Amazon Cognito Now Supports Access Token Customization for Machine-to-Machine (M2M) Authorization Flows
Kajanan Suganthan
1.Introduction
Amazon Cognito, AWS’s identity and access management service, now supports access token customization for machine-to-machine (M2M) authorization flows. This enhancement provides greater flexibility and security for developers managing authentication between services and applications.
In this article, we will explore the significance of this update, how it enhances M2M authentication, and the potential use cases for organizations leveraging Amazon Cognito.
2.Understanding Machine-to-Machine (M2M) Authorization Flows
M2M authorization flows are essential for enabling secure interactions between applications, microservices, and cloud services without requiring human intervention. In these workflows, a service or application requests an access token to authenticate and authorize API requests to another service.
Amazon Cognito provides identity and authentication capabilities using OAuth 2.0, OpenID Connect, and JWT tokens. With the latest update, Cognito now allows developers to customize access tokens dynamically, enabling them to include additional claims, enforce granular access policies, and improve interoperability between services.
3.Benefits of Access Token Customization
3.1 Enhanced Security and Compliance
Customizable Security Policies: With customizable access tokens, developers can embed application-specific security features, such as user roles or session data, directly within the token. This provides an additional layer of security where only users with valid tokens (and the appropriate claims) can gain access.
Identity and Permissions Verification: Custom claims within the access token allow the system to verify the identity and permissions of a user or service. This helps ensure that only authorized entities can access sensitive resources, which is essential for applications that handle highly confidential data.
Zero-Trust Model Implementation: Custom tokens are key to enforcing a zero-trust security model. By ensuring that every request is authenticated based on the token's claims, organizations can ensure that no entity is trusted by default. Every interaction is verified, regardless of whether it originates internally or externally.
Compliance Support: Customizable tokens also support regulatory compliance. Tokens can be configured to include data necessary for audit logging, access control, and data privacy. For example, you can embed GDPR-compliant claims to verify that personal data is only accessed in ways that meet privacy standards. This ensures that your applications are aligned with industry regulations and best practices.
Reduced Dependency on External Security Systems: By integrating security features into the token, there's less reliance on external identity and security services for authentication. This reduces the risk of security breaches from third-party dependencies while improving performance by reducing external API calls.
3.2 Greater Flexibility in Authentication and Authorization
Tailored Tokens for Specific Needs: Access tokens can be fully customized to suit the needs of specific applications or organizations. Developers can choose to include a variety of claims that represent roles, access levels, geographical locations, or even organization-specific identifiers. This allows organizations to build fine-grained access control models directly within the token.
Fine-Grained Access Control: Custom claims within the token enable highly specific access control decisions. For example, a token could include data such as the user's department or subscription level, allowing the system to grant or deny access based on a very granular understanding of the user's role or status.
Seamless Integration with Authorization Frameworks: Customizable tokens allow integration with existing authorization systems or frameworks that organizations may already have in place, such as OAuth2 or OpenID Connect. This allows for seamless adaptation without needing to overhaul existing systems, making it easier to adopt a new authentication system.
Dynamic User Attributes: Instead of relying on static permissions, tokens can be dynamically populated with user attributes at the time of issuance. For example, tokens can reflect whether the user is part of a specific team or has completed a necessary security check. This flexibility allows for real-time adjustments to access control based on the latest user data.
Customizable Security Models: Organizations can craft their own unique security models using customized tokens. For example, a financial institution may include claims that reflect a user’s account access level, transaction limits, or compliance status, enabling the system to implement policies specific to the financial sector.
3.3 Improved Interoperability with Third-Party APIs
Third-Party API Compatibility: Customizing the format and claims in the access token ensures compatibility with third-party APIs that require specific token structures or claim types. For instance, an external service might require a specific claim for user verification or a particular encoding for token validation.
Smoother Integration: With custom tokens, external integrations become much easier to manage. The need for middleware to transform tokens before sending them to external services is eliminated, reducing complexity. This enables smoother, more direct interactions between systems and APIs.
