Create a Network Admin AI: How to Integrate Ollama with Your Firewall via API
Z
Zack Saadioui
8/11/2025
Create a Network Admin AI: How to Integrate Ollama with Your Firewall via API
Hey everyone, let's talk about something pretty nerdy but also incredibly cool: building your own AI to help manage your network. If you've ever found yourself digging through firewall menus at 2 AM to block a suspicious IP, you've probably thought, "there has to be a better way."
Well, we're living in the future, & it turns out there is. We're going to explore how you can create your very own "Network Admin AI." The idea is to use natural language—you know, just talking to your computer—to manage your firewall. Imagine typing "Hey, block all traffic from North Korea" or "Show me all the denied connections in the last hour," & having it just... happen.
This isn't science fiction. It's about combining the power of local, open-source large language models (LLMs) with the APIs that modern firewalls provide. Specifically, we're going to be talking about using Ollama to run powerful models on your own hardware & connecting it to your firewall's API.
Honestly, this is one of those game-changer projects. It can simplify complex tasks, speed up your response to threats, & just make network administration feel a little less like a chore & a little more like having a conversation. We'll walk through the whole setup, from the core concepts to a practical Python script, & even discuss the VERY important security implications.
The Big Picture: How Does This Even Work?
Before we dive into the nitty-gritty, let's get a 10,000-foot view of what we're building. It's actually a pretty simple chain of events:
You (The Human): You type a command in plain English, like "Block the IP address 123.45.67.89."
The "Glue" Application: A simple script (we'll use Python) takes your text. This is the intermediary, the thing that connects everything.
Ollama (The Brains): The script sends your command to a running Ollama instance. We'll give the LLM a special prompt that tells it, "You are a network security assistant. Your job is to turn human language into a specific firewall API command."
The LLM Does Its Magic: The language model processes your request & the prompt, & based on its training, it generates the structured API call that the firewall will understand. For our example, it might spit out a JSON object like
Back to the Glue: The Python script receives this structured data from Ollama.
The Firewall (The Muscle): The script then makes a formal API request to your firewall, using the data generated by the LLM.
Action! The firewall receives the valid API call & adds the new rule, blocking the IP address.
Pretty cool, right? The LLM acts as a universal translator, turning your intent into a machine-readable command.
Core Component #1: Ollama - Your Local AI Powerhouse
First things first, you need an AI. This is where Ollama comes in.
Ollama is an incredible open-source tool that makes it ridiculously easy to run powerful LLMs like Llama 3.1, Mistral, & Gemma 2 right on your own computer (or a server in your homelab). This is key for a few reasons:
Privacy & Security: You're not sending your network commands or potentially sensitive log data to a third-party cloud service. Everything stays in-house.
Cost: It's free. You just need the hardware to run it.
Control & Customization: You can pick the model that works best for you & fine-tune its behavior.
Getting Ollama Up & Running
Setting up Ollama is super straightforward. You can download it for macOS, Linux, or Windows from their website.
Once installed, you can run a model from your terminal. Let's start with a small, fast model to test things out: