AWS Bedrock Security Guide
AWS Bedrock provides a fully managed service for building and scaling generative AI applications using foundation models. As organizations deploy production AI workloads on Bedrock, implementing comprehensive security controls becomes critical for protecting sensitive data, ensuring compliance, and preventing unauthorized access to AI capabilities.
This guide covers security best practices for AWS Bedrock deployments, including identity and access management (IAM), data protection, network security, monitoring and logging, compliance considerations, and operational security. Whether you're deploying Claude, Llama, Titan, or other foundation models through Bedrock, these security controls help protect your AI applications from threats while maintaining compliance with regulatory requirements.
AWS Bedrock integrates with AWS's comprehensive security infrastructure, providing enterprise-grade protection through features like AWS KMS for encryption, VPC endpoints for network isolation, CloudTrail for audit logging, and IAM for fine-grained access control. Understanding how to properly configure these security features and implement defense-in-depth strategies is essential for maintaining a robust security posture for your Bedrock deployments.
Key Security Features
Implement fine-grained access controls for Bedrock models and APIs using AWS Identity and Access Management (IAM). Control who can invoke specific foundation models, configure guardrails, and access Bedrock features.
- IAM Policies: Create custom policies to control model invocation permissions, guardrail configuration, and knowledge base access
- Resource-Based Policies: Attach policies directly to Bedrock resources for service-level access control
- Cross-Account Access: Securely share Bedrock resources across AWS accounts using IAM roles and resource policies
- Service Control Policies: Use AWS Organizations SCPs to enforce organization-wide Bedrock usage policies
- API Throttling: Configure rate limits and quotas to prevent abuse and control costs
Track and audit all Bedrock API calls, model invocations, and administrative actions using AWS CloudTrail, CloudWatch, and Bedrock's native logging capabilities.
- CloudTrail Integration: Comprehensive audit logging of all Bedrock API calls with detailed request/response metadata
- Model Invocation Logging: Enable logging for model inputs and outputs for debugging and compliance
- CloudWatch Metrics: Monitor API usage, latency, errors, and token consumption in real-time
- Anomaly Detection: Set up CloudWatch alarms for unusual usage patterns or security events
- Guardrail Violations: Log all content filter violations and policy breaches for security analysis
Data Protection & Privacy
AWS Bedrock provides multiple layers of data protection to ensure your prompts, model outputs, and training data remain secure and compliant with regulatory requirements. The service is designed with privacy-by-default principles, ensuring that your data is not used to train foundation models.
Encryption
- Encryption at Rest: All data stored in Bedrock is encrypted using AWS KMS with customer-managed keys (CMK) or AWS-managed keys
- Encryption in Transit: All API communications use TLS 1.2+ with perfect forward secrecy
- KMS Integration: Use AWS Key Management Service for centralized key management and rotation
- Knowledge Base Encryption: Vector embeddings and source data encrypted with customer-managed keys
Data Residency & Isolation
- Regional Deployment: Control where your data is processed with regional Bedrock availability
- Data Isolation: Your prompts and completions are never used to train foundation models
- VPC Endpoints: Access Bedrock privately from your VPC without internet exposure
- Dedicated Capacity: Provisioned throughput for isolated, dedicated model access
Compliance Certifications
AWS Bedrock inherits AWS's comprehensive compliance certifications, making it suitable for regulated industries:
Industry Standards
- • SOC 1, 2, 3
- • ISO 27001, 27017, 27018
- • PCI DSS Level 1
Regional Compliance
- • GDPR (EU)
- • HIPAA BAA available
- • FedRAMP (US Government)
Industry-Specific
- • HITRUST (Healthcare)
- • FINRA (Financial)
- • FERPA (Education)
Network Security
Secure your Bedrock API calls by deploying them within your Amazon Virtual Private Cloud (VPC) using VPC endpoints. This ensures that traffic between your applications and Bedrock never traverses the public internet, reducing exposure to network-based attacks.
