Tag Archives: Amazon Verified Permissions

Simplify How You Manage Authorization in Your Applications with Amazon Verified Permissions – Now Generally Available

Post Syndicated from Danilo Poccia original https://aws.amazon.com/blogs/aws/simplify-how-you-manage-authorization-in-your-applications-with-amazon-verified-permissions-now-generally-available/

When developing a new application or integrating an existing one into a new environment, user authentication and authorization require significant effort to be correctly implemented. In the past, you would have built your own authentication system, but today you can use an external identity provider like Amazon Cognito. Yet, authorization logic is typically implemented in code.

This might begin simply enough, with all users assigned a role for their job function. However, over time, these permissions grow increasingly complex. The number of roles expands, as permissions become more fine-grained. New use cases drive the need for custom permissions. For instance, one user might share a document with another in a different role, or a support agent might require temporary access to a customer account to resolve an issue. Managing permissions in code is prone to errors, and presents significant challenges when auditing permissions and deciding who has access to what, particularly when these permissions are expressed in different applications and using multiple programming languages.

At re:Invent 2022, we introduced in preview Amazon Verified Permissions, a fine-grained permissions management and authorization service for your applications that can be used at any scale. Amazon Verified Permissions centralizes permissions in a policy store and helps developers use those permissions to authorize user actions within their applications. Similar to how an identity provider simplifies authentication, a policy store let you manage authorization in a consistent and scalable way.

To define fine-grained permissions, Amazon Verified Permissions uses Cedar, an open-source policy language and software development kit (SDK) for access control. You can define a schema for your authorization model in terms of principal types, resource types, and valid actions. In this way, when a policy is created, it is validated against your authorization model. You can simplify the creation of similar policies using templates. Changes to the policy store are audited so that you can see of who made the changes and when.

You can then connect your applications to Amazon Verified Permissions through AWS SDKs to authorize access requests. For each authorization request, the relevant policies are retrieved and evaluated to determine whether the action is permitted or not. You can reproduce those authorization requests to confirm that permissions work as intended.

Today, I am happy to share that Amazon Verified Permissions is generally available with new capabilities and a simplified user experience in the AWS Management Console.

Let’s see how you can use it in practice.

Creating a Policy Store with Amazon Verified Permissions
In the Amazon Verified Permissions console, I choose Create policy store. A policy store is a logical container that stores policies and schema. Authorization decisions are made based on all the policies present in a policy store.

To configure the new policy store, I can use different methods. I can start with a guided setup, a sample policy store (such as for a photo-sharing app, an online store, or a task manager), or an empty policy store (recommended for advanced users). I select Guided setup, enter a namespace for my schema (MyApp), and choose Next.

Console screenshot.

Resources are the objects that principals can act on. In my application, I have Users (principals) that can create, read, update, and delete Documents (resources). I start to define the Documents resource type.

I enter the name of the resource type and add two required attributes:

  • owner (String) to specify who is the owner of the document.
  • isPublic (Boolean) to flag public documents that anyone can read.

Console screenshot.

I specify four actions for the Document resource type:

  • DocumentCreate
  • DocumentRead
  • DocumentUpdate
  • DocumentDelete

Console screenshot.

I enter User as the name of the principal type that will be using these actions on Documents. Then, I choose Next.

Console screenshot.

Now, I configure the User principal type. I can use a custom configuration to integrate an external identity source, but in this case, I use an Amazon Cognito user pool that I created before. I choose Connect user pool.

Console screenshot.

In the dialog, I select the AWS Region where the user pool is located, enter the user pool ID, and choose Connect.

Console screenshot.

Now that the Amazon Cognito user pool is connected, I can add another level of protection by validating the client application IDs. For now, I choose not to use this option.

In the Principal attributes section, I select which attributes I am planning to use for attribute-based access control in my policies. I select sub (the subject), used to identify the end user according to the OpenID Connect specification. I can select more attributes. For example, I can use email_verified in a policy to give permissions only to Amazon Cognito users whose email has been verified.

Console screenshot.

As part of the policy store creation, I create a first policy to give read access to user danilop to the doc.txt document.

Console screenshot.

In the following code, the console gives me a preview of the resulting policy using the Cedar language.

permit(
  principal == MyApp::User::"danilop",
  action in [MyApp::Action::"DocumentRead"],
  resource == MyApp::Document::"doc.txt"
) when {
  true
};

Finally, I choose Create policy store.

Adding Permissions to the Policy Store
Now that the policy store has been created, I choose Policies in the navigation pane. In the Create policy dropdown, I choose Create static policy. A static policy contains all the information needed for its evaluation. In my second policy, I allow any user to read public documents. By default everything is forbidden, so in Policy Effect I choose Permit.

