Advanced AWS Assume Role Patterns & Enterprise Security Best Practices

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Overview

AWS Assume Role is a fundamental security feature that enables temporary, controlled access to AWS resources across accounts or within the same account.

This comprehensive guide covers advanced patterns, automation strategies, and enterprise-grade security implementations for production environments.

What is AWS Assume Role?

AWS Assume Role is a function provided by AWS Security Token Service (STS) that allows one IAM entity (user or service) to temporarily adopt another role in AWS and use the permissions associated with that role.

This mechanism enhances security and simplifies access management by granting only the necessary permissions for the duration required to complete specific tasks.


The sts:AssumeRole operation enables a secure delegation model where:

Advanced Use Cases


How AWS Assume Role Works

Assume Role Process Flow

  1. Trust relationship: The target role specifies which entities (principals) can assume it
  2. Permission check: The assuming entity must have permission to call the sts:AssumeRole action
  3. STS call: The entity calls the AssumeRole API with the role ARN and optional parameters
  4. Temporary credentials: STS returns temporary security credentials (access key, secret key, session token)
  5. Using credentials: Applications use these credentials to make AWS API calls with the role’s permissions


Enterprise-Grade Role Architecture Patterns

1. Hub-and-Spoke Model

Central Security Account (Hub)
├── Identity Management
├── Audit & Compliance
├── Emergency Access Roles
└── Cross-Account Trust Relationships

Spoke Accounts
├── Production Account
├── Development Account
├── Testing Account
└── Shared Services Account

Implementation Strategy:

2. Layered Security Model

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "AssumeRoleWithMFA",
      "Effect": "Allow",
      "Principal": {
        "AWS": "arn:aws:iam::CENTRAL-ACCOUNT:root"
      },
      "Action": "sts:AssumeRole",
      "Condition": {
        "Bool": {
          "aws:MultiFactorAuthPresent": "true"
        },
        "NumericLessThan": {
          "aws:MultiFactorAuthAge": "3600"
        },
        "StringEquals": {
          "aws:PrincipalTag/Department": ["DevOps", "Security"],
          "aws:RequestedRegion": ["us-west-2", "us-east-1"]
        },
        "IpAddress": {
          "aws:SourceIp": ["203.0.113.0/24", "198.51.100.0/24"]
        },
        "StringLike": {
          "aws:userid": "AIDAI*:${aws:username}"
        }
      }
    }
  ]
}

3. Just-In-Time (JIT) Access Pattern

Automated Approval Workflow:

import boto3
import json
from datetime import datetime, timedelta

class JITAccessManager:
    def __init__(self):
        self.sts = boto3.client('sts')
        self.iam = boto3.client('iam')
        self.sns = boto3.client('sns')
        
    def request_elevated_access(self, requestor, role_arn, duration_hours, justification):
        """Request temporary elevated access with approval workflow"""
        
        # Create temporary policy for specific duration
        temp_policy = {
            "Version": "2012-10-17",
            "Statement": [
                {
                    "Effect": "Allow",
                    "Principal": {"AWS": f"arn:aws:iam::{self.get_account_id()}:user/{requestor}"},
                    "Action": "sts:AssumeRole",
                    "Resource": role_arn,
                    "Condition": {
                        "DateLessThan": {
                            "aws:CurrentTime": (datetime.utcnow() + timedelta(hours=duration_hours)).isoformat()
                        }
                    }
                }
            ]
        }
        
        # Send approval request
        approval_request = {
            "requestor": requestor,
            "role_arn": role_arn,
            "duration": duration_hours,
            "justification": justification,
            "timestamp": datetime.utcnow().isoformat(),
            "policy": temp_policy
        }
        
        self.sns.publish(
            TopicArn='arn:aws:sns:region:account:jit-access-requests',
            Message=json.dumps(approval_request),
            Subject=f'JIT Access Request: {requestor} -> {role_arn}'
        )
        
        return approval_request
    
    def approve_access_request(self, request_id, approver):
        """Approve and implement temporary access"""
        # Implementation for approval workflow
        pass

