Tag Archives: Security, Identity & Compliance

AWS Certificate Manager now supports exporting public certificates

Post Syndicated from Pravin Nair original https://aws.amazon.com/blogs/security/aws-certificate-manager-now-supports-exporting-public-certificates/

AWS Certificate Manager (ACM) simplifies the provisioning, management, and deployment of public and private TLS certificates for AWS services and your on-premises and hybrid applications. To further enhance the flexibility of ACM for diverse workloads, we’re introducing a powerful new capability: ACM exportable public certificates. You can use this capability to export public TLS certificates and associated private keys from ACM, which can be used to secure workloads on Amazon Elastic Compute Cloud (Amazon EC2) instances, Amazon Elastic Kubernetes Service (Amazon EKS) pods, on-premises servers, or servers hosted with other cloud providers. The capability supports public certificates that are newly created in your AWS account

In this post, we show you how to automate the export and distribution of public exportable certificates across a diverse infrastructure. We walk you through creating workflows that automatically deliver certificates to multiple destinations including EC2 instances and virtual machines in hybrid environments. We explore how this automation works, its benefits, and provide a step-by-step guide to get started. Additionally, we explore how you can use integration with Amazon EventBridge to trigger automatic certificate exports when certificates are issued or renewed, streamlining certificate deployment across heterogeneous environments and significantly reducing management overhead.

Background: ACM and certificate management

ACM is a managed service that removes the complexity of purchasing, uploading, and renewing TLS certificates. It provides public certificates at no additional cost for AWS services integrated with ACM such as Elastic Load Balancing (ELB), Amazon CloudFront, and Amazon API Gateway. ACM also supports importing third-party public certificates and issuing private certificates through AWS Private Certificate Authority. Prior to this release, ACM public certificates were designed for AWS services integrated with ACM such as CloudFront, providing seamless TLS encryption for those services. For use cases involving third-party content delivery networks (CDNs) or workloads terminating TLS on EC2 instances, customers typically sourced certificates from other providers or imported them into ACM for centralized management. Customers have told us that they would like to use ACM for these use cases, extending its simplicity and scalability to a wider range of environments. The new ACM exportable public certificates capability fulfills this need, enabling you to export ACM-managed public certificates for use with your custom workloads while maintaining centralized management and automated renewals.

With ACM you can now request a public certificate, validate domain ownership, and export the certificate for use with software that terminates TLS such as Apache, NGINX, or Microsoft IIS. ACM handles certificate renewals, reducing the risk of expirations that can disrupt your applications.

How it works: ACM public certificate issuance and renewal

To use ACM exportable public certificates, you need to understand how to automate certificate management using the issuance and renewal processes. In this section, we describe these processes and their automation capabilities, which are critical for deploying and maintaining certificates.

ACM public certificate issuance

Issuing an ACM public certificate involves the following steps:

  1. Request a certificate: In the AWS Management Console for ACM, or the AWS Command Line Interface (AWS CLI) or API, initiate a certificate request by specifying the domain names you want to secure (for example, example.com or *.example.com).
  2. Validate domain ownership: ACM requires that you prove control over the domain. If the domain is hosted on Amazon Route 53, you can request that ACM validate the domain ownership. For domains hosted outside AWS, you can use DNS validation (adding a CNAME record) or email validation (responding to emails sent to domain contacts).
  3. Certificate issuance: After the domain ownership has been validated, ACM issues the certificate, which includes the public key, private key, and certificate chain.
  4. Associate the certificate with an integrated AWS service: See Services integrated with ACM for information about associating the certificate with an integrated AWS service.
  5. Export the certificate: With the new capability you can now export the public certificate, private key, and certificate chain using the ACM console, AWS CLI, or API for use on servers that aren’t integrated with ACM.
  6. Bind to application: Install the exported certificate on your server (for example, Apache or NGINX) to enable TLS termination.

With the launch of this new capability, you can now control the future exportability of public certificates that you create in ACM.

To create an exportable public certificate, use the ACM console to create a new public certificate. To get started, choose Request certificate in the ACM console and on the Request public certificate page, under Allow export, select Enable export. If you select Disable export, the private key for this certificate will be disallowed for exporting from ACM, which cannot be changed after certificate issuance.

