24% OFF AI Powered Internship Scam Detection
AI Powered Internship Scam Detection is a web-based project developed using Python Flask, HTML, CSS, JavaScript, Bootstrap, and SQLite. It analyzes internship and job descriptions using suspicious keyword scoring, salary pattern checks, and email and domain validation to generate a scam probability score and classify the risk as Low, Medium, or High.
Read more- Built with
- PythonMachine LearningBootstrapHTML/CSS
- You get
- Source codeDatabaseProject reportPPTSetup guide
- Delivery
- Instant download after payment
Project Overview
AI Powered Internship Scam Detection, also known as InternShield, is a web-based application designed to analyze internship and job descriptions for suspicious patterns. It uses keyword scoring and rule-based risk analysis to calculate a scam probability score and help students identify potentially risky opportunities.
Available Features
- Job Description Analyzer: Analyzes pasted internship and job details to extract key patterns.
- Salary Scam Detector: Detects unrealistic salary claims using rule-based logic.
- Suspicious Keyword Scanner: Flags suspicious phrases such as registration fee, urgent joining, and limited seats.
- Email and Domain Validation: Identifies free email domains and risky email or domain patterns.
- Scam Probability Score: Generates a score out of 100 with an explanation.
- Risk Classification: Displays Low Risk, Medium Risk, or High Risk based on the calculated score.
- Admin Dashboard: Tracks total scans, high-risk cases, and keyword frequency analytics.
- Keyword Management: Allows administrators to manage rules and keywords that affect scoring.
Technology Stack
- Backend: Python and Flask
- Frontend: HTML, CSS, JavaScript, and Bootstrap
- Database: SQLite
- Analysis Logic: NLP keyword scoring and rule-based risk analysis
Watch Project Demo
Watch AI Powered Internship Scam Detection Project Demo
More Details and Full Documentation
Visit the official project page for more details and project documentation:
- Job Description Analyzer
- Salary Scam Detector
- Suspicious Keyword Scanner
- Email and Domain Validation
- Scam Probability Score
- Risk Classification
- Admin Dashboard
- Keyword and Rule Management
- Install Python on your system.
- Open the project folder in VS Code.
- Open the VS Code terminal.
- Install Flask using the project's requirements or dependency instructions.
- Configure the SQLite database according to the project files.
- Run the Flask application using the command specified in the project.
- Open the local URL displayed in the terminal.
- Paste an internship or job description to analyze its risk.
- Review the scam probability score and risk classification.
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