Advanced Automation with Infrastructure as Code

Terraform Module for Cross-Account Roles

# modules/cross-account-role/main.tf
variable "account_id" {
  description = "Account ID that can assume this role"
  type        = string
}

variable "role_name" {
  description = "Name of the role to create"
  type        = string
}

variable "policies" {
  description = "List of policy ARNs to attach"
  type        = list(string)
  default     = []
}

variable "max_session_duration" {
  description = "Maximum session duration in seconds"
  type        = number
  default     = 3600
}

variable "require_mfa" {
  description = "Require MFA for role assumption"
  type        = bool
  default     = true
}

variable "allowed_principals" {
  description = "List of principals allowed to assume this role"
  type        = list(string)
}

data "aws_iam_policy_document" "trust_policy" {
  statement {
    effect = "Allow"
    
    principals {
      type        = "AWS"
      identifiers = var.allowed_principals
    }
    
    actions = ["sts:AssumeRole"]
    
    dynamic "condition" {
      for_each = var.require_mfa ? [1] : []
      content {
        test     = "Bool"
        variable = "aws:MultiFactorAuthPresent"
        values   = ["true"]
      }
    }
    
    condition {
      test     = "StringEquals"
      variable = "aws:RequestedRegion"
      values   = ["us-west-2", "us-east-1"]
    }
  }
}

resource "aws_iam_role" "cross_account_role" {
  name                 = var.role_name
  assume_role_policy   = data.aws_iam_policy_document.trust_policy.json
  max_session_duration = var.max_session_duration
  
  tags = {
    ManagedBy   = "terraform"
    Purpose     = "cross-account-access"
    Environment = terraform.workspace
  }
}

resource "aws_iam_role_policy_attachment" "policies" {
  count      = length(var.policies)
  role       = aws_iam_role.cross_account_role.name
  policy_arn = var.policies[count.index]
}

# CloudTrail for auditing
resource "aws_cloudtrail" "role_audit" {
  name           = "${var.role_name}-audit-trail"
  s3_bucket_name = aws_s3_bucket.audit_logs.bucket
  
  event_selector {
    read_write_type           = "All"
    include_management_events = true
    
    data_resource {
      type   = "AWS::S3::Object"
      values = ["arn:aws:s3:::${aws_s3_bucket.audit_logs.bucket}/*"]
    }
  }
  
  insight_selector {
    insight_type = "ApiCallRateInsight"
  }
}

output "role_arn" {
  description = "ARN of the created role"
  value       = aws_iam_role.cross_account_role.arn
}

AWS CLI Wrapper Script for Enhanced Security


Advanced Monitoring and Alerting

CloudWatch Dashboards for Role Usage


Advanced EventBridge Rules for Security Alerts

import boto3
import json

def create_security_monitoring():
    events = boto3.client('events')
    sns = boto3.client('sns')
    
    # Rule for suspicious role assumptions
    suspicious_pattern = {
        "source": ["aws.sts"],
        "detail-type": ["AWS API Call via CloudTrail"],
        "detail": {
            "eventSource": ["sts.amazonaws.com"],
            "eventName": ["AssumeRole"],
            "errorCode": {"exists": False},
            "sourceIPAddress": {
                "anything-but": {
                    "prefix": ["10.", "172.16.", "192.168."]
                }
            }
        }
    }
    
    events.put_rule(
        Name='SuspiciousRoleAssumption',
        EventPattern=json.dumps(suspicious_pattern),
        State='ENABLED',
        Description='Alert on role assumptions from external IPs'
    )
    
    # Rule for failed role assumptions
    failure_pattern = {
        "source": ["aws.sts"],
        "detail-type": ["AWS API Call via CloudTrail"],
        "detail": {
            "eventSource": ["sts.amazonaws.com"],
            "eventName": ["AssumeRole"],
            "errorCode": {"exists": True}
        }
    }
    
    events.put_rule(
        Name='FailedRoleAssumption',
        EventPattern=json.dumps(failure_pattern),
        State='ENABLED',
        Description='Alert on failed role assumption attempts'
    )

def lambda_security_handler(event, context):
    """Lambda function to process security events and send alerts"""
    
    detail = event['detail']
    event_name = detail.get('eventName')
    source_ip = detail.get('sourceIPAddress')
    user_identity = detail.get('userIdentity', {})
    
