amazon-bedrock-agentcore-sa.../02-use-cases/SRE-agent/docs/security.md

# Security Considerations

## Overview

This document outlines security best practices and considerations for deploying and operating the SRE Multi-Agent System in production environments. Security is critical when handling infrastructure data and operational procedures.

## Security Best Practices

### Authentication and Authorization
- Implement API authentication using OAuth2 or API keys for infrastructure endpoints
- Use AWS IAM roles for Bedrock access instead of long-lived credentials
- Apply principle of least privilege for API access
- Implement role-based access control (RBAC) for different user types and permissions

### Encryption and Data Protection
- Enable TLS encryption for all API communications
- Encrypt sensitive data at rest and in transit
- Use secure secret management systems for credential storage
- Protect personally identifiable information (PII) and sensitive infrastructure details

### Operational Security
- Implement comprehensive audit logging for agent actions and investigations
- Regularly rotate API keys and tokens
- Monitor for unusual access patterns or suspicious activities
- Enable logging and monitoring for security events and anomalies

### Input Validation and Prompt Security
- Validate all user inputs to prevent prompt injection attacks
- Implement input sanitization for queries and commands
- Use Amazon Bedrock Guardrails to protect against malicious prompts
- Restrict agent capabilities based on user authorization levels

### Infrastructure Security
- Deploy the system in secure network environments with proper firewall rules
- Use VPC endpoints for AWS service communications when possible
- Implement network segmentation between different system components
- Regularly update dependencies and apply security patches

### Compliance and Governance
- Maintain audit trails for compliance requirements
- Implement data retention policies for logs and investigation records
- Ensure compliance with organizational security policies and standards
- Regular security assessments and penetration testing
fix(SRE Agent)- Deploy SRE Agent on Amazon Bedrock AgentCore Runtime with Enhanced Architecture (#158) * feat: Deploy SRE agent on Amazon Bedrock AgentCore Runtime - Add agent_runtime.py with FastAPI endpoints for AgentCore compatibility - Create Dockerfile for ARM64-based containerization - Add deployment scripts for automated ECR push and AgentCore deployment - Update backend API URLs from placeholders to actual endpoints - Update gateway configuration for production use - Add dependencies for AgentCore runtime support Implements #143 * chore: Add deployment artifacts to .gitignore - Add deployment/.sre_agent_uri, deployment/.env, and deployment/.agent_arn to .gitignore - Remove already tracked deployment artifacts from git * feat: Make ANTHROPIC_API_KEY optional in deployment - Update deploy_agent_runtime.py to conditionally include ANTHROPIC_API_KEY - Show info message when using Amazon Bedrock as provider - Update .env.example to clarify ANTHROPIC_API_KEY is optional - Only include ANTHROPIC_API_KEY in environment variables if it exists * fix: Use uv run python instead of python in build script - Update build_and_deploy.sh to use 'uv run python' for deployment - Change to parent directory to ensure uv environment is available - Fixes 'python: command not found' error during deployment * refactor: Improve deployment script structure and create .env symlink - Flatten nested if-else blocks in deploy_agent_runtime.py for better readability - Add 10-second sleep after deletion to ensure cleanup completes - Create symlink from deployment/.env to sre_agent/.env to avoid duplication - Move time import to top of file with other imports * feat: Add debug mode support and comprehensive deployment guide Add --debug command line flag and DEBUG environment variable support: - Created shared logging configuration module - Updated CLI and runtime to support --debug flag - Made debug traces conditional on DEBUG environment variable - Added debug mode for container and AgentCore deployments Enhanced build and deployment script: - Added command line argument for ECR repository name - Added help documentation and usage examples - Added support for local builds (x86_64) vs AgentCore builds (arm64) - Added environment variable pass-through for DEBUG, LLM_PROVIDER, ANTHROPIC_API_KEY Created comprehensive deployment guide: - Step-by-step instructions from local testing to production - Docker platform documentation (x86_64 vs arm64) - Environment variable configuration with .env file usage - Debug mode examples and troubleshooting guide - Provider configuration for Bedrock and Anthropic Updated README with AgentCore Runtime deployment section and documentation links. * docs: Update SRE Agent README with deployment flow diagram and fix directory reference - Fix reference from 04-SRE-agent to SRE-agent in README - Add comprehensive flowchart showing development to production deployment flow - Update overview to mention Amazon Bedrock AgentCore Runtime deployment - Remove emojis from documentation for professional appearance * docs: Replace mermaid diagram with ASCII step-by-step flow diagram - Change from block-style mermaid diagram to ASCII flow diagram - Show clear step-by-step progression from development to production - Improve readability with structured boxes and arrows - Minor text improvements for clarity * feat: Implement comprehensive prompt management system and enhance deployment guide - Create centralized prompt template system with external files in config/prompts/ - Add PromptLoader utility class with LRU caching and template variable substitution - Integrate PromptConfig into SREConstants for centralized configuration management - Update all agents (nodes, supervisor, output_formatter) to use prompt loader - Replace 150+ lines of hardcoded prompts with modular, maintainable template system - Enhance deployment guide with consistent naming (my_custom_sre_agent) throughout - Add quick-start copy-paste command sequence for streamlined deployment - Improve constants system with comprehensive model, AWS, timeout, and prompt configs - Add architectural assessment document to .gitignore for local analysis - Run black formatting across all updated Python files * docs: Consolidate deployment and security documentation - Rename deployment-and-security.md to security.md and remove redundant deployment content - Enhance security.md with comprehensive production security guidelines including: - Authentication and authorization best practices - Encryption and data protection requirements - Operational security monitoring and logging - Input validation and prompt security measures - Infrastructure security recommendations - Compliance and governance frameworks - Update README.md to reference new security.md file - Eliminate redundancy between deployment-guide.md and deployment-and-security.md - Improve documentation organization with clear separation of concerns * config: Replace hardcoded endpoints with placeholder domains - Update OpenAPI specifications to use placeholder domain 'your-backend-domain.com' - k8s_api.yaml: mcpgateway.ddns.net:8011 -> your-backend-domain.com:8011 - logs_api.yaml: mcpgateway.ddns.net:8012 -> your-backend-domain.com:8012 - metrics_api.yaml: mcpgateway.ddns.net:8013 -> your-backend-domain.com:8013 - runbooks_api.yaml: mcpgateway.ddns.net:8014 -> your-backend-domain.com:8014 - Update agent configuration to use placeholder AgentCore gateway endpoint - agent_config.yaml: Replace specific gateway ID with 'your-agentcore-gateway-endpoint' - Improve security by removing hardcoded production endpoints from repository - Enable template-based configuration that users can customize during setup - Align with existing documentation patterns for placeholder domain replacement 2025-07-27 15:05:03 -04:00			`# Security Considerations`

