QZ Management

We were inspired by creating security infrastructure

What it does

We Developed a Security Management Software which helps users and companies be informed on any vulnerabilities present within there infrastructure.

Our security management software has two parts the agent and the manager, first the agent which is installed on all work computers that need there software monitored, the agent scan all software and the version number and relays that information to a central management server. The central management server takes the data and uses Gemini AI to clean the names for better analysis.

(UI of the agent, the user must input there credentials which will then be tied to the software they have installed of there work computer)

At specified intervals (Default being 1 day) the management server takes all the software that has be inputted into the database and enriches the data with vulnerability information using the NVD (National Institute of Standards and Technology) Vulnerability APIs. (Management System Dashboard)

This data is then displayed on our management dashboard, System admins can go to the management and log into the dashboard to see all software installed on any of the companies systems and the system will warn the system admins about any vulnerabilities found allowing the system admins to keep on top of exploits that may be present in software within the company. (Login Page) (Management System Dashboard)

Selecting an entry in the software list will show a more extensive view of the software, including the version of software installed, who it belongs to (so the system admins know who needs to update their software) and also the Risk analysis showing all the known vulnerabilities.
![system(https://github.com/HaydenD100/QZMangment/blob/main/qz_more.png?raw=true) (In depth view of software page)

How we built it

We build this Management software using Python Flask for the back end which interacts with a Postgres SQL database and also interacts with all Agent software written in Python. We are also using React JS for the front end

Challenges we ran into

We ran into challenges with getting accurate results with the software names that we got from the system registry, we over came the challenge by using AI to process the data before checking the data.

Accomplishments that we're proud of

We are proud of developing this software within the time frame given and also our team collaboration.

What we learned

We learned a lot about security and how integrating AI can help with certain accepts of the security analysis.

What's next for QZ Management

There's many features we want to add including adding an ai recommendation on how the the system admin should procced including recommending an upgrade to a different version but also suggests on other un compromised software.

Built With

• api
• gemini
• javascript
• postgresql
• python
• react
• security
• web