BaitBlock

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  BaitBlock without emails

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  Logo

Inspiration

Our teammate's grandparents were victims of an email scam. A scammer pretended to be the teammate and tried to defraud money from the grandparents. We felt it was a great idea to design a web application to detect phishing scams using AI.

What it does

BaitBlock is a web application designed to detect and flag phishing emails, providing users with a robust defense against online scams. By leveraging advanced algorithms and the ChatGPT API, BaitBlock analyzes the content, context, and structure of emails to identify potentially malicious messages. Its primary goal is to protect users from falling victim to phishing attempts by detecting and flagging suspicious emails, thereby safeguarding personal, financial, and organizational data.

Key Features

Email Phishing Detection: BaitBlock uses the ChatGPT API to analyze the language and context of incoming emails, identifying phishing attempts through subtle indicators such as unusual requests, deceptive language, or suspicious links and attachments.

Contextual Analysis: The ChatGPT integration enables BaitBlock to understand the context of email content, such as detecting fake sender identities, misleading subject lines, and social engineering tactics designed to manipulate recipients.

Advanced Threat Intelligence: By continuously learning from flagged emails, BaitBlock enhances its detection capabilities, adapting to new phishing tactics and evolving threats.

User-Friendly Dashboard: BaitBlock offers a user-friendly interface where users can review flagged emails.

How we built it

Languages: HTML, CSS, JavaScript, Python. API: Open AI

Challenges we ran into

Implementing the open AI to analyze emails and flag phishing scams was our biggest challenge. Due to the time constraint we were in the stages of debugging and changing different features of the demo, Therefore, we were not able to complete this project as we wanted to.

We had planned to use Python to send external emails to the website, this concept was new and took time debugging but we were finally able to solve it.

Accomplishments that we're proud of

It was our first time implementing an Open AI API, into a web application. So we are proud of overcoming the challenges we faced and utilizing resources to make progress in areas that were new to us.

What we learned

We learned about security features in GitHub such as the secret variable and .env file to keep API keys safe. Our GitHub and debugging skills improved after creating BaitBlock. We learned about creating a domain and linking the web to the domain.

What's next for BaitBlock

Real-Time Flagging and Alerts: When a suspicious email is detected, BaitBlock flags it and sends an immediate alert to the user, providing details on why the email was flagged and advising on safe handling practices.

Protection Across Platforms: BaitBlock integrates with popular email clients (e.g., Gmail, Outlook) and works seamlessly across desktop and mobile devices, ensuring consistent protection regardless of where users access their emails.

Enhanced AI and Contextual Detection: BaitBlock plans to further develop its use of the ChatGPT API and other natural language processing (NLP) tools to detect increasingly sophisticated phishing techniques, such as personalized scams targeting specific individuals or organizations.

Integration with Enterprise Security Systems: BaitBlock seeks to expand its capabilities to enterprise environments, offering integration with corporate email security systems and providing detailed analytics on phishing threats targeting organizations.

Advanced Machine Learning Feedback Loops: Future iterations will include feedback loops where user interactions with flagged emails inform and improve BaitBlock’s detection algorithms, enhancing accuracy over time.

Built With

• api
• css
• godaddy
• html
• javascript
• openai
• python