PingPoint

Logo
Dashboard

Inspiration

Most of us took Ming Chow's CS116 Intro to Security Class and wanted to explore topics of network security more. Even though we had some exposure we there was so much unknown especially to people without any CS/security background. Our goal was to increase transparency and literacy on the more and more important domain of network security.

What it does

Can run a scan for all packets sent across your local network and display all associated devices / IPs in a node graph. Gives general LLM response and device specific responses based off security risks, health, and next steps for any problems. Runs nmap scans across all devices to discover open ports and other vulnerabilities. Generates graphs of packets of time, spikes, and suspicious activity detected from specific attack packet signatures.

How we built it

We used a Raspberry Pi 5.0 as a proxy in a network to parse through all network traffic. On this device we host all our backend scripts to analyze, parse, and send output to our web app. We use React, Nextjs, FastApi, Vercel, and ngrok

Challenges we ran into

Hosting our own local network with internet to use as our experimental playground. Also ran into a lot of hardware problems when connecting to our Pi over the network and communicating with it via HTTP requests both on local and deployed versions.

Accomplishments that we're proud of

Having a working product before the deadline with many moving parts.

What we learned

We learned a lot about linux, self hosting, setting up our own network and computer environments, and security tools.

What's next for PingPoint

Login authentication and device pairing with specific device IPs to detect network traffic on. Giving all external IP devices actual hostnames. Structured LLM responses. Threading nmap commands rather than a queue. Custom scan duration.