Reduced Development Overhead: Rather than creating additional middleware to handle token transformations, developers can configure the token format directly to align with the requirements of external services. This reduces development overhead and ensures that the integration process is simpler and more efficient.
Fewer Token Transformation Layers: Customizing tokens to meet external API standards eliminates the need for adding additional transformation layers, which can slow down communication and add complexity. This results in a more streamlined and performant solution.
Improved API Integration Security: Custom tokens can also enhance the security of API interactions by ensuring that the third-party service is able to verify claims directly within the token, reducing the chances of data manipulation or unauthorized access.
3.4 Optimized Performance for Machine-to-Machine (M2M) Workflows
Reduced API Call Dependency: By embedding claims directly into the access token, services can avoid making additional API calls to verify permissions or user data. This reduces the load on the authentication system and improves the overall performance of the application.
Faster Decision-Making: When tokens include the necessary information for authorization and permissions, the decision-making process is faster. Machines and services do not need to query external systems for verification, enabling quicker processing times for each request.
Lower Latency: Since the claims necessary for authorization are embedded within the token, services can process requests more quickly without waiting for external validation. This reduces latency, which is critical in high-demand environments, such as financial services or real-time data streaming.
High-Volume Scalability: In Machine-to-Machine (M2M) workflows, where large volumes of requests are common, optimized performance is essential. Custom tokens ensure that the workflow can scale by minimizing the overhead involved in user authentication. This is particularly beneficial in scenarios where latency is critical, such as IoT systems or microservices architectures.
Improved System Efficiency: By reducing external dependencies, services can perform the necessary authorization checks without unnecessary round-trip communication to authentication services, improving the overall efficiency of the system. This is especially important in distributed environments or cloud-native applications that handle large-scale interactions.
4.How to Customize Access Tokens in Amazon Cognito
Amazon Cognito allows developers to customize access tokens using AWS Lambda triggers. By leveraging Cognito's Token Customization Lambda Trigger, developers can modify the claims and attributes within access tokens before they are issued.
4.1 Create an AWS Lambda Function
Lambda Function Development: Start by creating an AWS Lambda function that will process the access token claims. This Lambda function is the core of your customization process, allowing you to modify or enrich the tokens issued by Cognito. The Lambda function can be written in languages supported by AWS Lambda, such as Node.js, Python, or Java.
Modify Access Token Claims: The function will have logic to add, modify, or remove specific claims from the token. For example, if you need to include custom attributes like user department or account access level, you can insert them into the token payload. Additionally, you can remove unnecessary attributes to reduce token size and improve security.
Business Logic Implementation: In this step, developers will define the business rules and logic that determine which attributes to include. This can involve checking conditions like user roles, groups, or organizational membership to conditionally include specific claims in the token. For example, if a user is part of the "Admin" group, you could add a custom claim reflecting administrative access.
Access Control Decisions: The Lambda function should ensure that it enforces the required access control policies, such as adding permissions or roles based on the user's context, and ensuring compliance with security requirements.
4.2 Configure Amazon Cognito User Pool
Attach the Lambda Function to the User Pool: After the Lambda function is developed, the next step is to link it to the Cognito User Pool by configuring the Token Customization Trigger. This trigger is executed when the token is about to be issued after a successful authentication event (e.g., after a user logs in).
Set Up Trigger in Cognito: In the Cognito console, navigate to the User Pools section and choose the desired pool. Under the Triggers section, configure the Token Customization Trigger to point to the newly created Lambda function. This ensures that the function will be executed as part of the token generation process.
Event Configuration: When setting up the trigger, specify the event that will invoke the Lambda function. In this case, the trigger should fire after successful user authentication, so the Lambda function can manipulate the token claims before they are returned to the user.
Ensure Proper Permissions: The Lambda function must have the correct IAM role and permissions to interact with Amazon Cognito, ensuring that it can modify the claims in the token without running into access issues.
