University of Bahrain

College of Information Technology

Department of Information Systems

PhishArena: An Interactive AI-Based Platform for Phishing Awareness and Detection

📄 View Resources 👥 Meet the Team 📧 Contact Us

Abstract

PhishArena is an interactive cybersecurity platform designed to simulate real-world phishing attacks and improve user awareness through practical experience. Instead of relying only on theoretical knowledge, the system provides structured, scenario-based training where users engage with realistic phishing situations.

Powered by AI and Large Language Models (LLMs), the platform evaluates user responses based on professionalism, realism, and completeness, providing intelligent feedback to improve understanding of social engineering attacks.

Project Objectives

1

Improve Phishing Awareness

Enhance users’ ability to identify and respond to phishing attacks through realistic training scenarios.

2

Provide Interactive Learning

Create an engaging and practical environment that goes beyond traditional theoretical awareness methods.

3

Simulate Real Email Systems

Replicate real-world email environments such as Outlook and Thunderbird to improve hands-on experience.

4

Integrate AI-Based Feedback

Use AI and LLM technologies to analyze responses and provide intelligent feedback and explanations.

Problem Statement

1

Lack of Practical Training

Many cybersecurity awareness programs focus mainly on theoretical knowledge rather than practical phishing detection skills.

2

Evolving Phishing Techniques

Attackers continuously improve phishing methods, making malicious emails harder for users to identify and detect.

3

Human Error in Cybersecurity

Human mistakes remain one of the leading causes of cybersecurity breaches, highlighting the need for better awareness solutions.

Key Features

📧

Realistic Email Simulation

Simulates real-world email environments to help users experience phishing scenarios in a practical way.

🤖

AI-Powered Feedback

Uses AI and Large Language Models to evaluate user responses and provide intelligent explanations and feedback.

🎮

Interactive Learning

Provides a gamified and engaging learning experience instead of traditional static cybersecurity training methods.

🛡️

Phishing Awareness Training

Helps users improve their ability to identify suspicious emails and reduce risks caused by phishing attacks.

Instant Response Evaluation

Analyzes submitted responses instantly and generates quick feedback to improve user decision-making skills.

Methodologies and Approach

PhishArena System Architecture

📧 Email-Based Mode
User Device
Thunderbird Client
Postfix SMTP Server
Maildir Storage
⚙️ Core Services
Flask Web Application
AI Evaluation Module
Feedback & Scores
🌐 Web Testing Mode
Browser Interface
Message Submission
Instant AI Response
📥 Dovecot IMAP Server
🗂️ Case Data / Profiles
📊 Logs & Progress Storage
🖥️ Dashboard

The PhishArena architecture combines realistic email communication with AI-powered evaluation services using Flask, SMTP/IMAP servers, and Large Language Models (LLMs).

Technology Used

AI & Backend

Ollama (LLM)

Flask (Python)

System Environment

Ubuntu Operating System

Frontend

HTML

CSS

JavaScript

System Deployment

🐧

Ubuntu Environment

The platform is deployed on Ubuntu Linux to provide a stable and secure environment for backend services and AI integration.

📧

Postfix SMTP

Postfix is used to manage SMTP communication and simulate realistic phishing email delivery scenarios.

📥

Dovecot IMAP

Dovecot handles IMAP services and mailbox access for receiving and managing user email interactions.

🤖

Ollama LLM

Ollama powers the AI evaluation process by analyzing user responses and generating intelligent feedback.

Flask Backend

Flask connects all system components together and processes communication between the frontend and AI services.

🌐

Web Interface

The web interface allows users to interact with the platform, submit responses, and receive evaluation results instantly.

Experimental Demonstration Workflow

The PhishArena platform operates within a dedicated experimental environment that integrates Ubuntu-based services, AI evaluation modules, and email simulation systems. The following workflow demonstrates how the platform is launched and used during testing and demonstrations.

1

Launch Virtual Machine

Start the Ubuntu-based environment containing Flask services, SMTP/IMAP servers, and AI modules.

2

Open Platform Interface

Access PhishArena through Thunderbird or the web-based interface for phishing simulation.

3

AI Evaluation Process

The system analyzes user responses using Large Language Models and generates intelligent feedback.

4

View Results & Progress

Users receive feedback, scores, and progress tracking after completing phishing scenarios.

🐧 Ubuntu VM
📧 SMTP / IMAP
🤖 Ollama LLM
⚡ Flask Backend

AI Model Evaluation

Different Large Language Models (LLMs) were tested to evaluate their phishing detection performance based on accuracy, response time, and practical usability within the PhishArena platform.

Accuracy vs. Generation Time

0%
20%
40%
60%
80%
100%
0s
10s
20s
30s
Llama 3.2:1B
Accuracy: 88%
Time: 4.8s
Qwen3:1.7b
Accuracy: 82%
Time: 6.2s
Gemma3:1b
Accuracy: 76%
Time: 5.9s
Qwen + all-minilm
Accuracy: 79%
Time: 4.5s
Phi4-mini
Accuracy: 64%
Time: 4.1s
Model Configuration Accuracy Avg Generation Time
Llama 3.2:1B + mxbai-embed-large 88% 4.8s
Qwen3:1.7b + mxbai-embed-large 82% 6.2s
Gemma3:1b + mxbai-embed-large 76% 5.9s
Qwen3:1.7b + all-minilm 79% 4.5s
Phi4-mini + all-minilm 64% 4.1s

Chosen Model: llama3.2:1B

Llama 3.2:1B was selected as the primary AI model due to its fast response time, lightweight deployment, and smooth real-time interaction through Ollama, making it suitable for interactive phishing awareness simulations.

Future Enhancements & Impact

Summary

PhishArena demonstrates how AI-powered phishing awareness platforms can provide realistic cybersecurity training through interactive simulations and intelligent response evaluation. By integrating LLM technologies with email-based environments, the platform enhances phishing detection skills while improving user awareness in a practical and engaging way.

Future Enhancements

  • Multi-language phishing scenario support
  • Advanced phishing email generation using AI
  • User performance analytics dashboard
  • Expanded real-world phishing case library

Intelligence & Scalability

  • Support for larger and more advanced LLM models
  • Adaptive AI feedback based on user behavior
  • Cloud-based deployment for larger environments
  • Real-time phishing campaign simulation

Impact: PhishArena bridges the gap between theoretical cybersecurity awareness and practical phishing detection by creating an immersive AI-driven training environment that improves user readiness against phishing attacks.

About the Project, Team & Instructor

This project is a Final Year Senior Project completed during Semester 2 of the Academic Year 2025/2026 at the College of Information Technology — University of Bahrain.

Development Team

Cybersecurity Graduates - Batch 2026

Project Supervisor

We sincerely appreciate Dr. Abdulla Khalifa Aldoseri for his continuous supervision, valuable feedback, and academic guidance throughout the development of PhishArena. His support and expertise played a significant role in shaping the project and improving its technical and research aspects.