    # Analyze the event
    risk_score = calculate_risk_score(detail)
    
    if risk_score > 70:  # High risk threshold
        send_security_alert(detail, risk_score)
        
        # Optionally, automatically revoke the session
        if risk_score > 90:
            revoke_active_sessions(user_identity)
    
    return {'statusCode': 200}

def calculate_risk_score(detail):
    """Calculate risk score based on various factors"""
    score = 0
    
    # Check source IP reputation
    if is_suspicious_ip(detail.get('sourceIPAddress')):
        score += 30
    
    # Check time of access
    if is_unusual_time(detail.get('eventTime')):
        score += 20
    
    # Check role sensitivity
    role_arn = detail.get('requestParameters', {}).get('roleArn', '')
    if 'Admin' in role_arn or 'Root' in role_arn:
        score += 25
    
    # Check user behavior anomaly
    if is_anomalous_behavior(detail):
        score += 25
    
    return score

Detailed Example: Cross-Account EKS Access with Enhanced Security

The following example demonstrates how to use AssumeRole to grant Account A access to EKS resources in Account B with production-grade security controls.

Step 1: Create Advanced IAM Role in Account B (Target Account)

Create an IAM role with comprehensive security controls and conditions.


Enhanced Trust Policy with Multiple Security Layers:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "CrossAccountAssumeRole",
      "Effect": "Allow",
      "Principal": {
        "AWS": [
          "arn:aws:iam::123456789012:role/DevOpsTeamRole",
          "arn:aws:iam::123456789012:role/SecurityTeamRole"
        ]
      },
      "Action": "sts:AssumeRole",
      "Condition": {
        "Bool": {
          "aws:MultiFactorAuthPresent": "true"
        },
        "NumericLessThan": {
          "aws:MultiFactorAuthAge": "1800"
        },
        "StringEquals": {
          "aws:PrincipalTag/Department": ["DevOps", "Security"],
          "aws:RequestedRegion": ["us-west-2", "us-east-1"],
          "sts:ExternalId": "unique-external-id-2024"
        },
        "IpAddress": {
          "aws:SourceIp": [
            "203.0.113.0/24",
            "198.51.100.0/24"
          ]
        },
        "DateGreaterThan": {
          "aws:CurrentTime": "2024-01-01T00:00:00Z"
        },
        "DateLessThan": {
          "aws:CurrentTime": "2025-12-31T23:59:59Z"
        }
      }
    },
    {
      "Sid": "EmergencyAccess",
      "Effect": "Allow",
      "Principal": {
        "AWS": "arn:aws:iam::123456789012:role/BreakGlassRole"
      },
      "Action": "sts:AssumeRole",
      "Condition": {
        "Bool": {
          "aws:MultiFactorAuthPresent": "true"
        },
        "StringEquals": {
          "aws:PrincipalTag/EmergencyAccess": "true"
        }
      }
    }
  ]
}


