Phishing Abhiyan
Navigating the Phishing Maze: - Your Trusted Ally
Created on 27th June 2024
•
Phishing Abhiyan
Navigating the Phishing Maze: - Your Trusted Ally
The problem Phishing Abhiyan solves
Our system addresses the outlined problems by integrating various advanced features and technologies to create an effective and comprehensive phishing simulation platform.
Features and Implementation
- Reconnaissance Dashboard
Login and Campaign Management: Users can log in to a dashboard to view and manage phishing campaigns.
Campaign Analytics and Visualizations: Visualizations for past campaigns, including success rates and detailed metrics.
Email Address Gathering:
Automated tools and techniques to gather email addresses.
Email verification tools to validate addresses and filter out inactive ones.
Option for manual CSV upload to add additional email addresses. - Email Profiling
Automated Profiling: Use of web scraping and APIs to gather profile information (e.g., social media data, job titles).
Manual Profiling: Users can upload CSV files to manually add or correct profiling data.
Comprehensive Profiles: Detailed profiles including parameters like age, gender, country, job title, interests, etc. - AI-Driven Phishing Email Generation
Model Training: Using a dataset of spam emails to train an AI model capable of generating phishing emails.
Phishing Email Creation: Generating realistic phishing emails tailored to mimic the communication style of the target domain.
Campaign Execution: Automated bot to send phishing emails and track performance metrics (e.g., open rates, click rates). - Bot Communication and Validation
AI Personas: Creating AI personas that simulate real users to respond to phishing emails.
Phishing Attempt Refinement: Evaluating responses and refining phishing email content until successful.
IP Tracking and Geolocation: Tracking the IP addresses of recipients and identifying their geolocation for better targeting and analysis.
Additional Feature: IP Tracking and Geolocation
IP Tracking: Logging IP addresses of phishing email recipients.
Geolocation: Using IP geolocation services to identify the ge
Challenges we ran into
-
Integration of Multiple Functionalities:
- Email Fetching (MailScout): Integrating the functionality to fetch emails using MailScout for both single and bulk data.
- Email Scraping (URLs): Adding the ability to scrape emails from a list of URLs.
- Email Deduplication: Ensuring the emails fetched or scraped are unique and removing duplicates.
-
File and Directory Management:
- Static and Template Files: Ensuring the correct placement and referencing of static files (CSS, JS) and template files (HTML) in the appropriate directories.
- Conflicting File Names: Managing multiple index.html files and renaming them appropriately to avoid conflicts.
-
Handling Multiple Inputs and Fetch Types:
- Single Input Handling: Accepting single or multiple names and a domain for email fetching.
- Bulk Input Handling: Parsing and processing bulk email data in JSON format.
- URL Input Handling: Accepting a list of URLs for email scraping.
-
Form Handling and Validation:
- Dynamic Form Display: Displaying different input fields based on the selected fetch type (single, bulk, URLs).
- Data Validation: Validating and parsing input data correctly from the forms.
-
API and Backend Logic:
- Flask Routes: Creating routes to handle different types of email fetching requests.
- Error Handling: Providing meaningful error messages for invalid input or fetch types.
-
Script and Module Management:
- Script Execution: Ensuring scripts are executed correctly in the environment, including resolving module import issues and handling relative imports.
- Dependency Management: Installing necessary dependencies using pip.
-
Cross-Platform Compatibility:
- Running Commands: Adapting commands for both Windows and Unix-based systems to ensure compatibility.
- User Experience:
- User Interface: Designing a user-friendly interface for input generative model responses.
Discussion
Builders also viewed
See more projects on Devfolio