4.3 Define Custom Claims
Custom Claim Identification: Decide which custom claims need to be included in the token based on your business requirements. Claims can be user attributes like department, region, or custom metadata that your application uses for authorization decisions.
Add Claims to the Token: In the Lambda function, you will define logic to add these custom claims to the token. This can involve querying user attributes from the Cognito User Pool or integrating with other services to retrieve relevant data. For example, if you need to include the user’s organization ID, you would fetch this information and add it as a custom claim within the token.
Modify Standard Claims: In addition to adding custom claims, you might want to modify standard claims like sub, iat, or exp. For instance, you could extend the exp claim to include a shorter token expiration for users with certain roles or group memberships.
Use Claims for Fine-Grained Access Control: Custom claims enable the token to carry rich context about the user, such as role-based access, permissions, or any other metadata necessary for controlling access to your application’s resources. For example, you can use the claims to provide data that determines whether the user has access to a certain API or resource, depending on their role.
4.4 Deploy and Test
Deploy the Updated Lambda Function: After completing the Lambda function and configuring the Cognito trigger, deploy the updated Lambda function in AWS. This ensures that the new logic is active and ready to process token claims during user authentication.
Test the Custom Token Generation: Once deployed, test the authentication flow by initiating login requests using a test user in your Cognito User Pool. You can use tools like Postman or cURL to simulate API calls that authenticate the user and generate the access token.
Check the Token: Examine the access token returned by Cognito to verify that it includes the custom claims you have defined. You can decode the token using JWT tools to ensure that the claims are correctly populated and that the token structure matches your expected format.
Iterate and Debug: If the token doesn’t include the expected claims or if there are any errors in the Lambda function, debug and iterate on the Lambda code. This may involve reviewing logs in AWS CloudWatch to track function execution and resolve any issues.
API Client Testing: In addition to direct testing, it’s essential to validate the custom token in your application's API clients. Ensure that your application can process and use the custom claims for authorization and access control purposes as intended. You may need to adjust your application logic to account for new claims in the token.
5.How to get start
Step 1: Set Up an Amazon Cognito User Pool
Sign in to the AWS Management Console.
Navigate to Amazon Cognito:
Go to the Cognito service under the Security, Identity, & Compliance section.
Create a New User Pool:
Click on Create a user pool and follow the prompts to set up your pool.
Choose the settings that match your application’s needs, such as authentication flow, multi-factor authentication (MFA), and user sign-up options.
Configure App Client:
Once the user pool is created, create an App client to allow your application to interact with Cognito.
Under the App clients section, configure settings such as token expiration times.
Step 2: Create an AWS Lambda Function
Go to the Lambda Console:
In the AWS Management Console, search for and select Lambda.
Create a New Lambda Function:
Click on Create function.
Choose Author from scratch, give it a name (e.g., TokenCustomizationFunction), and select the runtime (e.g., Node.js or Python).
For the role, either create a new role or use an existing role that has permissions to invoke Cognito and modify the token.
Write the Lambda Code:
Inside the Lambda function, write the code to modify the access token. For example, you could modify claims like adding custom attributes such as user roles, region, or permissions.
Example code snippet (in Node.js):
exports.handler = async (event) => {
// Modify token claims
event.response = {
claimsOverrideDetails: {
claimsToAddOrOverride: {
"custom:role": event.request.userAttributes['custom:role'],
"custom:department": event.request.userAttributes['custom:department'],
},
},
};
return event;
};
This code adds custom claims (custom:role, custom:department) to the token before it's issued.
Step 3: Configure the Token Customization Trigger in Cognito
Navigate to Cognito User Pool Settings:
In the Amazon Cognito console, go to your User Pool and open the Triggers section.
Link Lambda Function to Token Customization Trigger:
Under the Token Customization section, select Create a trigger and choose the Lambda function you created earlier.
This ensures that whenever Cognito issues a token, your Lambda function will be triggered to modify the token before it is returned.