Granular Permission Policy with Resource-Level Controls:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "EKSClusterManagement",
      "Effect": "Allow",
      "Action": [
        "eks:DescribeCluster",
        "eks:ListClusters",
        "eks:DescribeNodegroup",
        "eks:ListNodegroups",
        "eks:DescribeUpdate",
        "eks:ListUpdates"
      ],
      "Resource": [
        "arn:aws:eks:*:111122223333:cluster/prod-*",
        "arn:aws:eks:*:111122223333:cluster/staging-*"
      ],
      "Condition": {
        "StringEquals": {
          "aws:RequestedRegion": ["us-west-2", "us-east-1"]
        }
      }
    },
    {
      "Sid": "EKSConfigurationUpdates",
      "Effect": "Allow",
      "Action": [
        "eks:UpdateClusterConfig",
        "eks:UpdateClusterVersion",
        "eks:UpdateNodegroupConfig",
        "eks:UpdateNodegroupVersion"
      ],
      "Resource": [
        "arn:aws:eks:*:111122223333:cluster/staging-*",
        "arn:aws:eks:*:111122223333:nodegroup/staging-*/*/*"
      ],
      "Condition": {
        "StringEquals": {
          "aws:RequestedRegion": ["us-west-2"],
          "aws:PrincipalTag/Role": "DevOps"
        },
        "Bool": {
          "aws:MultiFactorAuthPresent": "true"
        }
      }
    },
    {
      "Sid": "ProductionReadOnly",
      "Effect": "Allow",
      "Action": [
        "eks:DescribeCluster",
        "eks:ListClusters",
        "eks:DescribeNodegroup",
        "eks:ListNodegroups"
      ],
      "Resource": [
        "arn:aws:eks:*:111122223333:cluster/prod-*"
      ],
      "Condition": {
        "StringEquals": {
          "aws:PrincipalTag/ProductionAccess": "read-only"
        }
      }
    },
    {
      "Sid": "CloudWatchLogs",
      "Effect": "Allow",
      "Action": [
        "logs:DescribeLogGroups",
        "logs:DescribeLogStreams",
        "logs:GetLogEvents",
        "logs:FilterLogEvents"
      ],
      "Resource": [
        "arn:aws:logs:*:111122223333:log-group:/aws/eks/*"
      ]
    }
  ]
}


Permission Boundary for Additional Security:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "PermissionBoundary",
      "Effect": "Allow",
      "Action": [
        "eks:*",
        "ec2:DescribeInstances",
        "ec2:DescribeSecurityGroups",
        "ec2:DescribeSubnets",
        "ec2:DescribeVpcs",
        "iam:ListRoles",
        "iam:PassRole",
        "logs:*"
      ],
      "Resource": "*",
      "Condition": {
        "StringEquals": {
          "aws:RequestedRegion": ["us-west-2", "us-east-1"]
        }
      }
    },
    {
      "Sid": "DenyDangerousActions",
      "Effect": "Deny",
      "Action": [
        "eks:DeleteCluster",
        "eks:DeleteNodegroup",
        "iam:DeleteRole",
        "iam:DeletePolicy",
        "iam:DetachRolePolicy"
      ],
      "Resource": "*",
      "Condition": {
        "StringNotEquals": {
          "aws:PrincipalTag/CanDelete": "true"
        }
      }
    }
  ]
}


Step 2: Create IAM Policy in Account A (Source Account)

Create and attach an IAM policy to the users or roles in Account A that need to assume the role in Account B.


Example Policy (in Account A):

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": "sts:AssumeRole",
      "Resource": "arn:aws:iam::111122223333:role/EKSAdminRole",
      "Condition": {
        "StringLike": {
          "aws:RequestedRegion": [
            "us-west-2",
            "us-east-1"
          ]
        }
      }
    }
  ]
}


Step 3: Assume Role from Account A

A user or service in Account A can now assume the role in Account B using the AWS CLI, SDK, or AWS console.


Using AWS CLI:



This command returns a JSON object containing:


Using AWS SDK (Python example):

import boto3

# Create an STS client
sts_client = boto3.client('sts')

# Assume the role
assumed_role = sts_client.assume_role(
    RoleArn='arn:aws:iam::111122223333:role/EKSAdminRole',
    RoleSessionName='EKSAdminSession',
    DurationSeconds=3600  # 1 hour
)

# Extract the temporary credentials
credentials = assumed_role['Credentials']

# Create an EKS client using the temporary credentials
eks_client = boto3.client(
    'eks',
    region_name='us-west-2',
    aws_access_key_id=credentials['AccessKeyId'],
    aws_secret_access_key=credentials['SecretAccessKey'],
    aws_session_token=credentials['SessionToken']
)

# Now you can make EKS API calls
clusters = eks_client.list_clusters()
print(clusters)


Step 4: Use Temporary Credentials for Access

These temporary credentials can be used to access EKS resources in Account B. Here’s an example of updating your kubeconfig:



You can also create a shell profile that automatically assumes the role:

# Add to your ~/.bash_profile or ~/.zshrc
function assume-eks-role() {
  output=$(aws sts assume-role --role-arn arn:aws:iam::111122223333:role/EKSAdminRole --role-session-name EKSSession)
  export AWS_ACCESS_KEY_ID=$(echo $output | jq -r '.Credentials.AccessKeyId')
  export AWS_SECRET_ACCESS_KEY=$(echo $output | jq -r '.Credentials.SecretAccessKey')
  export AWS_SESSION_TOKEN=$(echo $output | jq -r '.Credentials.SessionToken')
  echo "Temporary credentials set for EKS admin role"
}



What is sts:AssumeRoleWithWebIdentity?

