class LaylaKaddani:

    # Identity
    name        = "Layla KADDANI"
    location    = "Amiens, France | Nationwide mobility | Driving licence"
    languages   = ["French (Advanced)", "English (Advanced)", "Arabic (Native)"]

    # Education
    current     = "EiJV — Engineering Degree in Cybersecurity (CTI, SecNumedu, RNCP40947)"
    level       = "Diplôme d'ingénieure Bac+5 — expected 2028"
  

I understand connected systems from both their hardware logic and their vulnerabilities.

End-to-end Windows / Active Directory security lab covering IAM, hardening, security monitoring and detection

• Built and configured a complete Active Directory environment (cyberlab.local) with OUs, users, security groups and privileged roles
• Implemented Group Policy controls including Password Policy, Account Lockout Policy and workstation security policies
• Applied Least Privilege and (SoD) using dedicated IT and Direction roles, with access-control validation
• Hardened SMB by disabling SMBv1 and enforcing SMB Signing
• Configured and reviewed Windows Defender Firewall, Windows services and remote administration exposure through WinRM
• Collected and parsed Windows Security Event ID 4625 using PowerShell, including Logon Type and source IP analysis
• Developed a PowerShell-based detection workflow to identify repeated network authentication failures and automatically generate security alerts
• Produced structured security reports and CSV outputs for Security Monitoring and Detection Engineering

Windows Server Active Directory GPO IAM PowerShell SMB WinRM Windows Defender Firewall Security Logging Detection Engineering

Security audit of a vulnerable Web application

• Manual Code Review & Testing — analyzed PHP code, SQL queries, HTML output, forms and access controls; performed local functional security tests.
• Vulnerability Assessment — investigated SQL Injection, Stored XSS, broken access control, CSRF and server-side input validation.
• Security Tools — used Semgrep for static analysis and Burp Suite for web security testing in a local lab environment.
• Reporting & Remediation — produced technical reports with screenshots, code analysis, test evidence, impact assessments and mitigation recommendations.

PHP SQL Injection XSS Access Control CSRF Semgrep Burp Suite Docker

Location-based event sharing app — Security Lead on a team of 3

• Defense in Depth — 7 independent security layers
• Firestore Security Rules — server-side data protection independent of client code
• Privacy by Design — user location never stored, only used locally for distance filtering
• Runtime GPS permissions, unexported activities, API keys protected via .gitignore

Java Firebase Auth Firestore Google Maps SDK Cloudinary GitHub

Demonstrated a model swap attack on a cardiac risk detection AI — then built the defense

• Attack: silent model replacement inverting all diagnoses with no visible UI change
• Defense: SHA-256 integrity verification at every inference call — blocks diagnostic and triggers alert if tampering detected
• Model: Random Forest, 98.5% accuracy on Heart Disease UCI dataset

Python React scikit-learn Flask SHA-256

Real-time biometric access control deployed on Raspberry Pi

• Facial recognition with liveness detection (eye-blink EAR — anti-spoofing)
• Multi-page admin interface (PyQt5): user management, live video feed, access logs, CSV export
• Automated email alerts on intrusion attempts
• MongoDB for user and event log storage
• 🔧 Hardware: PIR sensor, servo motor, LED, buzzer

Python OpenCV dlib PyQt5 MongoDB Raspberry Pi

Full IoT smart city prototype with MQTT architecture and real-time supervision

• Flood management (ultrasonic sensor + pump relay)
• Adaptive street lighting (LDR + PIR)
• Bus tracking via RFID on ESP32
• Waste classification with YOLOv8 (Raspberry Pi + camera)
• Django web dashboard with RBAC (citizen / admin) and real-time alerts

Python Django MQTT Mosquitto ESP32 ESP8266 YOLOv8 Tkinter RFID

Python dashboard developed during my internship at Alpamare Saïdia to monitor water quality and chemical consumption

• Interactive dashboard for water quality analysis
• Monitoring of chemical consumption (chlorine, pH-, flocculant, anti-algae, etc.)
• Automatically calculates key performance indicators (chemical consumption, cost per customer, and pH compliance)
• Data cleaning and transformation from Excel
• Standalone executable generated with PyInstaller

Python Pandas Matplotlib Seaborn Excel PyInstaller