moneySCAMatters

KABAM! Money in the bank.

Inspiration

One day, our poor teammate, Emi, was SCAMMED $800 because he was texted a link from the USPS - or who he thought was the USPS. He had been trying to get his government-issued ID through the mail. He later realized that USPS mail could NOT be delivered to our campus. So when this text message, from the fake USPS, told him "Your USPS package has arrived at the warehouse and cannot be delivered to due to incomplete address information... Please confirm your address in the link." He acted swiftly to correct his address. After multiple attempts at verifying the validity of the link, the link opened to a look-a-like USPS website where he paid the "fee" to have it delivered to a new address. This was the beginning of all his troubles.

CHARGES OUT THE WAZOO were being BILLED to his account. Leading to a messy financial situation that he had to clean up with his bank. THIS SHOULD NEVER HAPPEN TO ANYONE.

What it does

moneySCAMatters protects the financial liability of vulnerable-unaware individuals. When a user is texted a link, in addition to "open with Safari, Chrome, etc", we prompt the user to "open with moneySCAMatters, Safari, Chrome". Once the user chooses to "open" then link with our application, the link and related information (the body of the message, the sender info, etc.) are parsed by our AI, ChatGPT API, and checked against our Google Cloud Database to see if it has already been documented as a scam. If it passes our database check, we send it to our VirusTotal API (an application that inspects items with over 70 antivirus scanners and URL/domain blocklisting services, in addition to a myriad of other tools). If it passes virustotal, our final check will use AI to check the domain information of the link with our jsons cross-verify it with the domain data of the entity they are claiming to be.

How we built it

With tears, fears, and engineers.

Analisa worked on the Database with scam-associated links she and her fellow teammates were texted. She used Google Cloud to host the MySQL Database and used .sql scripts to create the tables and data for known scams and the data of companies that are often impersonated (USPS, Fedex, Netflix, etc.)

Diem worked on setting up kivy with Xcode. She used her eye for aesthetics to work on front end and beautified the visuals for our users. She also worked on connecting the frontend with the backend for our project.

Emi worked on getting the API from Virus Total and setting it up so that when we run the database that Analisa created, the app is able to use Virus Total to identify which websites are a scam and which ones are not. He also worked on using ChatGPT to analyze the domain information of the link texted against the domain information of the entity the sender claimed to be.

Annalisa worked on creating simulated data to be able to parse in using chatGPT API. She worked on getting API keys, setting up the environment for openAI API to run on. She will then use LLM to analyze, isolate and clean data in order to feed into her teammate's database one it's determined that it is from an unsafe source.