The sts:AssumeRoleWithWebIdentity operation allows you to obtain temporary AWS credentials by using an OpenID Connect (OIDC) token or SAML 2.0 assertion from an external identity provider.

This mechanism enables federating AWS access with external identity systems without requiring AWS IAM users for each identity.

Key Benefits

Common Use Cases

Process Flow

  1. OIDC Provider Configuration: Register an OIDC provider in IAM and create a role with a trust policy
  2. Identity Authentication: User/service authenticates with the external IdP and receives an OIDC token
  3. AWS API Call: Application calls AssumeRoleWithWebIdentity API with the OIDC token
  4. Token Verification: AWS verifies the token with the configured OIDC provider
  5. Temporary Credentials: Upon successful verification, AWS issues temporary credentials

Example: GitHub Actions Integration


IAM OIDC Provider Configuration:

aws iam create-open-id-connect-provider --url https://token.actions.githubusercontent.com --client-id-list sts.amazonaws.com --thumbprint-list 6938fd4d98bab03faadb97b34396831e3780aea1


Role Trust Policy:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "Federated": "arn:aws:iam::ACCOUNT_ID:oidc-provider/token.actions.githubusercontent.com"
      },
      "Action": "sts:AssumeRoleWithWebIdentity",
      "Condition": {
        "StringEquals": {
          "token.actions.githubusercontent.com:aud": "sts.amazonaws.com",
          "token.actions.githubusercontent.com:sub": "repo:your-org/your-repo:ref:refs/heads/main"
        }
      }
    }
  ]
}


GitHub Actions Workflow:

jobs:
  deploy:
    runs-on: ubuntu-latest
    permissions:
      id-token: write
      contents: read
    steps:
      - name: Configure AWS credentials
        uses: aws-actions/configure-aws-credentials@v1
        with:
          role-to-assume: arn:aws:iam::ACCOUNT_ID:role/GitHubActionsRole
          aws-region: us-east-1
      
      - name: Deploy infrastructure
        run: aws cloudformation deploy --template-file template.yaml --stack-name my-stack


Comparison: AssumeRole vs AssumeRoleWithWebIdentity vs AssumeRoleWithSAML

Authentication:

Identity Source:

Primary Use Cases:

Required Setup:

Credential Duration:

Common Examples:


Advanced Best Practices for Enterprise AWS Assume Role


1. Security Architecture:
  • Implement defense-in-depth with multiple conditional layers
  • Use permission boundaries to limit maximum permissions
  • Enforce MFA with time-based conditions (MFA age < 30 minutes)
  • Implement IP allowlisting and geographic restrictions
  • Use external IDs for third-party access to prevent confused deputy attacks
  • Implement role chaining limits and session duration policies
2. Automation and Operations:
  • Use Infrastructure as Code (Terraform/CloudFormation) for consistent role deployment
  • Implement automated role lifecycle management
  • Create self-service portals for role requests with approval workflows
  • Establish break-glass procedures with proper audit trails
  • Implement just-in-time (JIT) access with time-bound permissions
  • Use AWS Config rules to monitor role configuration drift
3. Monitoring and Compliance:
  • Enable comprehensive CloudTrail logging with log file validation
  • Implement real-time alerting for suspicious role assumption patterns
  • Use AWS GuardDuty for behavioral analysis and threat detection
  • Create custom CloudWatch metrics for role usage analytics
  • Implement automated compliance checks with AWS Security Hub
  • Use IAM Access Analyzer for unused and over-privileged role detection
4. Governance and Risk Management:
  • Establish role naming conventions and tagging strategies
  • Implement regular access reviews and role audits
  • Use AWS Organizations SCPs as guardrails
  • Create role templates for common use cases
  • Implement risk-based access controls with conditional policies
  • Establish incident response procedures for compromised roles
5. Performance and Scalability:
  • Implement credential caching to reduce STS API calls
  • Use regional STS endpoints for reduced latency
  • Implement retry logic with exponential backoff
  • Monitor STS API throttling and adjust application behavior
  • Use session tags for enhanced authorization decisions
  • Implement efficient credential refresh mechanisms


