01 Synopsis
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- Problem statement & objectives
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01 Synopsis
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02 Pre Defined Project Report
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03 Customized Report
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04 Originality Reviewed
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Abstract
Table of Content
Introduction
Problem Statement
Existing System
Proposed System
Objectives
System Architecture
Major Functional Modules
Hardware Requirements
Software Requirements
Future Enhancement
Conclusion
References
Abstract
Table of Content
Chapter 1 — Introduction
Chapter 2 — Literature Review / System Study
Chapter 3 — System Analysis
Chapter 4 — System Design
Chapter 5 — System Implementation
Chapter 6 — Testing
Chapter 7 — Results and Discussion
Chapter 8 — Conclusion and Future Enhancements
Chapter 9 — References
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.
| Role | Password | |
|---|---|---|
| Administrator | [email protected] |
admin123 |
| Demo User | [email protected] |
user123 |
| 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 |
The admin panel includes users, security engine, monitoring, logs, configuration, reports, exports, and backup modules
The user panel includes dashboard, secure AI chat, profile, chat history, blocked prompts, approvals, usage stats, and report issue modules
The security engine includes AI analysis, rule-based fallback, sensitive data detection, automatic masking, prompt injection detection, and account blocking rules.
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.
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.
| 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 |
cd "c:\Project\Python Source Code\AI-Based Cybersecurity System for Safe and Controlled AI Usage"
python -m venv venv
.\venv\Scripts\Activate.ps1
pip install -r requirements.txt
copy .env.example .env
Edit .env and set required values.
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.
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.
| Role | Password | |
|---|---|---|
| Administrator | [email protected] |
admin123 |
| Demo User | [email protected] |
user123 |
| 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 |