Figure 1: Request a public certificate and enable export

Figure 1: Request a public certificate and enable export

After creating your certificate with the
Enable export option selected and completing domain ownership validation, you can proceed with the export process, as shown in Figure 2. To export your certificate, select it from the list of certificates, choose
More actions, and select
Export.

Figure 2: Export a certificate

Figure 2: Export a certificate

ACM public certificate renewal

ACM automates the process of certificate renewal, which includes:

  1. Renewal initiation: ACM automatically initiates renewal 60 days before a certificate expires.
  2. Domain revalidation: ACM revalidates domain ownership using the same method as the initial issuance (DNS or email).
  3. Certificate update: Upon successful revalidation, ACM issues a new certificate with the same Amazon Resource Name (ARN) with updated validity dates.
  4. When a certificate is renewed in ACM, the service automatically sends an EventBridge event to notify you that the new certificate is available. If the renewal fails, ACM sends notifications to both the AWS Health Dashboard and EventBridge. To stay informed about these certificate events, you can create EventBridge rules that monitor for specific certificate-related events. You can configure these rules to send notifications to an Amazon Simple Notification Service Amazon (SNS) topic so that interested parties receive timely updates about their certificate status.

New EventBridge schema fields: Following successful ACM certificate renewal, the ACM Certificate Available event now includes an exportable field that indicates with TRUE|FALSE whether the public certificate is ready to be exported.

{
    "version": "0",
    "id": "id", 
    "detail-type": "ACM Certificate Available",
    "source": "aws.acm",
    "account": "account",
    "time": "2019-12-22T18:43:48Z",
    "region": "region",
    "resources": [
        "arn:aws:acm:region:account:certificate/certificate_ID"
    ],
    "detail": {
       “Action” : "ISSUANCE" | "RENEWAL" | "IMPORT" | "REIMPORT",
       "CertificateType" : "AMAZON_ISSUED" | "PRIVATE" | "IMPORTED",    
       "CommonName": "example.com",     
       "DomainValidationMethod" : "EMAIL" | "DNS",    
       "CertificateCreatedDate" : "2019-12-22T18:43:48Z",
       "CertificateExpirationDate" : "2019-12-22T18:43:48Z",
       "DaysToExpiry" : 395,
       "InUse" : TRUE | FALSE,    
       "Exported" : TRUE | FALSE,
       "Exportable" : TRUE | FALSE   <== New     
     }
}
  1. Export and update: You can export the renewed certificate and update it on your servers manually or using EventBridge targets such as AWS Systems Manager Automation documents triggered by EventBridge rules. For more information, see Event bus targets in Amazon EventBridge.

You can use EventBridge rules to monitor specific events and route them to one or more targets (such as Amazon SNS topics, AWS Lambda functions, or other AWS services) for processing. For example, when domain validation fails because of DNS configuration issues, ACM generates an ACM Certificate Renewal Action Required EventBridge event. By creating an EventBridge rule that targets an SNS topic, you can subscribe to receive email alerts and take necessary corrective actions.

Automating deployment of renewed certificates using EventBridge

The certificate renewal process helps make sure that your TLS certificates remain valid without manual intervention, but updating certificates across diverse environments can still require effort. When ACM renews a certificate, it generates an EventBridge event. You can configure EventBridge rules to trigger targets based on this event, such as:

  • Send notifications: Route the event to Amazon SNS to send email or SMS notifications to administrators.
  • Automate certificate deployment: Trigger Lambda functions or Systems Manager Automation documents to retrieve the renewed certificate using the ACM API and update it on your servers.
  • Monitor renewal failures: Configure alerts based on ACM certificate renewal failure events. These events can be directly routed to notification channels to inform you about issues such as domain validation errors.

To set this up, create an EventBridge rule to match the ACM renewal event, specify a target, (such as an SNS topic or Lambda function). This automation minimizes manual intervention, helping to facilitate seamless certificate updates across your infrastructure.

Solution overview

In the section, we describe two workflows. The first demonstrates an automated process for exporting existing ACM public certificates and installing them on target EC2 instances or virtual machines. The second workflow is triggered when public certificates are automatically renewed by ACM when they become available in ACM, followed by updating these certificates on downstream EC2 instances and virtual machines. While this solution uses EC2 instances and virtual machines as the target systems, the same methods can be applied to refresh public certificates at scale across various types of systems.