Enterprise Role Patterns and Anti-Patterns


1. Principle of Least Privilege with Session Policies:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": "s3:GetObject",
      "Resource": "arn:aws:s3:::my-bucket/user-${aws:userid}/*"
    }
  ]
}


2. Time-Based Access Controls:

{
  "Condition": {
    "DateGreaterThan": {
      "aws:CurrentTime": "2024-01-01T09:00:00Z"
    },
    "DateLessThan": {
      "aws:CurrentTime": "2024-01-01T17:00:00Z"
    },
    "ForAllValues:StringEquals": {
      "aws:RequestedRegion": ["us-west-2"]
    }
  }
}


3. Emergency Access Pattern:

def create_emergency_access_role():
    """Create break-glass role with temporary elevated permissions"""
    
    trust_policy = {
        "Version": "2012-10-17",
        "Statement": [
            {
                "Effect": "Allow",
                "Principal": {"AWS": f"arn:aws:iam::{ACCOUNT_ID}:role/EmergencyAccessRole"},
                "Action": "sts:AssumeRole",
                "Condition": {
                    "Bool": {"aws:MultiFactorAuthPresent": "true"},
                    "StringEquals": {"aws:PrincipalTag/EmergencyAccess": "approved"},
                    "NumericLessThan": {"aws:MultiFactorAuthAge": "900"}  # 15 minutes
                }
            }
        ]
    }
    
    # Create role with temporary permissions
    # Automatically expire after 2 hours

Anti-Patterns to Avoid


1. Overly Permissive Trust Policies:

// DON'T DO THIS
{
  "Effect": "Allow",
  "Principal": {"AWS": "*"},
  "Action": "sts:AssumeRole"
}


2. Long-Lived Sessions Without Conditions:

// DON'T DO THIS
{
  "Effect": "Allow",
  "Principal": {"AWS": "arn:aws:iam::123456789012:root"},
  "Action": "sts:AssumeRole"
  // No conditions = unlimited access
}


3. Credential Hardcoding:

# DON'T DO THIS
AWS_ACCESS_KEY_ID = "AKIA..."
AWS_SECRET_ACCESS_KEY = "secret..."

# DO THIS INSTEAD
credentials = sts_client.assume_role(...)


Advanced Troubleshooting and Diagnostics


1. Access Denied Issues (Enhanced Diagnostics):
  • Use AWS CLI with --debug flag to see detailed API responses
  • Check CloudTrail for specific error codes and failure reasons
  • Validate all condition keys in trust policies
  • Test with AWS IAM Policy Simulator for permission validation
  • Verify external ID requirements and case sensitivity
  • Check for typos in role ARNs and account IDs
2. Session and Token Management:
  • Monitor credential expiration with automated renewal
  • Implement exponential backoff for STS API rate limiting
  • Handle token refresh gracefully in long-running applications
  • Use AWS SDKs' built-in credential providers when possible
  • Implement circuit breakers for STS endpoint failures
3. OIDC/SAML Federation Troubleshooting:
  • Validate OIDC provider thumbprint matches current certificate
  • Check token claims structure and required audience values
  • Verify clock synchronization between systems
  • Test token validation with online JWT decoders
  • Monitor for certificate rotation and update schedules
4. Performance and Reliability Issues:
  • Implement caching strategies for frequently used credentials
  • Use regional STS endpoints to reduce latency
  • Monitor STS API quotas and request patterns
  • Implement health checks for role assumption workflows
  • Use CloudWatch metrics to track assumption success rates
5. Security Incident Response:
  • Create runbooks for compromised role scenarios
  • Implement automated session revocation capabilities
  • Set up real-time alerting for anomalous access patterns
  • Use AWS Config to detect unauthorized role modifications
  • Maintain audit trails for forensic analysis

