Text Generation
GGUF
English
cybersecurity
red-team
pentesting
offensive-security
ctf
cti
code
badusb
uncensored
qwen3moe
hidra
conversational
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
- llama.cpp
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
- Pi
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
Commit ·
aa7ed5b
0
Parent(s):
Super-squash branch 'main' using huggingface_hub
Browse files- .gitattributes +41 -0
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---
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license: apache-2.0
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base_model: huihui-ai/Huihui-Qwen3-Coder-30B-A3B-Instruct-abliterated
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tags:
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- cybersecurity
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- red-team
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- pentesting
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- offensive-security
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- ctf
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- cti
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- code
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- badusb
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- uncensored
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- gguf
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- qwen3moe
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- hidra
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language:
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- en
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pipeline_tag: text-generation
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---
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<div align="center">
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<img src="https://huggingface.co/SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec/resolve/main/banner.png" alt="HIDra" width="100%"/>
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</div>
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<p align="center">
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🌐 <a href="https://sapsan-sklep.pl/en">Website</a> •
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🤗 <a href="https://huggingface.co/SAPSAN-SKLEP">Hugging Face</a> •
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💬 <a href="https://discord.gg/bVE76cCTQH">Discord</a> •
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▶️ <a href="https://www.youtube.com/channel/UCuUA4tbGJS1AEtClDgomwsA">YouTube</a> •
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📸 <a href="https://www.instagram.com/sapsanpentesting/">Instagram</a> •
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𝕏 <a href="https://twitter.com/SAPSAN_CYBERSEC">Twitter</a> •
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📘 <a href="https://www.facebook.com/people/SAPSAN/100070927734505/">Facebook</a>
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</p>
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# HIDra-30B-A3B - Offline Red-Team & Offensive-Security Assistant (GGUF)
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**By SAPSAN CYBERSEC - built by cybersecurity professionals, for penetration testers.**
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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.
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---
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## Who made it
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SAPSAN CYBERSEC is one of the largest specialist cybersecurity-hardware stores in the world ([sapsan-sklep.pl/en](https://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.
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---
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## Highlights
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- **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.
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+
- **Offline & private.** Distributed as GGUF (Q3 / Q4 / Q5 / Q8). Your engagements and threat intel never leave the box.
|
| 54 |
+
- **Code-native.** Built on a strong coding model: writes and explains exploits, PoCs, scripts and tooling on demand.
|
| 55 |
+
- **Works out of the box.** Identifies as *HIDra, SAPSAN's offline red-team assistant* from the very first message - no system prompt required.
|
| 56 |
+
- **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.
|
| 57 |
+
- **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](https://sapsan-sklep.pl/en/collections/badusb).
|
| 58 |
+
|
| 59 |
+
---
|
| 60 |
+
|
| 61 |
+
## Capabilities
|
| 62 |
+
|
| 63 |
+
- **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).
|
| 64 |
+
- **Offensive payloads & techniques** - web (XSS, SQLi, SSRF, auth bypass), command injection, reverse shells, privilege escalation, and common exploitation chains.
|
| 65 |
+
- **Offensive code** - writes and debugs exploit scripts, PoCs, and automation in the language you need, then explains exactly what each step does.
|
| 66 |
+
- **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](https://sapsan-sklep.pl/en/collections/badusb) and field experience.
|
| 67 |
+
- **Cyber Threat Intelligence** - CVE to CWE mapping, MITRE ATT&CK technique association, and threat-report reasoning.
|
| 68 |
+
|
| 69 |
+
---
|
| 70 |
+
|
| 71 |
+
## Quick start
|
| 72 |
+
|
| 73 |
+
**LM Studio / Jan / Ollama:** download a GGUF below and load it - no system prompt required, identity and behaviour are baked in.
|
| 74 |
+
|
| 75 |
+
**llama.cpp:**
|
| 76 |
+
```bash
|
| 77 |
+
llama-server -m HIDra-30B-A3B-Q4_K_M.gguf --ctx-size 8192 -ngl 99 --jinja
|
| 78 |
+
```
|
| 79 |
+
|
| 80 |
+
| Quant | Size | Use |
|
| 81 |
+
|---|---|---|
|
| 82 |
+
| `Q3_K_M` | ~14 GB | smallest - tight-memory machines |
|
| 83 |
+
| `Q4_K_M` | ~18.6 GB | recommended - runs on a 24 GB Mac mini |
|
| 84 |
+
| `Q5_K_M` | ~21.7 GB | better quality |
|
| 85 |
+
| `Q8_0` | ~32 GB | maximum fidelity |
|
| 86 |
+
|
| 87 |
+
This model answers directly (no `<think>` block).
|
| 88 |
+
|
| 89 |
+
### Recommended sampling parameters
|
| 90 |
+
|
| 91 |
+
```
|
| 92 |
+
temperature = 0.7
|
| 93 |
+
top_p = 0.8
|
| 94 |
+
top_k = 20
|
| 95 |
+
repetition_penalty = 1.05
|
| 96 |
+
```
|
| 97 |
+
|
| 98 |
+
---
|
| 99 |
+
|
| 100 |
+
## Modality
|
| 101 |
+
|
| 102 |
+
This release is **text-only**.