Prerequisites

  1. To extend this automated public certificate export and update process to:
    1. Register EC2 instances: Follow the instructions in Managing EC2 instances with Systems Manager.
    2. Register on-premises and other cloud environments’ virtual machines: Follow the instructions in Managing nodes in hybrid and multicloud environments with Systems Manager.
  2. Add TargetTagKey tags to EC2 instances and virtual machines where you want to deploy renewed certificates. The automation uses these tags to identify target instances.
  3. The ExportCertificate API requires a certificate passphrase for operation. To maintain security best practices, we recommend storing passwords in encrypted form using password vaults instead of plain text storage. Our implementation uses AWS Secrets Manager to securely store these sensitive credentials. The solution also uses Amazon DynamoDB to maintain certificate metadata, which includes a reference to the corresponding secret name stored in Secrets Manager. For added security, the DynamoDB table’s data is automatically encrypted at rest using AWS Key Management Service (AWS KMS).

ACM certificate export

Figure 3: ACM certificate issuance and export workflow

Figure 3: ACM certificate issuance and export workflow

The workflow shown in Figure 3 demonstrates an automated process for exporting existing public ACM certificates through an API-driven process and deploying them to downstream systems.

  1. The process begins when a user makes a request to an API Gateway endpoint, providing essential parameters including the CertificateArn to identify the certificate you want to export, CertName for certificate identification, and TargetTagKey and TargetTagValue for identifying the target EC2 instances where you want this certificate to be installed. The following is an example of the payload sent to API Gateway:
    {
      "CertificateArn": "arn:aws:acm:us-east-1:1234567890123:certificate/8106d6b2-f204-4354-8893-d49e311b3900",
      "CertName": "academe",
      "TargetTagKey": "env",
      "TargetTagValue": "dev"
    }

  2. Upon receiving the request, API Gateway triggers an AWS Step Functions workflow containing multiple orchestrated states.
  3. The initial state executes a Lambda function named acm-Export, which generates a passphrase for the private key.
  4. The acm-Export lambda function also securely stores the generated passphrase in Secrets Manager and uses the generated passphrase to export the ACM certificate.
  5. After completing the acm-Export function, the Step Functions workflow invokes the Lambda ssm-run function.
  6. This function performs two operations: it checks the certificate’s existence in DynamoDB (which serves as an inventory tracking system) and manages record-keeping. When the function encounters an existing certificateARN, it updates the record with the current CertExpiryDate and LastExportedDate timestamp values. For certificates being exported for the first time, the Lambda function creates a new record in DynamoDB if no matching entry exists. This new record captures the certificate’s metadata, including its details and tracking information. Figure 4 shows how this metadata is structured in a DynamoDB table entry in the console.
Figure 4: Certificate metadata in a DynamoDB table

Figure 4: Certificate metadata in a DynamoDB table

  1. Following the metadata verification step in DynamoDB, the Lambda function also initiates running a custom Systems Manager document called Install-ACMCertificate. This document handles the installation of newly exported public certificates onto specified EC2 instances. The same Systems Manager document can be used for certificate installation or updates onto on-premises servers, providing flexibility in certificate deployment.
  2. When the Systems Manager document execution succeeds, it deploys the newly exported public certificates to EC2 instances matching the TargetTagKey. By default, on Linux servers, certificates are stored in /etc/ssl/certs and /etc/ssl/private, though these paths can be customized in the Systems Manager document.
  3. After successfully running this Systems Manager document, the Step Functions workflow then advances to its next state, which triggers another Lambda function named Statuscheck. This function monitors the execution status of the previously initiated Systems Manager document. The Step Functions workflow concludes its execution after it confirms the successful installation of certificates on the targeted EC2 instances.