In the Policy scope, I leave All principals and All resources selected, and select the DocumentRead action. In the Policy section, I change the when condition clause to limit permissions to resources where isPublic is equal to true:

permit (
  principal,
  action in [MyApp::Action::"DocumentRead"],
  resource
)
when { resource.isPublic };

I enter a description for the policy and choose Create policy.

For my third policy, I create another static policy to allow full access to the owner of a document. Again, in Policy Effect, I choose Permit and, in the Policy scope, I leave All principals and All resources selected. This time, I also leave All actions selected.

In the Policy section, I change the when condition clause to limit permissions to resources where the owner is equal to the sub of the principal:

permit (principal, action, resource)
when { resource.owner == principal.sub };

In my application, I need to allow read access to specific users that are not owners of a document. To simplify that, I create a policy template. Policy templates let me create policies from a template that uses placeholders for some of their values, such as the principal or the resource. The placeholders in a template are keywords that start with the ? character.

In the navigation pane, I choose Policy templates and then Create policy template. I enter a description and use the following policy template body. When using this template, I can specify the value for the ?principal and ?resource placeholders.

permit(
  principal == ?principal,
  action in [MyApp::Action::"DocumentRead"],
  resource == ?resource
);

I complete the creation of the policy template. Now, I use the template to simplify the creation of policies. I choose Policies in the navigation pane, and then Create a template-linked policy in the Create policy dropdown. I select the policy template I just created and choose Next.

To give access to a user (danilop) for a specific document (new-doc.txt), I just pass the following values (note that MyApp is the namespace of the policy store):

  • For the Principal: MyApp::User::"danilop"
  • For the Resource: MyApp::Document::"new-doc.txt"

I complete the creation of the policy. It’s now time to test if the policies work as expected.

Testing Policies in the Console
In my applications, I can use the AWS SDKs to run an authorization request. The console provides a way to to simulate what my applications would do. I choose Test bench in the navigation pane. To simplify testing, I use the Visual mode. As an alternative, I have the option to use the same JSON syntax as in the SDKs.

As Principal, I pass the janedoe user. As Resource, I use requirements.txt. It’s not a public document (isPublic is false) and the owner attribute is equal to janedoe‘s sub. For the Action, I select MyApp::Action::"DocumentUpdate".

When running an authorization request, I can pass Additional entities with more information about principals and resources associated with the request. For now, I leave this part empty.

I choose Run authorization request at the top to see the decision based on the current policies. As expected, the decision is allow. Here, I also see which policies hav been satisfied by the authorization request. In this case, it is the policy that allows full access to the owner of the document.

I can test other values. If I change the owner of the document and the action to DocumentRead, the decision is deny. If I then set the resource attribute isPublic to true, the decision is allow because there is a policy that permits all users to read public documents.

Handling Groups in Permissions
The administrative users in my application need to be able to delete any document. To do so, I create a role for admin users. First, I choose Schema in the navigation pane and then Edit schema. In the list of entity types, I choose to add a new one. I use Role as Type name and add it. Then, I select User in the entity types and edit it to add Role as a parent. I save changes and create the following policy:

permit (
  principal in MyApp::Role::"admin",
  action in [MyApp::Action::"DocumentDelete"],
  resource
);

In the Test bench, I run an authorization request to check if user jeffbarr can delete (DocumentDelete) resource doc.txt. Because he’s not the owner of the resource, the request is denied.

Now, in the Additional entities, I add the MyApp::User entity with jeffbarr as identifier. As parent, I add the MyApp::Role entity with admin as identifier and confirm. The console warns me that entity MyApp::Role::"admin" is referenced, but it isn’t included in additional entities data. I choose to add it and fix this issue.

I run an authorization request again, and it is now allowed because, according to the additional entities, the principal (jeffbarr) is an admin.

Using Amazon Verified Permissions in Your Application
In my applications, I can run an authorization requests using the isAuthorized API action (or isAuthrizedWithToken, if the principal comes from an external identity source).

For example, the following Python code uses the AWS SDK for Python (Boto3) to check if a user has read access to a document. The authorization request uses the policy store I just created.

import boto3
import time

verifiedpermissions_client = boto3.client("verifiedpermissions")

POLICY_STORE_ID = "XAFTHeCQVKkZhsQxmAYXo8"

def is_authorized_to_read(user, resource):

    authorization_result = verifiedpermissions_client.is_authorized(
        policyStoreId=POLICY_STORE_ID, 
        principal={"entityType": "MyApp::User", "entityId": user}, 
        action={"actionType": "MyApp::Action", "actionId": "DocumentRead"},
        resource={"entityType": "MyApp::Document", "entityId": resource}
    )

    print('Can {} read {} ?'.format(user, resource))

    decision = authorization_result["decision"]

    if decision == "ALLOW":
        print("Request allowed")
        return True
    else:
        print("Request denied")
        return False

if is_authorized_to_read('janedoe', 'doc.txt'):
    print("Here's the doc...")

if is_authorized_to_read('danilop', 'doc.txt'):
    print("Here's the doc...")