			`## Overview`

			`This document outlines security best practices and considerations for deploying and operating the SRE Multi-Agent System in production environments. Security is critical when handling infrastructure data and operational procedures.`

			`## Security Best Practices`

			`### Authentication and Authorization`
			`- Implement API authentication using OAuth2 or API keys for infrastructure endpoints`
			`- Use AWS IAM roles for Bedrock access instead of long-lived credentials`
			`- Apply principle of least privilege for API access`
			`- Implement role-based access control (RBAC) for different user types and permissions`

			`### Encryption and Data Protection`
			`- Enable TLS encryption for all API communications`
			`- Encrypt sensitive data at rest and in transit`
			`- Use secure secret management systems for credential storage`
			`- Protect personally identifiable information (PII) and sensitive infrastructure details`

			`### Operational Security`
			`- Implement comprehensive audit logging for agent actions and investigations`
			`- Regularly rotate API keys and tokens`
			`- Monitor for unusual access patterns or suspicious activities`
			`- Enable logging and monitoring for security events and anomalies`

			`### Input Validation and Prompt Security`
			`- Validate all user inputs to prevent prompt injection attacks`
			`- Implement input sanitization for queries and commands`
			`- Use Amazon Bedrock Guardrails to protect against malicious prompts`
			`- Restrict agent capabilities based on user authorization levels`

			`### Infrastructure Security`
			`- Deploy the system in secure network environments with proper firewall rules`
			`- Use VPC endpoints for AWS service communications when possible`
			`- Implement network segmentation between different system components`
			`- Regularly update dependencies and apply security patches`

			`### Compliance and Governance`
			`- Maintain audit trails for compliance requirements`
			`- Implement data retention policies for logs and investigation records`
			`- Ensure compliance with organizational security policies and standards`
			`- Regular security assessments and penetration testing`