ACM certificate renewal and export

Figure 5: ACM certificate and renewal process

Figure 5: ACM certificate and renewal process

When a certificate is within 60 days of expiring, ACM automatically begins the renewal process. When ACM successfully completes a certificate renewal, it generates an
event in EventBridge as shown in the following example:


{
	"version": "0",
	"id": "id", 
	"detail-type": "ACM Certificate Available",
	"source": "aws.acm",
	"account": "account",
	"time": "2019-12-22T18:43:48Z",
	"region": "region",
	"resources": [
	"arn:aws:acm:region:account:certificate/certificate_ID"
	],
	"detail": 
	{
		"Action" : "RENEWAL",
		"CertificateType" : "AMAZON_ISSUED”, 
		"CommonName": "", 
		"DomainValidationMethod" : "DNS", 
		"CertificateCreatedDate" : "2025-05-22T18:43:48Z",
		"CertificateExpirationDate" : "2026-06-23T18:43:48Z",
		"DaysToExpiry" : 395,
		"InUse" : “TRUE”, 
		"Exported" : “TRUE”, 
		}
	}

The workflow illustrated in Figure 5 showcases an automated system for exporting existing public ACM certificates using an API-driven process and deploying them to downstream systems.

  1. The solution uses an EventBridge rule that watches for certificate renewal notifications and triggers the acm-renew Lambda function in response. The function begins its execution by receiving the certificate ARN from the ACM event. Using this ARN as a lookup key, it queries a DynamoDB table to retrieve the associated certificate metadata. From this query, it extracts essential certificate details including the Certificate Name and the TargetTag Key-Value pairs that identify which resources need the updated certificate. These details are needed for the subsequent certificate deployment process and help make sure that the updates are applied to the correct systems.
  2. This information is then formatted into a payload and used to trigger a Step Functions workflow. This Step Functions workflow follows the same process described in the ACM Certificate Export section.
  3. Steps 3 through 9 follow the process described in the ACM Certificate Export section. Upon successful completion of step 9, the Step Functions workflow concludes its execution. At this point, the renewed public certificate has been successfully installed on the targeted EC2 instances, completing the automated certificate export and installation process.

Detailed instructions for downloading the solution, executing it, validating the certificate export, and deploying it to your AWS account are available on GitHub.

Pricing and availability

ACM exportable public certificates are available in AWS commercial Regions, AWS GovCloud (US) Regions, and China Regions and follow a pay-as-you go pricing model, with no upfront commitments. You pay only for the certificates you export. Public certificates for AWS Services integrated with ACM such as ELB, CloudFront, and API Gateway remain available at no additional cost. For detailed pricing, see AWS Certificate Manager pricing.

Conclusion

The ACM exportable public certificates capability empowers customers to secure diverse workloads with a unified, managed certificate solution. By enabling certificate exports for EC2, containers, on-premises servers and other cloud providers, ACM simplifies TLS management, while offering centralized control, automated renewals and cost-effective pricing. Get started today by exploring this feature in the ACM console and streamline your certificate management workflows.

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

Pravin Nair

Pravin Nair

Pravin is a Sr. Security Solutions Architect in Data Protection and Privacy. He helps customers build secure, scalable solutions that support their business needs. He has a background in encryption at rest and in transit, infrastructure security, and privacy.

Santosh Vallurupalli

Santosh Vallurupalli

Santosh is a Sr. Solutions Architect at AWS. Santosh specializes in networking, containers, and migrations and enjoys helping customers in their journey of cloud adoption and building cloud-focused solutions for challenging issues. When not working, he likes traveling, watching Formula1, and watching “The Office” in repeat mode.

Chandan Kundapur

Chandan Kundapur

Chandan is a Principal Technical Product Manager on the AWS Certificate Manager (ACM) team. With close to 20 years of cybersecurity experience, he has a passion for driving the ACM team’s product strategy to help AWS customers identify and secure their resources and endpoints with public and private certificates.

Secure collaboration and file sharing with AWS Wickr

Post Syndicated from Anne Grahn original https://aws.amazon.com/blogs/messaging-and-targeting/secure-collaboration-and-file-sharing-with-aws-wickr/

File sharing has become an integral part of collaboration. However, when security protocols aren’t enforced, businesses expose themselves to the risk of data loss.

Whether you’re exchanging documents with colleagues, sharing information with partners, or transferring sensitive data, unsecure file sharing can lead to unauthorized access and security incidents. Although no organization is completely immune to data loss, the increasing frequency of cyber threats underscores the need for mitigation strategies.

This post highlights how AWS Wickr can help you protect sensitive data and securely share files as part of a balanced approach to security and compliance.

