Defendr

Logo
Tech Stack
Lesson
Dating Profile
Messaging
Email
Heart Rules

Inspiration

Getting scammed is a lot like getting your heart broken. You put your trust in someone and they end up taking advantage of you.

Our team was inspired to create Defendr to make sure no one experiences heartbreak again (at least from scams) and our personal experience with close friends recently getting scammed around a similar time.

As threats to cyber security become more creative and pervasive, we recognized the urgent need for a tool that could help people protect themselves. In particular, we wanted to create a solution that could benefit our parents, grandparents, and friends, who may be less tech-savvy and more vulnerable to online scams.

We believe that education and awareness are essential in preventing people from becoming victims of scams. Defendr is designed to teach users how use their analytical skills in searching for red flags in dating profiles and applying that to scam threats. Everyone deserves to feel safe and secure online, and we are proud to create a solution that helps people stay protected from scams by enjoying the process of learning how to do so.

What it does

Defendr teaches scam defense as a dating app through a two-fold process: education and practice. There a three lesson and practice tracks that you can choose from: Friends (friends that could have hacked), Strangers (promotions and phishing), and Workplace (phishing and credit card fraud).

Friend Track

Users are tasks to view different personas as if they were on a dating app. By reading more about your personal relationship with them, bond level, and their interests, you can gather data about the person to determine whether the persona has been hacked. If more information is needed, users can also choose to chat with the personas to practice recognizing the warning signs of online scams from people you know.

Stranger Track

In the Stranger Track, users are presented with a series of email messages that are designed to simulate phishing and promotional scams. By interacting with these messages, users can learn to recognize the warning signs of online scams from strangers, such as suspicious URLs and suspicious requests for personal information.

Workplace Track

Combines elements of both the Friend and Stranger tracks, presenting users with a variety of personas and email messages to test their ability to recognize and avoid online scams in a professional context from coworkers and external sources.

In each respective practice, a user will have 3 hearts. A user will have to chose whether to block or match (i.e trust) a persona. Each time a persona/email is falsely identified as a spam (blocked) or a spam persona/email is falsely trusted (matched) a heart will be broken. Once all three tasks have been completed, the user may try redo the task to achieve no hearts broken.

Through these interactions, users build intuition on how to avoid creative methods of scam in various settings. They develop critical thinking skills that help them to identify inconsistencies in a persona's story, recognize common tactics used by scammers, and spot red flags that signal a potential scam.

How we built it

created wireframes on Figma
designed low to high fidelity mockups
next.js, react, typescript, tailwind tech stack with a firebase authentication to sign in users and store data
built API routes to populate certain interfaces for users and personas
utilized Redux to pass global states and persist login
Referenced Cohere API to generate confidence intervals to provide analysis for user input related to scams

Challenges we ran into

learning for the first time typescript and next.js
only familiar with react express and javascript tech stack
- new to rendering pages
never used tailwind
- styling and animating components took longer than expected

Accomplishments that we're proud of

fully prototyped hi-fidelity design
completed chat feature
building a deployable app

What we learned

learning typescript, next.js, and tailwind for the first time
first time working with a designer
first time working together as a team
what its like to compete in an in-person hackathon

What's next for Defendr

implement AI to further create relevant chat responses, personas, and emails
- as online scammers become more sophisticated and creative, Defendr may need to continually update and innovate its technology in order to stay ahead of the curve and offer users the best possible protection
build a more comprehensive curriculum