SecureBank Open Banking API: Building a Secure API with Python, FastAPI and DevSecOps
What if a banking API could do more than move money — what if it could also protect sensitive financial data from common API attacks?
SecureBank Open Banking API is a practical learning project that demonstrates how modern backend development, API security, automated testing, containers, cloud infrastructure, and DevSecOps can work together.
What Is the SecureBank Open Banking API?
SecureBank is a training-focused banking API designed to demonstrate secure application development practices. Users can authenticate, access accounts, view balances, and create transactions through REST API endpoints.
The project combines Python, FastAPI, OAuth2, JWT, Pydantic, SQLAlchemy, Docker, AWS, automated testing, security scanning, and CI/CD.
Technology Stack
- Python – Backend programming
- FastAPI – REST API framework
- OAuth2 + JWT – Authentication
- Pydantic – Input and data validation
- SQLAlchemy – Database access and ORM
- SQLite – Demo banking database
- Docker & Docker Compose – Containerization
- pytest – Automated testing
- Semgrep – Static security analysis
- Trivy – Vulnerability and container scanning
- OWASP ZAP – Dynamic application security testing
- Checkov – Infrastructure-as-Code security scanning
- GitHub Actions – CI/CD automation
- Terraform – Infrastructure as Code
- AWS API Gateway – Cloud API gateway extension
Authentication vs Authorization
One of the most important concepts demonstrated by SecureBank is the difference between authentication and authorization.
Authentication answers: “Who are you?”
Authorization answers: “What are you allowed to access?”
SecureBank uses an OAuth2-based authentication flow with JWT tokens. After authentication, authorization rules determine which accounts and resources a user can access.
Preventing BOLA Attacks
BOLA (Broken Object Level Authorization) is a major API security risk.
Imagine Alice owns account 1 and Bob owns account 2. If Alice changes an API request from:
/api/v1/accounts/1
to:
/api/v1/accounts/2
a vulnerable application might return Bob's information.
SecureBank demonstrates ownership validation so that users cannot access resources belonging to other users. Unauthorized access is rejected rather than simply trusting the object ID supplied by the client.
Input Validation with Pydantic
APIs should never blindly trust data received from clients. SecureBank uses Pydantic models to validate incoming requests.
For example, a transaction containing an invalid or negative amount should be rejected by the backend.
Database Security
Database security is another important part of API development. Unsafe dynamic SQL can expose applications to SQL injection attacks.
SecureBank demonstrates safer database access using SQLAlchemy filtering and parameterized queries. This helps developers understand the difference between unsafe database operations and secure data-access patterns.
Security Testing with OWASP ZAP
OWASP ZAP (Zed Attack Proxy) is used as part of the application's dynamic security testing approach. It can interact with a running application and help identify potential web and API security weaknesses.
This complements static analysis and automated application tests by testing the application from an external perspective.
DevSecOps Security Pipeline
Security checks are integrated into the development workflow using GitHub Actions.
- Semgrep – analyzes source code for security patterns
- Trivy – scans filesystems and container images
- OWASP ZAP – performs dynamic security testing
- Checkov – scans Terraform infrastructure
- pytest – executes automated application tests
- GitHub Actions – automates the overall workflow
Build → Test → Secure → Scan → Deploy → Improve
Docker and Cloud Deployment
The application can be run locally using Docker Compose. Developers can authenticate, call API endpoints, test authorization, and execute security scans in a repeatable environment.
An AWS extension demonstrates how API Gateway and Terraform can be incorporated into a cloud architecture.
This Is a Training Project — Not a Production Banking System
SecureBank is designed for learning and demonstration. Real production banking systems require significantly more controls, including comprehensive compliance, monitoring, secrets management, encryption, key management, fraud detection, resilience, operational controls, threat modeling, and extensive security reviews.
Who Should Study This Project?
- Python developers
- Backend engineers
- Cybersecurity students
- DevSecOps practitioners
- Cloud learners
- Software architects
- QA and automation engineers
- Graduates building technology portfolios
Instead of simply saying “I know Python”, a project like this can demonstrate practical experience in building, testing, securing, containerizing, scanning, and deploying an API.
The Concepts Go Beyond Banking
These security principles are not limited to financial applications. The same concepts apply to healthcare, e-commerce, SaaS, payments, government systems, enterprise applications, and other API-driven platforms.
If an application has users, it needs authentication and authorization. If it accepts input, it needs validation. If it communicates with a database, it needs secure queries. If it is deployed in containers or cloud infrastructure, security must extend to those layers as well.
Don't Just Learn. Build.
The best way to learn modern application security is to build projects and understand why each security control exists.
Clone projects. Run them. Test them. Break them in a controlled environment. Secure them. Scan them. Deploy them. Learn from the results.
Watch the Full SecureBank Project
Watch the complete walkthrough of the SecureBank Open Banking API:
Learn with EduArn.com
At EduArn.com, we focus on practical technology learning across AI, software architecture, application development, cloud, cybersecurity, DevSecOps, DevSecTestOps, and modern engineering practices.
Our approach is simple:
Learn. Build. Secure. Test. Deploy.