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1- 🔐 Cybersecurity and Social Engineering / Main Repository

Main repository for the PUC-SP 5th Semester Academic Hub (2026) — focused on Cybersecurity & Social Engineering, featuring hands-on labs, ethical hacking simulations, AI security practices, threat analysis, and applied defense strategies aligned with real-world security scenarios.

Cybersecurity and Social Engineering Integrated Project - PUC-SP 5th Semester (2026)

Institution: Pontifical Catholic University of São Paulo (PUC-SP Humanistic AI & Data Science • 5º Semestre • 2026
School: FACEI - Faculty of Interdisciplinary Studies
Course Repo: INTEGRATED PROJECT: Cybersecurity and Social Engineering - 72 Hours
Professor: ✨ Eduardo Savino Gomes
Extensionist Activities: Social projects with open-source software for community support.

Note

⚠️ Heads Up

• Projects and deliverables may be made publicly available whenever possible.

• The course emphasizes practical, hands-on experience with real datasets to simulate professional consulting scenarios in the fields of Machine Learning and Neural Networks for partner organizations and institutions affiliated with the university.

• All activities comply with the academic and ethical guidelines of PUC-SP.

• Any content not authorized for public disclosure will remain confidential and securely stored in private repositories.

Table of Contents

• Course Overview
• Core Areas
• Objective
• Core Learning Pillars
• Weekly Classes Schedule
• Folder Structure
• Related Project Repositories
• Professor Information
• Quick Start Guide
• Grading & Assessment
• Learning Resources
• Tooling Stack
• Contributing Guidelines
• License
• Repository Stats

Course Overview

This repository serves as the central academic and practical hub for a course in Cybersecurity, Social Engineering, AI System Protection, and Ethical Hacking.

It is designed to integrate theoretical foundations, applied methodologies, and real-world perspectives, preparing learners for modern security challenges.

Core Areas

• Cybersecurity Foundations — principles, threats, and defense strategies
• Social Engineering — human factors, persuasion, and attack vectors
• AI System Protection — securing intelligent systems and mitigating adversarial risks
• Ethical Hacking — penetration testing concepts and responsible exploitation

Objective

The course aims to develop a comprehensive understanding of vulnerabilities across both technical systems and human behavior, enabling learners to:

- Master core cybersecurity principles and architectures.
- Identify + mitigate social engineering threats (phishing, pretexting).
- Protect AI/ML systems against adversarial attacks + model poisoning.
- Apply encryption + authentication mechanisms correctly.
- Conduct ethical security testing (penetration testing, CTF).
- Design defensive strategies aligned with AI ethics standards.

With a strong focus on AI-driven environments and emerging risks.

Core Learning Pillars

Pillar	Technical Focus	Applied Outcome	Kid Analogy
Cybersecurity Foundations	Encryption, IDS/IPS, firewalls	Infrastructure protection	Digital castle walls
Social Engineering	Phishing, pretexting, baiting	Human risk mitigation	Tricking the guards
AI Security	Adversarial ML, model poisoning	Secure ML pipelines	Poisoning the well
Ethical Hacking	Penetration testing, CTF	Attack simulation	Friendly spy games
Pillar	Technical Focus	Applied Outcome	Kid Analogy
------------	-------------------	-------------------	-----------------
Cybersecurity Foundations	Encryption, IDS/IPS, firewalls	Infrastructure protection	Digital castle walls
Social Engineering	Phishing, pretexting, baiting	Human risk mitigation	Tricking the guards
AI Security	Adversarial ML, model poisoning	Secure ML pipelines	Poisoning the well
Ethical Hacking	Penetration testing, CTF	Attack simulation	Friendly spy games

Course Scope

72-hour comprehensive program covering:

• Authentication + password security
  
• Malware analysis + threat actors
  
• Network security fundamentals
  
• Cryptography + secure communication
  
• Social engineering tactics + prevention
  
• AI applications in cybersecurity
  
• Ethical hacking methodologies
  
• Defense architecture design
  

Weekly Roadmap /Classes Schedule

Week	Date (2026)	Topic	Status
1	Feb 2	Introduction to Cybersecurity	📋 Planned
2	Feb 9	Authentication & Passwords	📋 Planned
3	Feb 16	Malware & Threat Actors	📋 Planned
4	Feb 23	Network Security	📋 Planned
5	Mar 2	Encryption & Cryptography	📋 Planned
6	Mar 9	Social Engineering Fundamentals	📋 Planned
7	Mar 16	Phishing & Pretexting	📋 Planned
8	Mar 23	Midterm Labs & Review	📋 Planned
9	Mar 30	Advanced Social Attacks	📋 Planned
10	Apr 6	AI in Cybersecurity	📋 Planned
11	Apr 13	Defensive Architectures	📋 Planned
12	Apr 20	Ethical Hacking	📋 Planned
13	Apr 27	Real Case Studies	📋 Planned
14	May 4	Group Projects	📋 Planned
15	May 11	Presentations	📋 Planned
16	May 18	Advanced Topics	📋 Planned
17	May 25	AI Ethics & Compliance	📋 Planned
18	Jun 1	Final Assessment	📋 Planned

Extension & Applied Projects / Repositories

Project	Description	Status
Phishing Detector	Machine Learning model to detect fraudulent emails	Coming Soon
Social Engineering Simulator	Awareness training simulation	Coming Soon
AI Security Toolkit	Monitoring and protection utilities	Coming Soon
CTF Challenges	Capture The Flag exercises	Coming Soon

Important

Projects are structured to be publicly documented and version-controlled.

💌 Let the data flow... Ping Me !

🛸๋ My Contacts Hub

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Copyright 2026 Quantum Software Development. Code released under the MIT license.

Objective

The course aims to develop a comprehensive understanding of vulnerabilities across both technical systems and human behavior, enabling learners to:

- Identify and analyze security weaknesses
- Understand attack methodologies
- Anticipate complex threat scenarios
- Design and implement effective defensive solutions

with a strong focus on AI-driven environments and emerging risks.

💌 Let the data flow... Ping Me !

🛸๋ My Contacts Hub

────────────── ⊹🔭๋ ──────────────

➣➢➤ Back to Top

Copyright 2026 Quantum Software Development. Code released under the MIT license.