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MCA Project Report
MCA AI-Based Cybersecurity System Final Year Project Report
Get structured MCA AI-Based Cybersecurity System Final Year Project Report Final Year Project Report and Documentation with project objectives, methodology, system design, diagrams, implementation details, testing and complete project explanations. Suitable as a learning, documentation and project-presentation resource for students working on related final year projects.
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Abstract
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Table of Content
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01
Introduction
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02
Problem Statement
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03
Existing System
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04
Proposed System
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05
Objectives
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06
System Architecture
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07
Major Functional Modules
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08
Hardware Requirements
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09
Software Requirements
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10
Future Enhancement
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11
Conclusion
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12
References
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Abstract
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Table of Content
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01
Chapter 1 — Introduction
- 1.1 Background of the Project
- 1.2 Problem Statement
- 1.3 Objectives of the System
- 1.4 Scope of the Project
- 1.5 Existing System Overview
- 1.6 Proposed System Overview
- 1.7 Technologies Used
- 1.8 Overview
- 1.9 Limitations
- 1.10 Advantages
- 1.11 Disadvantages
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02
Chapter 2 — Literature Review / System Study
- 2.1 Introduction
- 2.2 Review of Similar Systems
- 2.3 Comparative Analysis
- 2.4 Software Development Models
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03
Chapter 3 — System Analysis
- 3.1 Introduction
- 3.2 Functional Requirements
- 3.3 Non-Functional Requirements
- 3.4 User Requirements
- 3.5 Feasibility Study
- 3.5.1 Technical Feasibility
- 3.5.2 Economic Feasibility
- 3.5.3 Operational Feasibility
- 3.6 System Architecture
- 3.7 Data Flow Diagram (Level 0)
- 3.8 Data Flow Diagram (Level 1)
- 3.9 Data Flow Diagram (Level 2)
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04
Chapter 4 — System Design
- 4.1 Introduction
- 4.2 Use Case Diagram
- 4.3 Class Diagram
- 4.4 Sequence Diagram
- 4.5 Activity Diagram
- 4.6 ER Diagram
- 4.7 Database Schema
- 4.8 Table Structures
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05
Chapter 5 — System Implementation
- 5.1 Introduction
- 5.2 Development Environment
- 5.3 Tools and Technologies Used
- 5.4 Hardware Requirements
- 5.5 Software Requirements
- 5.6 Module-wise Implementation
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06
Chapter 6 — Testing
- 6.1 Introduction
- 6.2 Testing Strategy
- 6.3 Unit Testing
- 6.4 Integration Testing
- 6.5 System Testing
- 6.6 Test Cases
- 6.7 Bug Reports
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07
Chapter 7 — Results and Discussion
- All screenshots
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08
Chapter 8 — Conclusion and Future Enhancements
- 8.1 Conclusion
- 8.2 Future Enhancements
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09
Chapter 9 — References
Project's Overview
AI-Based Cybersecurity System for Safe and Controlled AI Usage is a Flask-based cybersecurity web application designed to provide safe, monitored, and controlled AI chat access for colleges, enterprises, and organizations. The platform scans every user prompt before sending it to OpenAI, performs AI-based risk scoring, masks sensitive data, blocks malware/phishing/injection/policy-violating requests, and gives administrators full control over users, rules, approvals, logs, exports, and system policies.
The system includes a secure user panel for AI chat, prompt safety results, usage limits, safe templates, chat history, blocked prompt tracking, approval requests, and false-positive reporting. It also includes a powerful admin panel for user CRUD, security policy management, prompt monitoring, approvals, incident review, usage logs, security logs, login history, audit trail, OpenAI settings, branding, system settings, reports, CSV/Excel export, and database backup.
This project is suitable for B.Tech, M.Tech, BCA, MCA, BE, ME, BSc, and MSc students who need a practical final year project, major project, or minor project based on cybersecurity, AI safety, secure AI chat, prompt injection detection, sensitive data masking, Flask development, OpenAI API integration, audit logging, admin dashboard, policy control, and secure web application design. FileMakr can provide this project with source code, project report, documentation, and setup support for academic submission.