Enable Lambda Trigger:
Save your changes to ensure the Lambda function is linked to the user pool and will run during the authentication process.
Step 4: Define Custom Claims
Define Custom Claims in Lambda Function:
Inside the Lambda function, identify the custom claims that you need (e.g., user’s department, role, organization ID, etc.).
These claims should be extracted from the user attributes or other systems (like an external database or an API).
Add Claims to Token:
Modify the Lambda function to add these custom claims to the token.
For example, adding "custom:role" or "custom:team" to the access token helps your application make authorization decisions based on these claims.
Step 5: Deploy and Test the Token Customization
Deploy Lambda Function:
After writing the Lambda function, click Deploy to save and make it live.
Test Token Issuance:
Use tools like Postman, cURL, or the Cognito Hosted UI to simulate the authentication flow.
Log in with a test user and verify the returned access token contains your custom claims.
Decode and Inspect the Token:
Use tools like JWT.io to decode the JWT token and inspect the claims. Ensure your custom claims appear as expected in the decoded token.
Test API Clients:
If you have application clients (mobile apps, web apps, etc.), test them to ensure they can correctly process and use the custom claims in the access token.
Step 6: Iterate and Refine
Debugging: If the custom claims don’t appear in the token, check the Lambda logs in CloudWatch Logs to troubleshoot.
Refinement: Based on testing, you may need to refine the Lambda logic to add or remove claims, adjust logic based on roles, or modify other aspects of the token.
6. Benefits of Machine-to-Machine (M2M) Authorization Flows
Customizing access tokens in Amazon Cognito offers several benefits, making it a powerful feature for developers and organizations looking to fine-tune their authentication and authorization processes. Below are the key benefits:
6.1 Enhanced Security and Compliance
Fine-Grained Control: Custom access tokens allow you to include specific claims related to user identity, roles, or permissions. This enables better control over who can access particular resources, ensuring that only authorized users can perform certain actions.
Zero-Trust Security Models: By embedding custom claims that are specific to your security policies, such as user roles or organizational identifiers, you can implement a zero-trust security model. This helps ensure that no implicit trust is granted based on location or network but is instead based on authenticated and authorized claims within the token.
Compliance Requirements: Custom tokens help businesses meet specific industry compliance standards (e.g., GDPR, HIPAA) by ensuring that tokens contain only the data necessary for a specific operation, reducing the risk of exposing sensitive user information.
6.2 Greater Flexibility in Authentication and Authorization
Tailored Claims: Organizations can include custom claims like user attributes, business-specific identifiers, or metadata, allowing the token to carry exactly the information needed for their specific use case.
Seamless Integration: Custom tokens allow for easy integration with existing authentication and authorization frameworks. By customizing the token's structure, businesses can ensure compatibility with legacy systems, third-party applications, or microservices, all without needing additional middleware to transform tokens.
Role-Based Access Control (RBAC): You can include role or permission-based claims that allow for role-specific access. This helps ensure users only access resources relevant to their roles within the organization.
6.3 Improved Interoperability with Third-Party APIs
Custom Token Formats: Many external services or APIs require specific token formats or custom claims to work. By customizing access tokens, organizations can ensure that tokens meet the required standards for interacting with these services, avoiding the need for complex token transformation layers.
Cross-Platform Consistency: Customizing tokens helps maintain consistency in how authentication is handled across multiple platforms (e.g., web, mobile, third-party applications). You can ensure that all platforms use the same token format, reducing inconsistencies and potential security risks.
6.4 Optimized Performance for Machine-to-Machine (M2M) Workflows
Reduced External API Calls: By embedding relevant claims directly into the access token, you can reduce the need for repeated API calls to validate user permissions or retrieve user data. This can help lower network latency and speed up authorization decisions, making the system more efficient, particularly for machine-to-machine (M2M) workflows.
