Cloud Security Lab with Terraform and Python

Build, Secure, and Automate Cloud Environments

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Overview

This project simulates a real-world cloud security environment where you will deploy a multi-account AWS architecture with Terraform and automate compliance, monitoring, and remediation using Python. The lab combines Infrastructure as Code (IaC) with security automation and a real-time monitoring dashboard to enhance your skills in cloud security engineering.

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Features

• Deploy secure AWS environments with Terraform.
• Enable centralized logging with S3 and CloudTrail for compliance tracking.
• Integrate AWS native tools like GuardDuty and Security Hub for threat detection and monitoring.
• Automate S3 bucket compliance checks and incident response workflows using Python scripts.
• Visualize real-time security insights with a Flask-based web dashboard.

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Scenarios

1. S3 Bucket Security Violation

Violation: Create a public, unencrypted S3 bucket.

Remediation: Use the Python compliance checker to automatically detect and remediate the issue by revoking public access and enabling server-side encryption.

2. EC2 Instance Compromise

Violation: Simulate a compromised EC2 instance flagged by GuardDuty.

Remediation: Trigger a Lambda function to isolate the instance by moving it to a quarantine Security Group.

3. IAM Role Violation

Violation: Create an overly permissive IAM role with Administrator Access.

Remediation: Use Security Hub to detect the violation and detach the policy manually or programmatically.

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Outcomes

• Gain hands-on experience with cloud security best practices.
• Master Infrastructure as Code (IaC) with Terraform for repeatable deployments.
• Develop Python scripts for automated compliance and threat detection.
• Build a real-time security dashboard to monitor your AWS environment.
• Learn how to simulate and remediate security violations in a controlled environment.

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How to Use This Project

1. Deploy Infrastructure: Use Terraform to deploy the AWS environment with secure VPC, S3 logging, GuardDuty, and Security Hub.
2. Run Python Automation: Execute scripts to enforce compliance and analyze findings.
3. Simulate Violations: Create intentional security violations to test detection and remediation.
4. Visualize Insights: Access the Flask dashboard for a centralized view of compliance and threats.

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Prerequisites

• Terraform and AWS CLI installed on your machine.
• An AWS account with administrative privileges.
• Basic knowledge of Python and cloud security concepts.

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Technologies Used

• AWS Services: VPC, S3, GuardDuty, Security Hub, CloudTrail, Lambda
• Terraform: For Infrastructure as Code (IaC).
• Python: For automation and monitoring.
• Flask: For building the security dashboard.

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License

This project is licensed under the MIT License. Feel free to use and modify it for personal or professional use.