I run this code and, as you can expect, the output is in line with the tests run before.

Can janedoe read doc.txt ?
Request denied
Can danilop read doc.txt ?
Request allowed
Here's the doc...

Availability and Pricing
Amazon Verified Permissions is available today in all commercial AWS Regions, excluding those that are based in China.

With Amazon Verified Permissions, you only pay for what you use based on the number of authorization requests and API calls made to the service.

Using Amazon Verified Permissions, you can configure fine-grained permissions using the Cedar policy language and simplify the code of your applications. In this way, permissions are maintained in a centralized store and are easier to audit. Here, you can read more about how we built Cedar with automated reasoning and differential testing.

Manage authorization for your applications with Amazon Verified Permissions.

Danilo

Three key security themes from AWS re:Invent 2022

Post Syndicated from Anne Grahn original https://aws.amazon.com/blogs/security/three-key-security-themes-from-aws-reinvent-2022/

AWS re:Invent returned to Las Vegas, Nevada, November 28 to December 2, 2022. After a virtual event in 2020 and a hybrid 2021 edition, spirits were high as over 51,000 in-person attendees returned to network and learn about the latest AWS innovations.

Now in its 11th year, the conference featured 5 keynotes, 22 leadership sessions, and more than 2,200 breakout sessions and hands-on labs at 6 venues over 5 days.

With well over 100 service and feature announcements—and innumerable best practices shared by AWS executives, customers, and partners—distilling highlights is a challenge. From a security perspective, three key themes emerged.

Turn data into actionable insights

Security teams are always looking for ways to increase visibility into their security posture and uncover patterns to make more informed decisions. However, as AWS Vice President of Data and Machine Learning, Swami Sivasubramanian, pointed out during his keynote, data often exists in silos; it isn’t always easy to analyze or visualize, which can make it hard to identify correlations that spark new ideas.

“Data is the genesis for modern invention.” – Swami Sivasubramanian, AWS VP of Data and Machine Learning

At AWS re:Invent, we launched new features and services that make it simpler for security teams to store and act on data. One such service is Amazon Security Lake, which brings together security data from cloud, on-premises, and custom sources in a purpose-built data lake stored in your account. The service, which is now in preview, automates the sourcing, aggregation, normalization, enrichment, and management of security-related data across an entire organization for more efficient storage and query performance. It empowers you to use the security analytics solutions of your choice, while retaining control and ownership of your security data.

Amazon Security Lake has adopted the Open Cybersecurity Schema Framework (OCSF), which AWS cofounded with a number of organizations in the cybersecurity industry. The OCSF helps standardize and combine security data from a wide range of security products and services, so that it can be shared and ingested by analytics tools. More than 37 AWS security partners have announced integrations with Amazon Security Lake, enhancing its ability to transform security data into a powerful engine that helps drive business decisions and reduce risk. With Amazon Security Lake, analysts and engineers can gain actionable insights from a broad range of security data and improve threat detection, investigation, and incident response processes.

Strengthen security programs

According to Gartner, by 2026, at least 50% of C-Level executives will have performance requirements related to cybersecurity risk built into their employment contracts. Security is top of mind for organizations across the globe, and as AWS CISO CJ Moses emphasized during his leadership session, we are continuously building new capabilities to help our customers meet security, risk, and compliance goals.

In addition to Amazon Security Lake, several new AWS services announced during the conference are designed to make it simpler for builders and security teams to improve their security posture in multiple areas.

Identity and networking

Authorization is a key component of applications. Amazon Verified Permissions is a scalable, fine-grained permissions management and authorization service for custom applications that simplifies policy-based access for developers and centralizes access governance. The new service gives developers a simple-to-use policy and schema management system to define and manage authorization models. The policy-based authorization system that Amazon Verified Permissions offers can shorten development cycles by months, provide a consistent user experience across applications, and facilitate integrated auditing to support stringent compliance and regulatory requirements.

Additional services that make it simpler to define authorization and service communication include Amazon VPC Lattice, an application-layer service that consistently connects, monitors, and secures communications between your services, and AWS Verified Access, which provides secure access to corporate applications without a virtual private network (VPN).

Threat detection and monitoring

Monitoring for malicious activity and anomalous behavior just got simpler. Amazon GuardDuty RDS Protection expands the threat detection capabilities of GuardDuty by using tailored machine learning (ML) models to detect suspicious logins to Amazon Aurora databases. You can enable the feature with a single click in the GuardDuty console, with no agents to manually deploy, no data sources to enable, and no permissions to configure. When RDS Protection detects a potentially suspicious or anomalous login attempt that indicates a threat to your database instance, GuardDuty generates a new finding with details about the potentially compromised database instance. You can view GuardDuty findings in AWS Security Hub, Amazon Detective (if enabled), and Amazon EventBridge, allowing for integration with existing security event management or workflow systems.