The need to safeguard communications and files

Following the breach of telecommunication networks by a state-sponsored threat actor known as Salt Typhoon, the Cybersecurity and Infrastructure Security Agency (CISA) and the Federal Bureau of Investigation (FBI) advised individuals to start using end-to-end encryption to protect sensitive text and voice communications.

CISA’s Mobile Communications Best Practice Guidance recommends the adoption of “…a free messaging application for secure communications that guarantees end-to-end encryption.” However, as the role of messaging applications in business communication expands, it’s important not to lose sight of recordkeeping and compliance obligations. Although consumer messaging applications can protect data and offer file sharing capabilities, they often lack the administrative controls and data retention features needed to reduce organizational risk.

During RSA Conference 2025 Cryptographer’s Panel, concerns about the recent US government group chat leak were raised. Public-key cryptography pioneer Whitfield Diffie noted that the use of an encrypted consumer messaging application to communicate classified information broke archiving laws. Because some commercial tools use 256-bit Advanced Encryption Standard (AES) encryption, which is strong enough to protect communications, he predicted an increase in the use of consumer applications to protect sensitive information in unapproved ways.

How Wickr can help

Wickr can help you protect communications and files against external threats, and employees that misuse their privileges (either intentionally or unintentionally) and expose sensitive data.

Wickr is a secure messaging and collaboration solution that protects one-to-one and group messaging, voice and video calling, file sharing, screen sharing, and location sharing with end-to-end encryption. Additionally, Wickr provides the data retention and administrative controls needed to help you meet recordkeeping requirements, and manage user and device data remotely. Specialized features help you organize files and control how they’re viewed and downloaded.

Wickr Files provides a dedicated space to access and manage files in conversations. Moderators of Wickr rooms and users in self-moderated group conversations can upload and organize files in folders. Users can toggle between Messages and Files tabs to access relevant content and streamline collaboration.

The new Wickr File Previews feature helps you protect sensitive files and lower the risk of data loss. Wickr network administrators can configure a view-only mode in the Security Groups section of the AWS Management Console for Wickr. Users within these groups will be restricted to only viewing the supported files, and will be unable to download them.

Wickr is available in commercial AWS Regions that include US East (N. Virginia), Canada (Central), Asia Pacific (Malaysia, Singapore, Sydney, and Tokyo), and Europe (Frankfurt, London, Stockholm, and Zurich). It is also available as Department of Defense Cloud Computing Security Requirements Guide Impact Level 5 (DoD CC SRG IL5) and Federal Risk and Authorization Management Program (FedRAMP) High-authorized AWS WickrGov in AWS GovCloud (US-West).

Conclusion

There is no single solution for preventing data loss. However, Wickr facilitates efforts to protect sensitive conversations and files while meeting regulatory requirements. Incorporating Wickr alongside clear policies and awareness training covering messaging apps and secure file sharing can position you to accelerate collaboration, mitigate risks, and drive positive business outcomes.

To learn more and get started, see the following resources:


About the authors

CISPE Data Protection Code of Conduct Public Register now certifies 122 AWS services as adherent

Post Syndicated from Gokhan Akyuz original https://aws.amazon.com/blogs/security/cispe-data-protection-code-of-conduct-public-register-now-certifies-122-aws-services-as-adherent/

We continue to expand the scope of our assurance programs at Amazon Web Services (AWS) and are pleased to announce that 122 services are now certified as adherent to the Cloud Infrastructure Services Providers in Europe (CISPE) Data Protection Code of Conduct. This alignment with the CISPE requirements demonstrates our ongoing commitment to adhere to the heightened expectations for data protection by cloud service providers. AWS customers who use AWS certified services can be confident that their data is processed in adherence with the European Union’s General Data Protection Regulation (GDPR).

The CISPE Code of Conduct is the first pan-European, sector-specific code for cloud infrastructure service providers and received a favorable opinion that it complies with the GDPR. It helps organizations across Europe accelerate the development of GDPR-aligned, cloud-based services for consumers, businesses, and institutions.

The accredited monitoring body EY CertifyPoint evaluated AWS as of May 19, 2025, and successfully audited 112 certified services. AWS added ten additional services to the current scope in May 2025. As of the date of this post, 122 services are in scope of this certification. The Certificate of Compliance that illustrates AWS compliance status is available on the CISPE Public Register. For up-to-date information, including when additional services are added, search the CISPE Public Register by entering AWS as the Seller of Record; or see the AWS CISPE Data Protection Code of Conduct page.

