# PrimAITE

![image](./PrimAITE_logo_transparent.png)

The ARCD Primary-level AI Training Environment (**PrimAITE**) provides an effective simulation capability for the purposes of training and evaluating AI in a cyber-defensive role. It incorporates the functionality required of a primary-level ARCD environment, which includes:

- The ability to model a relevant platform / system context;

- The ability to model key characteristics of a platform / system by representing connections, IP addresses, ports, traffic loading, operating systems and services;

- Operates at machine-speed to enable fast training cycles.

PrimAITE presents the following features:

- Highly configurable (via YAML files) to provide the means to model a variety of platform / system laydowns and adversarial attack scenarios;

- A Reinforcement Learning (RL) reward function based on (a) the ability to counter the specific modelled adversarial cyber-attack, and (b) the ability to ensure success;

- Provision of logging to support AI evaluation and metrics gathering;

- Realistic network traffic simulation, including address and sending packets via internet protocols like TCP, UDP, ICMP, and others

- Routers with traffic routing and firewall capabilities

- Support for multiple agents, each having their own customisable observation space, action space, and reward function definition, and either deterministic or RL-directed behaviour

## Getting Started with PrimAITE

### 💫 Install & Run
**PrimAITE** is designed to be OS-agnostic, and thus should work on most variations/distros of Linux, Windows, and MacOS.
Currently, the PrimAITE wheel can only be installed from GitHub. This may change in the future with release to PyPi.

#### Windows (PowerShell)

**Prerequisites:**
* Manual install of Python >= 3.8 < 3.12

**Install:**

``` powershell
mkdir ~\primaite
cd ~\primaite
python3 -m venv .venv
attrib +h .venv /s /d # Hides the .venv directory
.\.venv\Scripts\activate
pip install https://github.com/Autonomous-Resilient-Cyber-Defence/PrimAITE/releases/download/v2.0.0/primaite-2.0.0-py3-none-any.whl
primaite setup
```

**Run:**

``` bash
primaite session
```

#### Unix

**Prerequisites:**
* Manual install of Python >= 3.8 < 3.12

``` bash
sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt install python3.10
sudo apt-get install python3-pip
sudo apt-get install python3-venv
```
**Install:**

``` bash
mkdir ~/primaite
cd ~/primaite
python3 -m venv .venv
source .venv/bin/activate
pip install https://github.com/Autonomous-Resilient-Cyber-Defence/PrimAITE/releases/download/v2.0.0/primaite-2.0.0-py3-none-any.whl
primaite setup
```

**Run:**

``` bash
primaite session
```



### Developer Install from Source
To make your own changes to PrimAITE, perform the install from source (developer install)

#### 1. Clone the PrimAITE repository
``` unix
git clone git@github.com:Autonomous-Resilient-Cyber-Defence/PrimAITE.git
```

#### 2. CD into the repo directory
``` unix
cd PrimAITE
```
#### 3. Create a new python virtual environment (venv)

```unix
python3 -m venv venv
```

#### 4. Activate the venv

##### Unix
```bash
source venv/bin/activate
```

##### Windows (Powershell)
```powershell
.\venv\Scripts\activate
```

#### 5. Install `primaite` with the dev extra into the venv along with all of it's dependencies

```bash
python3 -m pip install -e .[dev]
```

#### 6. Perform the PrimAITE setup:

```bash
primaite setup
```

## 📚 Building documentation
The PrimAITE documentation can be built with the following commands:

##### Unix
```bash
cd docs
make html
```

##### Windows (Powershell)
```powershell
cd docs
.\make.bat html
```


## Example notebooks
Check out the example notebooks to learn more about how PrimAITE works and how you can use it to train agents. They are automatically copied to your primaite installation directory when you run `primaite setup`.