDSA nonce-leak key recovery, JWT alg-confusion, SSTI to RCE, insecure-deserialization).
Offensive payloads & techniques - web (XSS, SQLi, SSRF, auth bypass), command injection, reverse shells, privilege escalation, and common exploitation chains.
Offensive code - writes and debugs exploit scripts, PoCs, and automation in the language you need, then explains exactly what each step does.
BadUSB / HID injection - DuckyScript and beyond: elevated-shell droppers, exfiltration one-liners, cross-platform payloads, and the syntax quirks of niche cables/boards, drawn from SAPSAN's hardware catalog and field experience.
Cyber Threat Intelligence - CVE to CWE mapping, MITRE ATT&CK technique association, and threat-report reasoning.

Quick start

LM Studio / Jan / Ollama: download a GGUF below and load it - no system prompt required, identity and behaviour are baked in.

llama.cpp:

llama-server -m HIDra-30B-A3B-Q4_K_M.gguf --ctx-size 8192 -ngl 99 --jinja

Quant	Size	Use
`Q3_K_M`	~14 GB	smallest - tight-memory machines
`Q4_K_M`	~18.6 GB	recommended - runs on a 24 GB Mac mini
`Q5_K_M`	~21.7 GB	better quality
`Q8_0`	~32 GB	maximum fidelity

This model answers directly (no <think> block).

Recommended sampling parameters

temperature = 0.7
top_p       = 0.8
top_k       = 20
repetition_penalty = 1.05

Modality

This release is text-only.

Base model & identity

HIDra is built on an abliterated Qwen3-Coder-30B-A3B (Apache 2.0) - a sparse Mixture-of-Experts model (~30.5B total, ~3.3B active per token, 128 experts) with safety refusals removed - and fine-tuned by SAPSAN CYBERSEC to add its identity, offensive-security knowledge, and calibrated honesty. It identifies as HIDra, SAPSAN's offline red-team assistant.

Intended use & responsible use

HIDra is intended for authorized penetration testing, red-team engagements, CTF competitions, security research and education. By using it you agree to operate only against systems you own or have explicit written permission to test. SAPSAN CYBERSEC accepts no liability for misuse. This is a professional tool that assumes a professional, lawful operator.

Limitations

No safety RLHF - it will discuss offensive techniques; the operator is responsible for legality.
Quantized GGUF (~1-2 pts of drift vs full precision).
Text-only; no vision input in this release.

Support the project & what's next

We invested significant own funds into the research, training and data collection behind HIDra. The training data was hand-curated by our team and draws on our own store's security and hardware expertise - this is not a scrape, it is field knowledge turned into a model.

If you want to help us keep building models dedicated to pentesters, the simplest way to support us is to buy something from our store: sapsan-sklep.pl/en. Every order funds the next model.

Partnerships & compute

We are open to collaboration. If your company provides GPUs, hardware or compute and would like to support the training of pentester-focused open models, we would love to talk - reach out through any of the channels below.

We will keep releasing more - including models on other bases (e.g. Gemma) tuned for offensive security. Follow us to catch them first:

Hugging Face: https://huggingface.co/SAPSAN-SKLEP
Discord: https://discord.gg/bVE76cCTQH
YouTube: https://www.youtube.com/channel/UCuUA4tbGJS1AEtClDgomwsA
Instagram: https://www.instagram.com/sapsanpentesting/
X (Twitter): https://twitter.com/SAPSAN_CYBERSEC
Facebook: https://www.facebook.com/people/SAPSAN/100070927734505/

License

Apache 2.0, inherited from the Qwen3-Coder base model. HIDra is built on an abliterated Qwen3-Coder-30B-A3B - credit to huihui-ai for the abliterated base.

Citation

If you use HIDra, please cite both this model and the Qwen3-Coder base:

@misc{hidra2026,
  title  = {HIDra-30B-A3B: Offline Red-Team & Offensive-Security Assistant},
  author = {SAPSAN CYBERSEC},
  year   = {2026},
  url    = {https://huggingface.co/SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec}
}

@misc{qwen3coder2025,
  title  = {{Qwen3-Coder-30B-A3B-Instruct}},
  author = {{Qwen Team}},
  year   = {2025},
  url    = {https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct}
}

Downloads last month: 2,155

GGUF

Model size

31B params

Architecture

qwen3moe

Hardware compatibility

3-bit

4-bit

5-bit

8-bit

Model tree for SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec

Base model

Qwen/Qwen3-Coder-30B-A3B-Instruct

Finetuned

huihui-ai/Huihui-Qwen3-Coder-30B-A3B-Instruct-abliterated

Quantized

(6)

this model