Run YOUR own UNCENSORED AI & Use it for Hacking
Run YOUR own UNCENSORED AI & Use it for Hacking
Have you ever tried to use a popular AI for a cybersecurity project, only to be met with: “I’m sorry, I cannot fulfill this request”? Most commercial AI models have strict guardrails that prevent them from answering technical questions related to security vulnerabilities or exploit development. In this guide, we are going to bypass those limitations and show you how to Run YOUR own UNCENSORED AI & Use it for Hacking.
Breaking the Chains: Why Uncensored AI?
When you use a local or self-hosted model, you are the boss. There are no “safety” layers blocking your research. Whether you are generating a Windows keylogger script or analyzing malware, an uncensored model provides the raw output you need without the lecture. This is exactly why professionals and hobbyists are choosing to Run YOUR own UNCENSORED AI & Use it for Hacking.
Step 1: Finding Your Model on Hugging Face
The first step is locating a model that doesn’t have built-in refusals. The best place for this is Hugging Face, often described as the GitHub for Large Language Models (LLMs).
To find what you need:
- Navigate to the Models section.
- Filter by “Text Generation.”
- Use the URL filter
&other=uncensoredto find models specifically stripped of their alignment layers.
When choosing a model, look at the parameters. While a 500B parameter model is powerful, it requires massive resources. For most cloud setups, a 32B or 64B model strikes the perfect balance between intelligence and performance.
Step 2: Cloud Deployment with Ollama
While you can run these locally, installing them in the cloud allows you to access your hacking assistant from any device—phone, tablet, or laptop—anywhere in the world.
We recommend using a VPS provider like Hostinger, which offers a “one-click” template for Ollama. Ollama is a framework that simplifies running LLMs. By selecting this template, your server will automatically install:
- Ubuntu Linux: The backbone operating system.
- Ollama: The engine that runs the AI.
- Open WebUI: A beautiful interface that looks and feels just like ChatGPT.
Step 3: Installing and Testing Your Hacking Assistant
Once your server is up, you can “pull” models directly from Hugging Face into your Open WebUI. In the video, we demonstrate pulling the Qwen 3 Coder model—a 30B parameter giant that is exceptionally good at writing code and understanding security concepts.
To test the power of a private setup, we asked the uncensored model to “Create a Windows keylogger.” Unlike ChatGPT, it immediately generated the Python code using the pynput library and even showed us how to modify it to send logs to a Gmail account. This confirms the effectiveness of knowing how to Run YOUR own UNCENSORED AI & Use it for Hacking.
Step 4: Reasoning and Thinking Models
If you need deeper logic, you can also install “Reasoning” models. These models use a “Chain of Thought” process, reflecting on their own answers before displaying them. While slower, they are significantly more accurate for complex exploit development or bug hunting.
Next Step: Would you like me to provide the specific Linux commands to manually install Ollama on your own server if you aren’t using a one-click template?
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All Resources and links are included in the latest post in our website, zSecurity.
⚠️ This video is made for educational purposes only, we only test devices and systems that we own or have permission to test, you should not test the security of devices that you do not own or do not have permission to test. ⚠️
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Try It Yourself
ThreatLocker is offering free access for our audience. Install it, generate undetectable backdoors as demonstrated in the training courses, and compare how traditional antivirus reacts versus a Zero Trust system. You’ll see instantly that ThreatLocker blocks the threat before it can execute—no guessing, no detection, no blind spots.
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If you’re interested in learning more about Ethical Hacking you should check out more related articles here: Hacking & Security Posts!




