🚔Cloud Security Baseline for Azure OpenAI

Minimum Security Baseline for Azure OpenAI

1. Identity and Access Management (IAM)

• Use Azure Active Directory (AAD) Integration

  • Action: Integrate Azure OpenAI with Azure Active Directory (AAD) for centralized identity management.

  • Recommendation: Ensure all users authenticate through AAD and enable single sign-on (SSO) for seamless and secure access.

• Implement Role-Based Access Control (RBAC)

  • Action: Define and assign roles based on the principle of least privilege.

  • Recommendation: Regularly review and update role assignments. Use built-in roles to manage permissions effectively.

• Enable Multi-Factor Authentication (MFA)

  • Action: Require MFA for all users accessing Azure OpenAI resources.

  • Recommendation: Enforce MFA through AAD policies to protect against credential theft and unauthorized access.

2. Data Security

• Encrypt Data at Rest and in Transit

  • Action: Use Azure-managed encryption keys or customer-managed keys to encrypt data.

  • Recommendation: Ensure all data stored and transmitted is encrypted using industry-standard encryption algorithms.

• Implement Data Masking and Anonymization

  • Action: Apply data masking techniques to protect sensitive data used in training or inference processes.

  • Recommendation: Use Azure Data Masking features to anonymize sensitive information.

• Use Secure Data Storage Solutions

  • Action: Store data in secure, compliant storage services like Azure Blob Storage with appropriate access controls.

  • Recommendation: Implement access policies and regularly review access permissions to data storage resources.

3. API Security

• Use API Management Solutions

  • Action: Implement Azure API Management to secure, monitor, and manage access to APIs.

  • Recommendation: Apply rate limiting, throttling, and access controls to API endpoints.

• Enable API Key Management

  • Action: Use API keys or tokens to authenticate and authorize API requests.

  • Recommendation: Rotate API keys regularly and use secure storage for API keys.

• Implement Rate Limiting and Throttling

  • Action: Protect APIs from abuse by enforcing rate limits and throttling.

  • Recommendation: Configure appropriate rate limits to prevent denial-of-service attacks.

4. Model Security

• Secure Model Training and Deployment Environments

  • Action: Ensure that environments where models are trained and deployed are secure and isolated.

  • Recommendation: Use virtual networks and private endpoints to restrict access to model training and deployment environments.

• Implement Model Versioning and Monitoring

  • Action: Track and monitor model versions and their usage to detect anomalies and unauthorized modifications.

  • Recommendation: Use Azure Machine Learning for model management and versioning.

• Use Secure Model APIs

  • Action: Ensure that model inference APIs are secured with appropriate authentication and authorization mechanisms.

  • Recommendation: Apply API security best practices and monitor API usage for anomalies.

5. Logging and Monitoring

• Enable Auditing

  • Action: Track user activities, changes to configurations, and access attempts.

  • Recommendation: Enable Azure OpenAI auditing to monitor and review activities for security and compliance.

• Integrate with Monitoring Tools

  • Action: Use Azure Monitor, Log Analytics, and Security Center to collect and analyze logs from Azure OpenAI.

  • Recommendation: Set up alerts for suspicious activities and potential security incidents.

6. Compliance and Governance

• Implement Azure Policy and Blueprints

  • Action: Enforce compliance with organizational and regulatory requirements.

  • Recommendation: Use Azure Policy and Blueprints to govern Azure resources and ensure they adhere to security standards.

• Regular Security Assessments

  • Action: Conduct regular security assessments and audits to identify and remediate vulnerabilities.

  • Recommendation: Use tools like Microsoft Defender for Cloud to perform security assessments and receive actionable recommendations.

7. Endpoint Security

• Secure Development Workstations

  • Action: Ensure that all workstations used for accessing Azure OpenAI are secured with antivirus and endpoint protection solutions.

  • Recommendation: Keep all development workstations up-to-date with the latest security patches and updates.

• Use Secure Network Practices

  • Action: Ensure that network access to Azure OpenAI is secure.

  • Recommendation: Use VPNs and firewalls to protect network traffic and restrict access based on IP address ranges.

8. Backup and Recovery

• Regular Backups

  • Action: Regularly back up Azure OpenAI configurations and critical data.

  • Recommendation: Use built-in backup options or third-party tools to ensure data can be restored in case of accidental deletion or data loss.

• Disaster Recovery Plan

  • Action: Develop and test a disaster recovery plan for Azure OpenAI.

  • Recommendation: Ensure that the plan includes steps for restoring configurations and data from backups.