To bolster vulnerability management processes, Amazon Inspector now supports AWS Lambda functions, adding automated vulnerability assessments for serverless compute workloads. With this expanded capability, Amazon Inspector automatically discovers eligible Lambda functions and identifies software vulnerabilities in application package dependencies used in the Lambda function code. Actionable security findings are aggregated in the Amazon Inspector console, and pushed to Security Hub and EventBridge to automate workflows.

Data protection and privacy

The first step to protecting data is to find it. Amazon Macie now automatically discovers sensitive data, providing continual, cost-effective, organization-wide visibility into where sensitive data resides across your Amazon Simple Storage Service (Amazon S3) estate. With this new capability, Macie automatically and intelligently samples and analyzes objects across your S3 buckets, inspecting them for sensitive data such as personally identifiable information (PII), financial data, and AWS credentials. Macie then builds and maintains an interactive data map of your sensitive data in S3 across your accounts and Regions, and provides a sensitivity score for each bucket. This helps you identify and remediate data security risks without manual configuration and reduce monitoring and remediation costs.

Encryption is a critical tool for protecting data and building customer trust. The launch of the end-to-end encrypted enterprise communication service AWS Wickr offers advanced security and administrative controls that can help you protect sensitive messages and files from unauthorized access, while working to meet data retention requirements.

Management and governance

Maintaining compliance with regulatory, security, and operational best practices as you provision cloud resources is key. AWS Config rules, which evaluate the configuration of your resources, have now been extended to support proactive mode, so that they can be incorporated into infrastructure-as-code continuous integration and continuous delivery (CI/CD) pipelines to help identify noncompliant resources prior to provisioning. This can significantly reduce time spent on remediation.

Managing the controls needed to meet your security objectives and comply with frameworks and standards can be challenging. To make it simpler, we launched comprehensive controls management with AWS Control Tower. You can use it to apply managed preventative, detective, and proactive controls to accounts and organizational units (OUs) by service, control objective, or compliance framework. You can also use AWS Control Tower to turn on Security Hub detective controls across accounts in an OU. This new set of features reduces the time that it takes to define and manage the controls required to meet specific objectives, such as supporting the principle of least privilege, restricting network access, and enforcing data encryption.

Do more with less

As we work through macroeconomic conditions, security leaders are facing increased budgetary pressures. In his opening keynote, AWS CEO Adam Selipsky emphasized the effects of the pandemic, inflation, supply chain disruption, energy prices, and geopolitical events that continue to impact organizations.

Now more than ever, it is important to maintain your security posture despite resource constraints. Citing specific customer examples, Selipsky underscored how the AWS Cloud can help organizations move faster and more securely. By moving to the cloud, agricultural machinery manufacturer Agco reduced costs by 78% while increasing data retrieval speed, and multinational HVAC provider Carrier Global experienced a 40% reduction in the cost of running mission-critical ERP systems.

“If you’re looking to tighten your belt, the cloud is the place to do it.” – Adam Selipsky, AWS CEO

Security teams can do more with less by maximizing the value of existing controls, and bolstering security monitoring and analytics capabilities. Services and features announced during AWS re:Invent—including Amazon Security Lake, sensitive data discovery with Amazon Macie, support for Lambda functions in Amazon Inspector, Amazon GuardDuty RDS Protection, and more—can help you get more out of the cloud and address evolving challenges, no matter the economic climate.

Security is our top priority

AWS re:Invent featured many more highlights on a variety of topics, such as Amazon EventBridge Pipes and the pre-announcement of GuardDuty EKS Runtime protection, as well as Amazon CTO Dr. Werner Vogels’ keynote, and the security partnerships showcased on the Expo floor. It was a whirlwind week, but one thing is clear: AWS is working harder than ever to make our services better and to collaborate on solutions that ease the path to proactive security, so that you can focus on what matters most—your business.

For more security-related announcements and on-demand sessions, see A recap for security, identity, and compliance sessions at AWS re:Invent 2022 and the AWS re:Invent Security, Identity, and Compliance playlist on YouTube.

If you have feedback about this post, submit comments in the Comments section below.

Anne Grahn

Anne Grahn

Anne is a Senior Worldwide Security GTM Specialist at AWS based in Chicago. She has more than a decade of experience in the security industry, and has a strong focus on privacy risk management. She maintains a Certified Information Systems Security Professional (CISSP) certification.

Author

Paul Hawkins

Paul helps customers of all sizes understand how to think about cloud security so they can build the technology and culture where security is a business enabler. He takes an optimistic approach to security and believes that getting the foundations right is the key to improving your security posture.