Project Name: Auror Project Track: Integration Team Name: Auror Team Member(s):@auror +1 DevPost Project Link: Auror | Devpost Project Goal: Auror aims to help people share information they encounter when scammed. By sharing this information with the community, other developers can use it to blacklist addresses or domains. After users share information, we leverage Vertex AI to provide advice on preventing and remediating scams based on the timeline provided by the user. Project Value: Auror empowers users to share their scam experiences, helping to create a collective database that can be used by developers to protect the community. By using Vertex AI, we provide tailored advice on how to avoid scams and remediate after being targeted. Project Info:Auror is a platform that allows users to share scam experiences, helping others avoid similar threats. It provides real-time scam reporting, blacklisting addresses and domains, and AI-driven prevention and remediation strategies Project Website: https://auror.vercel.app/ Project Test Instructions:
Create an account or log in with your credentials.
Visit Auror to create your own scam report, and AI will generate personalized suggestions based on your input.
Use the “Upvote” or “Downvote” buttons to vote on reports. Voting data contributes to blacklisting decisions.
Project Details: Auror assists users in sharing scam information, enabling the community and developers to blacklist addresses or domains. We use Vertex AI to analyze shared data and provide prevention and remediation advice based on users’ reported timelines.
Project Milestones: 1.Initial Setup and Infrastructure(done):
-Set up the Auror platform on Google Cloud (Firebase, Vertex AI, BigQuery).
-Implement the foundational architecture for data sharing and reporting. 2.Scam Reporting Feature(done):
Develop the reporting system categorized by blockchain.
Implement backend support for managing shared scam data. 3.Community Engagement and Voting Mechanism(done):
-Implement voting (upvote/downvote) functionality on reports.
-Use voting data to influence blacklisting of addresses and domains. 4.API Development and Developer Tools(50%):
-Launch the API for developers to access scam data.
-GitHub repository (json data). 5.AI Integration with Vertex AI(50%):
-Integrate Vertex AI to analyze scam timelines.
-Develop models for scam prevention and remediation advice.
-Provide guidelines and documentation on integrating the API. 6.Machine Learning Model Enhancement:
-Continuously improve AI models based on user feedback and new data.
-Update machine learning models to provide more accurate scam prevention tips.
Welcome to season 7 of hackathon
Your project is groundbreaking knowing that it initiate fight against scammer by mobilizing the power of community driven intelligent.
Welcome to the Hackathon of season 7, I am very happy to see another project in the integration track and I have read everything that you write, please tell me how are you going to properly handle every privacy concern that will be connected to scam reporting, thank you
Welcome to hackaTron S7. When I first read the title of your project, I thought it’s going to be on real-time information of how users are going to avoid being victims of scams but reading through I understand it’s about collecting information from these users after they have become victims of scam. That then made me wonder the usability of this project since it can’t help these users on becoming scam victims neither will it make scam victims recover from their lost.
Again you said that through your project, you will help to create collective database that will be used by developers. Then my other question is in what way can this database help developers to fight against scams?
Hello Aurora, welcome to this session.
First, let get this straight. A scam victim reaching out to your project to share about their experience.
And your project will gather the information. And from your website it is stated > support affected with advice and solution.
Now the big question is, how will your project provide solutions to scam victim? By refund or? Because a scam victim reaching out to you and sharing their experience all they need at that point is REFUND and so desperate for help.
I will add that your project should clearly state the kind of solution to be given to scam victim. Thanks.
just like a sick person reaching to doctors to explain their experience to doctor, they seek medication after.
Welcome to Hackathon Season 7, your offering in my opinion raises serious concerns and produces a strong discourse.
Allowing users to share scam experiences, creating a crowdsourced database of scam information, and in turn this empowers individuals to contribute to a safer community, making it easier to detect scam patterns and hence leveraging AI to provide real-time scam reporting, blacklisting, and prevention strategies. I sense some high risks and some sort of very serious contradiction here. High risk in the sense that malicious actors could flood the platform with false reports to manipulate the blacklisting process.
What measures are in place to prevent potential abuse of the voting and reporting system?
And again, not attaching your DevPost link isn’t a good look at all.
Welcome to hackathon S7, I really like the idea behind your project am sure it will help people alot which I am still trying to figure out how you will do it.
my question is will there be any plans to partner with law enforcement agencies or other organizations to fight scams more effectively?
There is indeed a potential risk, as you pointed out.
We can only minimize it to the greatest extent possible.
We limit blacklisting based solely on voting for reports. From there, we evaluate the credibility of the users who submitted the reports.
Based on the evaluation of the reports, we can increase the trust level for each user. Reports can either be shared publicly or restricted, depending on their credibility."
thank for question,
-We provide solutions to help victims avoid losing more money, such as implementing multi-signature permissions on the TRON network to prevent easy withdrawals.
-At the same time, we encourage them to share information about the scams to help the community stay vigilant and protect one another.
Not bad, but you know that setting up the multi-sig can be very technical and most of the scam victim might not have time to check how it be done.
Would be best your resources or content should be made available for not just scam victim, because not all will each to anyone after been scammed… all the best.
Knowing that scammer has become part of the day to day activities in the cyber world,I will like to know if there’s any collaboration with the law enforcement agency or cyber security organization.
Thanks for your reply, controlled sharing of reports is a good step toward maintaining data accuracy and reducing the likelihood of manipulation.
In cases where an address or domain has been blacklisted but later found to be legitimate, how will you handle appeals and corrections?
Welcome to the hackathon season 7
I understand that not many victims of scam have the courage to tell their stories of what happened to them. I want to know how you are going to encourage these users to share their scam experiences?
Are there any measures that will ensure the quality and accuracy of these reports to avoid people coming out to tell false stories?
welcome team, not bad. I believe sharing experiences helps a lot. I have shared a lot of scam incidence here and it is helping a lot. Getting a platform to compile all these at one place for people to learn from them is cool. Personally the blacklisting wont make a change or wont make enough change. These scammers come prepared and the will use different addresses and domains for new scams
welcome,
We believe it is inevitable that there may be some confusion or false reports. However, we think such cases will be very rare, as the primary goal of the platform is to share information with the community to help prevent others from falling victim to the same scams. Most users are motivated by the desire to protect others and raise awareness, so we expect the majority of reports to be genuine.
As for users whose reports receive a lot of ‘downvotes’ due to false information, we will review the details they provide before allowing their reports to be posted
welcome,
We will have a process for addressing incorrect reports, and users can submit an issue on GitHub or through the provided form. After that, we will review and handle the blacklist accordingly.
thank for question,
At this stage, the features are being finalized, and we want to focus on the community, so initially, we will only support English.
Your project goal aims to help people share information they encounter when scammed, and your project value empowers users to share their scam experience so my question is what measures will be taken to prevent false or misleading reports, and also in what way will the database of the community be updated.