Need to research on the building the images on different Operating System architectures for better performance.

Need to find out the correct directory

A new issue has arisen with the installation of Python modules using setup.py, which indicates that this method has been deprecated.

Add the latest GO Language build and push to main branch

Adding support to GitHub docker packages and providing the images as a package associated with the GitHub itself.

Need to resolve the error in the github action for the action link
https://github.com/RAJANAGORI/Nightingale/actions/runs/9187469603

TTYD service should run in background. It always points to zsh or bash based on your requirements.

Need to look out for the better terminal experience for the users.

Is your feature request related to a problem? Please describe.
The Docker images are not versioned so migrating to an older version is not possible. Apart from that everything in one image makes it very huge. I think we can build multiple images based on use-cases like one for mobile, one for web, one for network, and maybe one image for everything. This way we can give use-case-driven images that engineers can use as per their requirements.

Describe the solution you'd like
So the solution is to build a base image (very small with minimal tools which are used everywhere) and extend it in multiple other images based on use cases.

Tracking issue for:

• https://github.com/RAJANAGORI/Nightingale/security/code-scanning/7870

This integration will allow organization to add their users from AD to authenticate an individual pod of Nightingale which can be accessible by a user having a separate instance to start testing from the nightingale.

Hi Raja,

You have done a great job by creating Nightingale docker images with all web penetration based tools under one roof. This makes our tasks so simple without installing any dependencies. similar to that can you please add Android penetration tools in Nightingale.

Tools:
MOBSF, Apktool, JD-GUI, Dex2jar, objection, Frida, ADB platform tools, Drozer, d2j-dex2jar

Thanks,
Yogi

Currently, Nightingale deployment in our Kubernetes architecture relies on a static Docker image. To ensure that our application stays up to date with the latest improvements and security patches, it's essential to automate the process of updating the Docker image in every month.

I propose enhancing our Helm chart to include a feature that automates the monthly update of the Nightingale Docker image within the Kubernetes cluster. This enhancement will streamline the maintenance process and ensure that our application benefits from the latest features and security enhancements without manual intervention.

Below is the list of the task that need to do

• Design the website using markdown website
• Further updates on Helm Charts
• Look out for the Dockerfile Optimization to reduce the redundant code

Go Installation Added for the installation.

Apart from Offensive and Defensive, planning to add different domain as well like DevSecOps, Learning Labs, Wireless section and many others

This integration will help to monitor the user logs, pod usages running inside the k8s environment.

Planning phase to add GUI in the Nightingale for those who hate CLI haha

Need to fix the stability of the Frida to connect to mobile devices for App VAPT

• First, try with frida-tools
• If not work, try with github repo to make a build

Is your feature request related to a problem? Please describe.
I was checking the docker image size of the project and it is of size 3 GB.

The VM like Kali and others are also very heavy and as this is a docker project so sizes should be small so that people can download them, use them easily (even though I agree that there is docker layer caching but still 3 GB is huge).

Describe the solution you'd like
Solutions could be:

1. the docker file can be optimized such that the base docker image is small (use alpine or google distroless)
2. Multiple Copy/Run statements could be merged. why? because each layer has a pointer to another (and few other things) so size increases because of layers.
3. Docker Run and Copy statements can be structured like frequently changing statements should be below the infrequent changes.
4. better way to handle layering issue is by using Docker Multistage builds
5. Cleanups are of no use in docker images because it is layered architecture so if a layer is created above then removing it in next layer has no impact and it doesn't help in reducing the size. (https://github.com/RAJANAGORI/Nightingale/blob/main/Dockerfile#L348) (use multistage build, it is the best for deletion use cases)

Additional context
I can help with ideas on making docker files better.

It will be a game changer, if the Nightingale can be integrated with ZAP and everything will be possible around pentesting can be done with the browser itself or more precisely in your testing environment without setup anything.

Working on the build size of the final image in order to minimize and fast installation of the tool

Is your feature request related to a problem? Please describe.
I checked the readme and there are many options based on commands, I think it would be easier to give a docker-compose.yaml file which can help users run it with just docker-compose up command which is pretty easy.

• Need to check the frida
• Need to check the objection
• Need to check the diresearch
• Need to check the Sqlmap

Objective:

The aim of this pull request is to implement a scalable architecture using Docker and Kubernetes (K8s). This architectural enhancement will not only streamline our workflow but also facilitate the onboarding process for new team members through the utilization of namespaces with our hosting domain.

Expected Benefits:

Scalability: By leveraging Docker and Kubernetes, our architecture becomes inherently scalable. It empowers us to handle increased workloads seamlessly, ensuring optimal performance under varying demands.

Efficiency in Onboarding: The utilization of namespaces with our hosting domain simplifies the onboarding process for new team members. They can easily navigate and understand the architecture, accelerating their integration into the team.

Streamlined Workflow: Docker and Kubernetes enable a more streamlined development workflow. With consistent deployment environments and automated management, testers can focus more on penetration testing and less on infrastructure concerns.

Tracking issue for:

• https://github.com/RAJANAGORI/Nightingale/security/code-scanning/7871