Faster Authorization: When all the necessary information is included in the token (e.g., user roles, permissions), services can make faster authorization decisions without querying additional databases or services. This is especially important in systems where speed is critical, such as in real-time data processing or microservice architectures.
6.5 Simplified User Experience
Reduced Friction for Users: By customizing the token with information like roles or permissions, you can streamline the user experience. For instance, the token could directly indicate a user's access level to different resources, avoiding the need for the user to go through additional authorization steps or login processes.
Dynamic Access Control: Custom tokens can adjust dynamically based on the user’s context (e.g., a user’s group, region, or account level), allowing you to provide a personalized and seamless experience while maintaining tight security controls.
6.6 Improved Scalability and Flexibility
Easily Add New Claims: As your application or business grows, the requirements for what needs to be included in access tokens might change. Customizing tokens allows you to scale and adapt the claims included without needing to overhaul your entire authentication system.
Support for Multiple Environments: If your application operates in multiple environments (e.g., development, staging, production), you can customize tokens differently depending on the environment. This helps ensure that each environment has appropriate security and access controls.
6.7 Better Auditing and Monitoring
Track User Actions: Custom claims allow you to embed additional metadata about user actions or resources they access, which can be useful for auditing purposes. For instance, custom claims might include access timestamps or session information that helps in monitoring and logging user activities.
Regulatory Reporting: For businesses that need to comply with regulations, customizing tokens can ensure that you track and report on the correct set of user information as part of audit trails. You can include custom claims that record critical events, like changes in user permissions or access rights.
6.8 Cost Efficiency
Fewer External Requests: By embedding necessary data directly in the token, your systems will make fewer calls to external services for authorization, which can help reduce API request costs. This is especially beneficial in cloud environments, where each API call can incur costs.
Simplified Architecture: Custom tokens can help simplify your overall architecture by reducing the need for additional services or middleware for token transformation or external validation. This can help lower infrastructure costs and improve system performance.
. Use Cases for Access Token Customization in M2M Authorization
7.1 Secure API Authentication
Description: Customizing access tokens enables services to authenticate and authorize API calls with precise control over the permissions granted to each request. For example, custom claims in the token can determine whether a service has permission to access specific endpoints, which is essential for enforcing the principle of least privilege.
Use Case: A payment service API may issue tokens that include specific permissions for reading transaction history, processing payments, or modifying user data. This ensures that only authorized services or users can perform sensitive actions.
7.2 Multi-Tenant Applications
Description: In multi-tenant software applications, access tokens can be customized to include tenant-specific attributes, such as tenant ID, user roles, or feature flags. This enables SaaS providers to ensure that each tenant is securely isolated and that access is granted only to the appropriate resources within their respective environments.
Use Case: A SaaS application that serves multiple customers (tenants) can use access tokens to embed tenant-specific data, such as a tenant's ID or custom settings. This ensures that a user from Tenant A cannot access resources or data from Tenant B, even though both tenants share the same infrastructure.
7.3 IoT Device Authentication
Description: Internet of Things (IoT) devices often have specific security policies that need to be enforced. By customizing access tokens, each IoT device can receive a tailored token that includes claims based on the device’s identity and its specific security requirements. This allows devices to authenticate with other services or the cloud while ensuring they are only granted access to resources that match their security context.
Use Case: An IoT sensor used in a smart factory could receive an access token containing device-specific claims like sensor type, location, or access permissions. This ensures that the sensor can only transmit data to the cloud and interact with authorized services related to its specific function.
7.4 Regulated Environments
Description: In regulated industries, such as healthcare, finance, or government, it is critical to ensure compliance with data protection regulations. Customizing access tokens allows businesses to control what data is included in tokens and to restrict access to sensitive information based on the role or the environment. This can help organizations avoid exposing sensitive data unnecessarily and ensure that only authorized parties can access it.
Use Case: A healthcare application that uses Cognito for patient authentication can customize access tokens to exclude certain personal health information (PHI) unless the user or service has the necessary permissions. This helps meet compliance standards like HIPAA by ensuring that sensitive health data is only accessible to authorized users or services.