Login Credentials
Primary Seeded Accounts
| Role | Password | |
|---|---|---|
| Administrator | [email protected] |
admin123 |
| Demo User | [email protected] |
user123 |
Additional Demo Accounts
| Role | Password | Notes | |
|---|---|---|---|
| Normal User | [email protected] |
user123 |
Active student with chat history |
| Normal User | [email protected] |
user123 |
Active student |
| Normal User | [email protected] |
user123 |
Blocked — test unlock flow |
| Restricted User | [email protected] |
user123 |
Daily limit: 20 |
| Security Reviewer | [email protected] |
reviewer123 |
Reviewer role |
Related & Popular Reports
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- Secure administrator login in this final year project
- Administrator role-based access
- Admin dashboard
- View system statistics
- View risk category charts
- View daily usage charts
- Quick action shortcuts
- Manage users
- Search users
- List all users
- View user detail
- Update user profile
- Update user role
- Update user status
- Update prompt limits
- Update feature access
- Reset user password
- Unlock user account
- Delete user
- Create new user accounts
- Review user false-detection reports
- Update report status
- Add admin remarks
- Manage blocked keywords
- Add high-risk keywords
- Toggle blocked keywords
- Delete blocked keywords
- Manage allowed keywords
- Whitelist educational keywords
- Manage prompt risk categories
- Manage regex-based security rules
- Add security rules
- Toggle security rules
- Delete security rules
- Manage sensitive data patterns
- Configure PII detection regex patterns
- Manage masking rules
- Configure mask tokens by data type
- Manage risk score ranges
- Define low, medium, high, and critical score ranges
- Configure account blocking rules
- Auto-block based on critical prompts
- Auto-block based on failed logins
- Monitor all prompts
- Review latest 200 prompts
- Open prompt detail modals
- Monitor blocked prompts
- Filter blocked prompts by user
- Monitor sensitive data incidents
- View detected and masked sensitive data logs
- Manage approval requests
- Approve pending prompt requests
- Reject pending prompt requests
- Update approval status
- View usage logs
- Track OpenAI API calls
- Track token usage
- Track request duration
- Track API errors
- View security logs
- Track block events
- Track injection attempts
- Track account actions
- View login history
- Track login/logout sessions
- Track failed login attempts
- Track IP addresses
- View audit trail
- Track admin actions
- Track user updates
- Track approvals
- Track backups
- Manage OpenAI settings
- Configure model
- Configure token limit
- Configure temperature
- Configure system instruction
- Toggle API usage
- Manage safe templates
- Create pre-approved prompt templates
- Manage warning messages
- Customize block, warn, and mask messages
- Manage branding
- Configure app name
- Configure tagline
- Configure titles
- Configure footer
- Configure support email
- Manage system settings
- Enable or disable maintenance mode
- Enable or disable registration
- Configure limits
- Configure session timeout
- Run database backup
- Export daily prompts
- Export blocked prompts
- Export user activity
- Export API usage reports in CSV/Excel
The admin panel includes users, security engine, monitoring, logs, configuration, reports, exports, and backup modules
- User registration in this final year project
- User login
- Password reset
- User logout
- Secure AI chat
- Submit prompts safely
- View security analysis result
- View risk badges
- Receive AI response after safety checks
- Use safe prompt templates
- Request approval for blocked prompts
- Dashboard with daily prompt limit
- Dashboard with usage stats
- View recent chats
- Quick action shortcuts
- Profile management
- Update name
- Update department
- Update course
- Update contact details
- Change password
- Chat history
- View all past prompts
- Open prompt detail modal
- Delete single history entry
- Clear complete chat history
- Blocked prompts page
- View read-only list of blocked prompts
- Approval tracking
- View pending approval requests
- View approved requests
- View rejected requests
- Usage statistics
- View personal API usage
- View token counts
- View prompt statistics
- Report incorrect detection
- Report false-positive blocks
- View submitted reports
- View admin responses
The user panel includes dashboard, secure AI chat, profile, chat history, blocked prompts, approvals, usage stats, and report issue modules
Security Engine Features in this final year project
- GPT-powered AI security analyzer
- JSON risk analysis
- Risk score generation
- Risk level classification
- Recommended action: allow, warn, mask, or block
- Blocking reason generation
- Rule-based fallback engine
- Regex security rules
- Blocked keyword detection
- Allowed keyword handling
- Sensitive data detection
- Email detection
- Phone number detection
- Aadhaar detection
- PAN detection
- Credit card detection
- API key detection
- Password detection
- Automatic sensitive value masking
- Prompt injection detection
- Jailbreak pattern detection
- Instruction override detection
- Command execution pattern detection
- Account blocking rules
- Auto-block after critical prompts
- Auto-block after blocked prompt threshold
The security engine includes AI analysis, rule-based fallback, sensitive data detection, automatic masking, prompt injection detection, and account blocking rules.
