Patch Dashboard - Part 1 Gaining Visibility

[shawnsong]

Hi Folks,

It's me again. I've been working on this side project for quite some time. Recently, I was inspired by @urvashi this project made a huge breakthrough - I'll delve into that later, but first and foremost, a million thanks go to her!

Let’s dive straight in 😀.

Get Started

Download the notebook here. 

System Requirements

• Jupyter Notebook with Python's Conda distribution - recommended all-in-one package Anaconda.
• The Jupyter notebook should work on all desktop OSes.

Note

• Currently, the Patch Dashboard is only in scope for Windows, MacOS, and Ubuntu Desktop (with UI).
• The script will compare the patch level information, extracted from the osVersionDetail attribute (thanks Urvashi 😉) with the latest patch level published by the respective OS manufacturer:
• Win 11 & Win10
• MacOS
• Ubuntu
• As the post title suggests, this is V1. I understand there may be aspects I've overlooked, so please feel free to share your comments below. I appreciate your feedback in advance!

A Quick Manual

• On Jupyter Notebook, go to “kernel”, make sure the Conda kernel is selected.
• Input the read-only API key as instructed:
• Run each cell till step 2.
• On Step 2, fill in a path if you wanted to export the raw data to a CSV file:
• Run the rest of the cells. 

You should have the dashboards look like these:

P.S. If you have exported the CSV in step 2, you can bind these outdated systems to the patch policies (or create "aggressive" patch policies from our templates ) to force a "spring cleaning".

For MacOS, you can also use this method to force an update via the MDM cmd in the case of ultra-emergency 

That’s all for now. I hope you find it useful (and don’t forget to hit the kudos button 👇). Stay tuned for part 2!

[Update 14-08-2023] Part 2 is here.

[urvashi]

Excellent! Glad the community's questions help build stuff like this! 😄