Zahra Al Salili

Cybersecurity Specialization · Cohort 2025

AI-Powered Vulnerability Scanner for E-Commerce Android Applications

This project focuses on utilizing Artificial Intelligence (AI) to strengthen the security posture of Jarir e-commerce website and its associated mobile application. The project will explore AI-driven solutions for threat detection, vulnerability assessment, and continuous monitoring to identify and mitigate risks in real-time. Additionally, AI will be used to review and optimize both the website and mobile app for security, performance, and user experience. Key objectives include: 1. AI for Threat Detection: Implementing machine learning algorithms to analyze user behaviors, traffic patterns, and interactions to identify anomalous activities such as fraud, data breaches, and bot attacks. 2. Vulnerability Scanning: Using AI-powered tools to scan for security vulnerabilities on the website and mobile app code, identifying common issues and insecure APIs. 3. Automated Penetration Testing: Leveraging AI to perform automated penetration testing, simulating real-world cyberattacks on the e-commerce platform to identify weaknesses and suggest corrective actions. 4. Real-Time Risk Monitoring: Deploying AI-based solutions for real-time monitoring, alerting on suspicious activity, and quickly responding to potential threats. 5. Mobile App Security Optimization: Utilizing AI to analyze and enhance mobile app security, ensuring data protection, secure authentication, and adherence to best practices for mobile security. This project provides an opportunity to work with cutting-edge AI tools, gain hands-on experience in securing e-commerce platforms, and contribute to the development of robust, future-proof security strategies for both websites and mobile applications.

Mentor: Ali Hassan & Mahmoud Ellouh

See it in the program report (PDF)