Security Workflow in this final year project
User submits prompt
↓
Sensitive data scan
↓
Mask emails, phones, API keys, passwords, etc.
↓
AI Security Analyzer + Rule Engine
↓
Risk score, level, and action generated
↓
If unsafe: block prompt and save reason
↓
If safe/warn/mask: send safe prompt to OpenAI
↓
AI response generated and logged
Security analysis uses gpt-4o-mini for fast JSON scoring, while user responses use gpt-4o, configurable from Admin → OpenAI Settings.
Other Features in this final year project
- Flask web application
- Multi-layer AI security engine
- Safe and controlled AI usage
- Prompt risk scanning before OpenAI request
- Sensitive data masking before AI processing
- Dangerous request blocking
- Audit trail
- Approval workflow
- False-positive report workflow
- Daily usage limits
- Chat history
- Admin incident review
- CSV report export
- Excel report export
- Database backup
- Branding configuration
- OpenAI model configuration
- System configuration
- SQLite default database
- PostgreSQL production support
- Bootstrap-based responsive UI
- Chart.js dashboard charts
- Flask-WTF forms
- CSRF protection
- Flask-Login authentication
- Werkzeug password hashing
- Python dotenv environment configuration
- Sample/dummy data seeding
The technology stack includes Python, Flask, Flask-Login, Werkzeug, Flask-SQLAlchemy, SQLite/PostgreSQL, Flask-WTF, OpenAI API, Bootstrap, Chart.js, Pandas, openpyxl, and python-dotenv.
Technology Used in this final year project
| Layer | Technology |
|---|---|
| Backend | Python 3.10+, Flask 3.0 |
| Authentication | Flask-Login, Werkzeug password hashing |
| Database ORM | Flask-SQLAlchemy |
| Database | SQLite default, PostgreSQL production |
| Forms / CSRF | Flask-WTF, WTForms |
| AI / LLM | OpenAI API, gpt-4o, gpt-4o-mini |
| Frontend | Bootstrap 5, Bootstrap Icons, Inter font |
| Charts | Chart.js |
| Reports / Export | Pandas, openpyxl |
| Configuration | python-dotenv |
| Architecture | Flask app factory, blueprints, services, templates |
Step 1: Open project folder
cd "c:\Project\Python Source Code\AI-Based Cybersecurity System for Safe and Controlled AI Usage"
Step 2: Create virtual environment
python -m venv venv
Step 3: Activate virtual environment
.\venv\Scripts\Activate.ps1
Step 4: Install dependencies
pip install -r requirements.txt
Step 5: Configure environment file
copy .env.example .env
Edit .env and set required values.
Step 6: Run application
python run.py
Open in browser:
| Page | URL |
|---|---|
| Landing Page | http://127.0.0.1:5000 |
| User Panel | http://127.0.0.1:5000/user/dashboard |
| Admin Panel | http://127.0.0.1:5000/admin/dashboard |
On first run, the database is automatically created and default configuration with sample data is seeded.
Environment Variables
Create .env in the project root:
FLASK_SECRET_KEY=your-random-secret-key
OPENAI_API_KEY=sk-...
DATABASE_URL=sqlite:///cybersecurity_ai.db
| Variable | Description |
|---|---|
FLASK_SECRET_KEY |
Flask session signing key |
OPENAI_API_KEY |
OpenAI API key |
DATABASE_URL |
Database connection string |
The uploaded documentation lists Flask secret key, OpenAI API key, and database URL as environment variables.
README Included
Setup Support Available
Primary Seeded Accounts
| Role | Password | |
|---|---|---|
| Administrator | [email protected] |
admin123 |
| Demo User | [email protected] |
user123 |
Additional Demo Accounts
| Role | Password | Notes | |
|---|---|---|---|
| Normal User | [email protected] |
user123 |
Active student with chat history |
| Normal User | [email protected] |
user123 |
Active student |
| Normal User | [email protected] |
user123 |
Blocked — test unlock flow |
| Restricted User | [email protected] |
user123 |
Daily limit: 20 |
| Security Reviewer | [email protected] |
reviewer123 |
Reviewer role |