VPC Endpoint Configuration
- Interface Endpoints: Create VPC endpoints for Bedrock API access within your private subnets, ensuring all traffic stays within AWS network
- Security Groups: Configure security group rules to restrict Bedrock endpoint access to specific source IPs or security groups
- Private Subnets: Deploy applications in private subnets without internet gateways for maximum isolation
- VPC Peering: Connect multiple VPCs securely to share Bedrock access across accounts or regions
- Transit Gateway: Centralize Bedrock access management across multiple VPCs and on-premises networks
Guardrails & Content Safety
AWS Bedrock Guardrails provide configurable content filters and safety controls to prevent harmful, inappropriate, or sensitive content from being generated or processed. These guardrails work alongside foundation model safety features to provide defense-in-depth content protection.
Content Filtering
- • Hate speech and harassment detection
- • Sexual content filtering
- • Violence and self-harm prevention
- • Misinformation and disinformation detection
- • Custom word filters and content policies
PII & Sensitive Data
- • PII detection and redaction
- • Sensitive information filtering
- • Custom sensitive data patterns
- • Compliance-aware content filtering
- • Audit logging of filtered content
Best Practice: Configure guardrails with appropriate severity levels for your use case. Test guardrail configurations thoroughly to balance content safety with application functionality. Monitor guardrail violation logs to identify potential security issues or false positives.
Security Best Practices
Use AWS KMS customer-managed keys (CMK) for encryption. Rotate keys regularly, implement key policies with least privilege, and enable CloudTrail logging for all KMS operations.
- • Enable automatic key rotation
- • Use separate keys per environment
- • Implement key access policies
- • Monitor key usage metrics
Follow the principle of least privilege. Grant only necessary permissions, use IAM roles instead of access keys, and regularly audit access permissions.
- • Use IAM roles for applications
- • Implement resource-level permissions
- • Enable MFA for admin access
- • Regular access reviews
Enable comprehensive logging, set up CloudWatch alarms for anomalies, and implement automated responses to security events.
- • Enable CloudTrail for all regions
- • Set up cost anomaly detection
- • Monitor API usage patterns
- • Alert on guardrail violations
Cost Control & Abuse Prevention
Implement controls to prevent unauthorized usage and unexpected costs from Bedrock API calls. Configure budgets, quotas, and monitoring to detect and prevent abuse.
Budget Controls
- • Set AWS Budgets with alerts
- • Configure cost anomaly detection
- • Implement spending limits per project
- • Use Cost Allocation Tags
Rate Limiting
- • Configure API throttling policies
- • Set token consumption limits
- • Implement request quotas
- • Monitor usage per IAM principal
Related Resources
Frequently Asked Questions
AWS Bedrock provides comprehensive security features including IAM-based access control, AWS KMS encryption for data at rest and in transit, VPC endpoints for network isolation, CloudTrail for audit logging, and guardrails for content safety and filtering.
Access to Bedrock models is controlled through AWS IAM policies. You can create fine-grained policies that specify which models can be accessed, by which users/roles, from which networks, and with what rate limits. Use IAM conditions for additional restrictions.
Yes, AWS Bedrock encrypts data in transit using TLS 1.2+ and supports encryption at rest using AWS KMS. You can use customer-managed KMS keys for additional control over encryption keys and compliance requirements.
AWS CloudTrail logs all Bedrock API calls including model invocations, configuration changes, and access attempts. CloudWatch provides metrics and alarms. You can also enable VPC Flow Logs for network-level monitoring.
Bedrock Guardrails provide content safety controls that filter harmful content, block inappropriate prompts and responses, and enforce content policies. They use configurable filters for topics, words, and content categories to protect your applications.
Yes, you can use AWS PrivateLink to create VPC endpoints for Bedrock, allowing you to access Bedrock services from your VPC without traversing the public internet. This provides network isolation and reduces exposure to internet-based threats.
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