Production-Ready Code Examples

Advanced Session Management Class

import boto3
import json
import time
from datetime import datetime, timedelta
from botocore.exceptions import ClientError, BotoCoreError
import logging
from typing import Dict, Optional, Any
import threading
from dataclasses import dataclass

@dataclass
class AssumeRoleConfig:
    role_arn: str
    session_name: str
    duration_seconds: int = 3600
    external_id: Optional[str] = None
    session_policy: Optional[str] = None
    mfa_serial: Optional[str] = None
    region: str = 'us-east-1'

class EnhancedSTSManager:
    """Enterprise-grade STS session manager with caching and error handling"""
    
    def __init__(self):
        self.logger = logging.getLogger(__name__)
        self._sessions: Dict[str, Dict[str, Any]] = {}
        self._lock = threading.RLock()
        self.sts_client = boto3.client('sts')
        
    def assume_role(self, config: AssumeRoleConfig, mfa_token: Optional[str] = None) -> Dict[str, Any]:
        """Assume role with comprehensive error handling and caching"""
        
        cache_key = self._generate_cache_key(config)
        
        with self._lock:
            # Check cache first
            if self._is_cached_session_valid(cache_key):
                self.logger.info(f"Using cached credentials for {config.role_arn}")
                return self._sessions[cache_key]['credentials']
            
            try:
                credentials = self._perform_assume_role(config, mfa_token)
                self._cache_session(cache_key, credentials)
                return credentials
                
            except ClientError as e:
                self._handle_client_error(e, config)
                raise
            except Exception as e:
                self.logger.error(f"Unexpected error assuming role: {str(e)}")
                raise
    
    def _perform_assume_role(self, config: AssumeRoleConfig, mfa_token: Optional[str] = None) -> Dict[str, Any]:
        """Perform the actual assume role operation with retry logic"""
        
        assume_role_params = {
            'RoleArn': config.role_arn,
            'RoleSessionName': config.session_name,
            'DurationSeconds': config.duration_seconds
        }
        
        # Add optional parameters
        if config.external_id:
            assume_role_params['ExternalId'] = config.external_id
        
        if config.session_policy:
            assume_role_params['Policy'] = config.session_policy
        
        if config.mfa_serial and mfa_token:
            assume_role_params['SerialNumber'] = config.mfa_serial
            assume_role_params['TokenCode'] = mfa_token
        
        # Retry logic with exponential backoff
        max_retries = 3
        base_delay = 1
        
        for attempt in range(max_retries):
            try:
                response = self.sts_client.assume_role(**assume_role_params)
                
                # Enhance credentials with metadata
                credentials = response['Credentials']
                credentials['AssumedRoleUser'] = response['AssumedRoleUser']
                credentials['PackedPolicySize'] = response.get('PackedPolicySize', 0)
                
                self.logger.info(f"Successfully assumed role: {config.role_arn}")
                return credentials
                
            except ClientError as e:
                error_code = e.response['Error']['Code']
                
                if error_code in ['Throttling', 'RequestLimitExceeded'] and attempt < max_retries - 1:
                    delay = base_delay * (2 ** attempt)
                    self.logger.warning(f"Rate limited, retrying in {delay} seconds...")
                    time.sleep(delay)
                    continue
                else:
                    raise
    
    def _handle_client_error(self, error: ClientError, config: AssumeRoleConfig):
        """Provide detailed error analysis and suggestions"""
        
        error_code = error.response['Error']['Code']
        error_message = error.response['Error']['Message']
        
        troubleshooting_guide = {
            'AccessDenied': "Check trust policy, ensure calling identity has sts:AssumeRole permission",
            'InvalidParameterValue': "Verify role ARN format and account ID",
            'MalformedPolicyDocument': "Review session policy JSON syntax",
            'TokenRefreshRequired': "MFA token expired, obtain new token",
            'RegionDisabledException': "STS not available in requested region"
        }
        
        suggestion = troubleshooting_guide.get(error_code, "Check AWS documentation for error code")
        
