Aegis.ai

The extension

Inspiration

The internet has become increasingly unsafe, especially for students, job seekers, freelancers, and everyday users who face fake internships, phishing emails, investment scams, and fraudulent financial pages. These threats often look legitimate on the surface, making them easy to fall for. We wanted to create a simple, instant, and trustworthy layer of protection that helps people understand whether a link, post, or webpage is safe before they interact with it. That idea became Aegis.ai.

What it does

Aegis.ai is a browser extension that scans webpages, emails, job postings, and financial links to detect warning signs of scams or fraud. It analyzes:

Suspicious keywords, red-flag language, and impersonation patterns
Phishing indicators
Fake job/internship templates
Financial risks such as unrealistic investment claims or unsafe payment pages
Metadata and structural anomalies often found in scam sites

The result is shown as a simple rating: Safe ✔ | Suspicious ⚠ | Dangerous ✖

A Premium concept version adds deeper scanning, scam history tracking, and early alerts for new fraud patterns.

How we built it

The extension combines:

JavaScript, HTML/CSS
Browser extension APIs
AI/NLP models for language analysis
Custom heuristics for financial and phishing detection
A modular structure that allows rapid updates as scam patterns evolve

All processing is lightweight, fast, and privacy-focused, running directly in the browser.

Tracks: ✔ Artificial Intelligence & Machine Learning ✔ FinTech & Digital Economy

Challenges we ran into

Designing a detection system that works reliably across different types of webpages.
Keeping the extension lightweight without compromising risk analysis.
Ensuring clear communication of risk without overwhelming users.
Navigating constraints around publishing and distributing browser extensions.

Accomplishments that we're proud of

Built a functional, user-friendly safety tool within a very short timeframe.
Achieved consistent detection of phishing cues and suspicious financial content.
Designed an interface suitable for both tech and non-tech users.
Created a solution that blends AI, safety, and digital trust in a practical way.

What we learned

How AI can be applied to real-world scam and fraud detection.
How online threats evolve, especially in job markets and digital finance.
How important UI clarity is for trust and adoption.
How browser extension architecture can be adapted quickly for security use cases.