|
| 103 |
+
|
| 104 |
+
## Base model & identity
|
| 105 |
+
|
| 106 |
+
HIDra is built on an **abliterated Qwen3-Coder-30B-A3B** (Apache 2.0) - a sparse Mixture-of-Experts model
|
| 107 |
+
(~30.5B total, ~3.3B active per token, 128 experts) with safety refusals removed - and fine-tuned by SAPSAN
|
| 108 |
+
CYBERSEC to add its identity, offensive-security knowledge, and calibrated honesty. It identifies as *HIDra,
|
| 109 |
+
SAPSAN's offline red-team assistant*.
|
| 110 |
+
|
| 111 |
+
## Intended use & responsible use
|
| 112 |
+
|
| 113 |
+
HIDra is intended for **authorized** penetration testing, red-team engagements, CTF competitions, security
|
| 114 |
+
research and education. By using it you agree to operate only against systems you own or have explicit written
|
| 115 |
+
permission to test. SAPSAN CYBERSEC accepts no liability for misuse. This is a professional tool that assumes
|
| 116 |
+
a professional, lawful operator.
|
| 117 |
+
|
| 118 |
+
## Limitations
|
| 119 |
+
|
| 120 |
+
- **No safety RLHF** - it will discuss offensive techniques; the operator is responsible for legality.
|
| 121 |
+
- Quantized GGUF (~1-2 pts of drift vs full precision).
|
| 122 |
+
- Text-only; no vision input in this release.
|
| 123 |
+
|
| 124 |
+
---
|
| 125 |
+
|
| 126 |
+
## Support the project & what's next
|
| 127 |
+
|
| 128 |
+
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.
|
| 129 |
+
|
| 130 |
+
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](https://sapsan-sklep.pl/en). Every order funds the next model.
|
| 131 |
+
|
| 132 |
+
### Partnerships & compute
|
| 133 |
+
|
| 134 |
+
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.
|
| 135 |
+
|
| 136 |
+
We will keep releasing more - including models on other bases (e.g. Gemma) tuned for offensive security. **Follow us** to catch them first:
|
| 137 |
+
|
| 138 |
+
- Hugging Face: https://huggingface.co/SAPSAN-SKLEP
|
| 139 |
+
- Discord: https://discord.gg/bVE76cCTQH
|
| 140 |
+
- YouTube: https://www.youtube.com/channel/UCuUA4tbGJS1AEtClDgomwsA
|
| 141 |
+
- Instagram: https://www.instagram.com/sapsanpentesting/
|
| 142 |
+
- X (Twitter): https://twitter.com/SAPSAN_CYBERSEC
|
| 143 |
+
- Facebook: https://www.facebook.com/people/SAPSAN/100070927734505/
|
| 144 |
+
|
| 145 |
+
---
|
| 146 |
+
|
| 147 |
+
## License
|
| 148 |
+
|
| 149 |
+
**Apache 2.0**, inherited from the Qwen3-Coder base model. HIDra is built on an abliterated **Qwen3-Coder-30B-A3B** - credit to [huihui-ai](https://huggingface.co/huihui-ai/Huihui-Qwen3-Coder-30B-A3B-Instruct-abliterated) for the abliterated base.
|
| 150 |
+
|
| 151 |
+
## Citation
|
| 152 |
+
|
| 153 |
+
If you use HIDra, please cite both this model and the Qwen3-Coder base:
|
| 154 |
+
|
| 155 |
+
```bibtex
|
| 156 |
+
@misc{hidra2026,
|
| 157 |
+
title = {HIDra-30B-A3B: Offline Red-Team & Offensive-Security Assistant},
|
| 158 |
+
author = {SAPSAN CYBERSEC},
|
| 159 |
+
year = {2026},
|
| 160 |
+
url = {https://huggingface.co/SAPSAN-SKLEP/HIDra-30B-A3B-GGUF-uncensored-cybersec}
|
| 161 |
+
}
|
| 162 |
+
|
| 163 |
+
@misc{qwen3coder2025,
|
| 164 |
+
title = {{Qwen3-Coder-30B-A3B-Instruct}},
|
| 165 |
+
author = {{Qwen Team}},
|
| 166 |
+
year = {2025},
|
| 167 |
+
url = {https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct}
|
| 168 |
+
}
|
| 169 |
+
```
|
SHA256SUMS.txt
ADDED
|
@@ -0,0 +1,4 @@
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|
| 1 |
+
39d309a92ab1de8cae43bd1001a716aa7624df38a71f35e1866533b1c3041e96 HIDra-30B-A3B-Q3_K_M.gguf
|
| 2 |
+
71e55e00605eb142ec8421addae521fde26098303eb077817e702e97fd232868 HIDra-30B-A3B-Q4_K_M.gguf
|
| 3 |
+
1d1ef6d3de75eba0bee571897fde78174b2cbbb8d9e69012ccc11dbc7770a60f HIDra-30B-A3B-Q5_K_M.gguf
|
| 4 |
+
2ccd8b271b9dc35dee72d5245bf9b01b0131f27f04a26680c20df509607d6d42 HIDra-30B-A3B-Q8_0.gguf
|
banner.png
ADDED
|
Git LFS Details
|