8. Pricing for Access Token Customization in Amazon Cognito (2025)
As of 2025, Amazon Cognito pricing for access token customization primarily revolves around Cognito User Pools and the usage of AWS Lambda functions for the Token Customization Lambda Trigger. The cost structure includes several components, with the key aspects being the number of requests, the duration of Lambda execution, and any associated data transfer fees. Below is an outline of the pricing model:
8.1 Amazon Cognito User Pool Pricing
Active Users: Amazon Cognito charges based on the number of monthly active users (MAUs) in the user pool. A "monthly active user" is defined as a user who signs in or is authenticated during the month.
Free Tier: The free tier of Amazon Cognito includes up to 50,000 MAUs per month.
Beyond Free Tier:
First 50,000 MAUs: Free
Next 950,000 MAUs: $0.0055 per MAU
Beyond 1,000,000 MAUs: Contact AWS for pricing.
8.2 AWS Lambda Pricing (for Token Customization)
Requests: AWS Lambda charges are based on the number of requests made to the Lambda function.
First 1M requests per month: Free
After the Free Tier: $0.20 per 1 million requests.
Duration: Lambda execution time is billed based on the memory allocated to the function and the duration of the execution. The pricing is as follows:
$0.00001667 per GB-second (after the free tier).
For example, if a Lambda function uses 128 MB of memory and runs for 500ms, the cost would be $0.000004167 per invocation.
8.3 Data Transfer Pricing
Data Transfer In: Free (inbound data is always free).
Data Transfer Out to the Internet:
First 1 GB per month: Free
Beyond 1 GB: $0.09 per GB for the next 10 TB.
8.4 Example Pricing Calculation
Let’s assume a scenario where an application has the following usage in one month:
100,000 active users using Amazon Cognito for authentication and access token customization.
1,000,000 Lambda requests made to customize access tokens.
The average Lambda function execution time is 300 ms, with 128 MB of allocated memory.
Cost Breakdown:
Amazon Cognito User Pool:
First 50,000 MAUs: Free
Next 50,000 MAUs: 50,000 * $0.0055 = $275
Total for Cognito User Pool = $275
AWS Lambda (for Token Customization):
Requests: First 1M requests: Free
Total for Lambda Requests = $0 (since within the free tier)
Duration: 1,000,000 requests with 128 MB memory for 300 ms:
1,000,000 requests * 128 MB * 0.3 seconds = 30,000,000 MB-seconds = 30,000 GB-seconds.
30,000 GB-seconds * $0.00001667 = $0.50
Total for Lambda Duration = $0.50
Data Transfer:
Assume 1 GB of data transferred out to the internet.
1 GB * $0.09 = $0.09
Total for Data Transfer = $0.09
Total Monthly Cost:
Cognito User Pool: $275
AWS Lambda (Requests and Duration): $0.50
Data Transfer: $0.09
Total = $275 + $0.50 + $0.09 = $275.59
8.5 Key Takeaways:
Free Tier: The free tier for both Amazon Cognito (up to 50,000 MAUs) and AWS Lambda (up to 1 million requests and 400,000 GB-seconds) means that small applications with limited use can take advantage of these services without incurring significant costs.
Scalability: As the number of active users and Lambda invocations increases, the costs will rise, but the pricing model is relatively affordable for most businesses with moderate usage.
Cost Optimization: By optimizing Lambda function execution (e.g., reducing the duration or memory allocation), you can further control costs, especially if token customization becomes more frequent in high-scale environments.
9. Conclusion
Amazon Cognito’s new support for access token customization in M2M authorization flows significantly enhances security, flexibility, and efficiency for developers managing service-to-service authentication. By leveraging this feature, businesses can create more secure and optimized authentication workflows while maintaining compliance with industry standards.
This update marks an important step forward in making Amazon Cognito a more powerful tool for managing modern authentication needs in machine-to-machine interactions.