        self.logger.error(f"AssumeRole failed: {error_code} - {error_message}")
        self.logger.error(f"Suggestion: {suggestion}")
        self.logger.error(f"Role ARN: {config.role_arn}")
    
    def _generate_cache_key(self, config: AssumeRoleConfig) -> str:
        """Generate unique cache key for session"""
        return f"{config.role_arn}:{config.session_name}:{config.duration_seconds}"
    
    def _is_cached_session_valid(self, cache_key: str) -> bool:
        """Check if cached session is still valid"""
        if cache_key not in self._sessions:
            return False
        
        session = self._sessions[cache_key]
        expiration = datetime.fromisoformat(session['credentials']['Expiration'].replace('Z', '+00:00'))
        
        # Consider session valid if more than 5 minutes remaining
        return datetime.now(expiration.tzinfo) < (expiration - timedelta(minutes=5))
    
    def _cache_session(self, cache_key: str, credentials: Dict[str, Any]):
        """Cache session credentials"""
        self._sessions[cache_key] = {
            'credentials': credentials,
            'cached_at': datetime.utcnow()
        }
    
    def get_session_info(self, cache_key: str) -> Optional[Dict[str, Any]]:
        """Get information about cached session"""
        with self._lock:
            if cache_key in self._sessions:
                session = self._sessions[cache_key]
                return {
                    'cached_at': session['cached_at'],
                    'expires_at': session['credentials']['Expiration'],
                    'assumed_role_arn': session['credentials']['AssumedRoleUser']['Arn']
                }
        return None
    
    def revoke_session(self, cache_key: str):
        """Manually revoke cached session"""
        with self._lock:
            if cache_key in self._sessions:
                del self._sessions[cache_key]
                self.logger.info(f"Revoked cached session: {cache_key}")

# Usage example
def main():
    manager = EnhancedSTSManager()
    
    config = AssumeRoleConfig(
        role_arn='arn:aws:iam::111122223333:role/EKSAdminRole',
        session_name=f'enhanced-session-{int(time.time())}',
        duration_seconds=3600,
        external_id='unique-external-id-2024'
    )
    
    try:
        credentials = manager.assume_role(config, mfa_token='123456')
        
        # Use credentials to create service clients
        eks_client = boto3.client(
            'eks',
            aws_access_key_id=credentials['AccessKeyId'],
            aws_secret_access_key=credentials['SecretAccessKey'],
            aws_session_token=credentials['SessionToken'],
            region_name='us-west-2'
        )
        
        # Your EKS operations here
        clusters = eks_client.list_clusters()
        print(f"Found {len(clusters['clusters'])} EKS clusters")
        
    except Exception as e:
        logging.error(f"Failed to assume role: {str(e)}")

if __name__ == "__main__":
    logging.basicConfig(level=logging.INFO)
    main()



Reference and Additional Resources

Enterprise Adoption Checklist


Phase 1: Foundation (Weeks 1-2)
☐ Establish AWS Organizations structure
☐ Define role naming conventions and tagging strategy
☐ Create central identity account (hub-and-spoke model)
☐ Enable CloudTrail in all accounts
☐ Set up basic cross-account roles

Phase 2: Security Hardening (Weeks 3-4)
☐ Implement MFA requirements for all role assumptions
☐ Add IP restrictions and geographic controls
☐ Deploy permission boundaries
☐ Configure AWS Config rules for compliance
☐ Set up CloudWatch alarms for suspicious activities

Phase 3: Automation (Weeks 5-6)
☐ Deploy Infrastructure as Code for role management
☐ Implement automated compliance checking
☐ Create self-service role request portal
☐ Set up just-in-time access workflows
☐ Deploy credential caching solutions

Phase 4: Advanced Features (Weeks 7-8)
☐ Implement break-glass procedures
☐ Deploy advanced monitoring and alerting
☐ Create emergency response runbooks
☐ Establish regular access review processes
☐ Integrate with existing identity providers

Ongoing Maintenance
☐ Regular role and permission audits
☐ Security awareness training for teams
☐ Performance monitoring and optimization
☐ Threat model updates and security reviews
☐ Documentation and procedure updates