AWS strives to bring additional services into the scope of its compliance programs to help you meet your architectural and regulatory needs. If you have questions or feedback about AWS compliance with CISPE Code, reach out to your AWS account team.

To learn more about our compliance and security programs, see AWS Compliance Programs, AWS General Data Protection Regulation (GDPR) Center, and the EU data protection section of the AWS Cloud Security website. As always, we value your feedback and questions; reach out to the AWS Compliance team through the Contact Us page.

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

Gokhan Akyuz

Gokhan Akyuz

Gokhan is an Audit Program Manager at AWS, based in Amsterdam. He leads security audits, attestations, and certification programs across Europe. He has 18 years of experience in audit and risk management in a wide range of industries. Gokhan is a Certified Information Systems Security Professional (CISSP), Certified Cloud Security Professional (CCSP), and AWS Certified Cloud Practitioner.

How to prioritize security risks using AWS Security Hub exposure findings

Post Syndicated from Shahna Campbell original https://aws.amazon.com/blogs/security/how-to-prioritize-security-risks-using-aws-security-hub-exposure-findings/

At re:Inforce 2025, AWS unveiled an enhanced AWS Security Hub that transforms how organizations prioritize their most critical security issues and respond at scale to protect their cloud environments. In this blog post, we discuss how you can use Security Hub to prioritize these issues with exposure findings. The enhanced Security Hub now uses advanced analytics to automatically correlate, enrich, and prioritize security signals across your cloud environment. Security Hub seamlessly integrates with Amazon GuardDuty, Amazon Inspector, Amazon Macie, and AWS Security Hub Cloud Security Posture Management (CSPM), formerly known as AWS Security Hub. Through these integrations, it provides comprehensive threat detection and vulnerability assessment. This intelligent integration helps organizations quickly identify critical security issues, from potential credential compromises to unintended resource exposures, enabling security teams to focus on what matters most.

What is Security Hub?

Security Hub delivers three key security capabilities to help you strengthen your cloud security posture through a unified cloud security solution:

  • Provides visibility across your organization through centralized management and continuous monitoring.
  • Enriches security signals from services such as Amazon Inspector and AWS Security Hub CSPM to surface active risks specific to your environment, so you can prioritize with confidence and streamline response.
  • Delivers integrated risk analysis by correlating findings from Amazon Inspector, AWS Security Hub CSPM, Amazon Macie, and other AWS services to help identify potential attack paths, surface exploitable vulnerabilities and misconfigurations, and provide actionable remediation guidance.

A top concern for customers is: How do I know where to prioritize response first? Managing large volumes of findings across multiple accounts and regions becomes more challenging when security findings are viewed in isolation, making it difficult to determine true priority and impact. Security Hub solves this by providing context-driven analysis. It surfaces the most critical risks by correlating related vulnerabilities, threats, and misconfigurations to reveal exploitable paths. This can help you make informed decisions about which issues to address first.

With exposure findings, you can prioritize critical security issues and respond at scale. Exposures are based on an analysis of findings and traits from Security Hub CSPM, Amazon Inspector (which scans for vulnerabilities), and Amazon Macie (which discovers and protects sensitive data). They are defined as potential security issues, and they are generated by different exposure traits.

Without automated correlation and enriched signals, security teams can struggle to effectively prioritize issues. For example, a vulnerability that Amazon Inspector detects might become critically important when combined with misconfigurations that Security Hub CSPM identifies. However, manually analyzing relationships across thousands of signals is time-consuming and prone to missing critical security context. Teams often build custom solutions to achieve this, but this approach requires significant analyst time and maintenance, which can cause critical security relationships to be overlooked.

Security Hub reduces this complexity by providing native integration across these AWS services in a unified cloud security center, without the operational overhead of log collection and aggregation. For security teams, this means they can help identify and respond to their most critical exposures before the exposures can lead to business impact, rather than spending valuable time manually piecing together individual security signals. Automated correlation and enriched context can help you make faster, more informed decisions about where to focus your efforts. This ultimately helps protect your cloud environment more effectively.

Exposure findings identify security risks in your environment by providing a comprehensive view of your security posture. These findings enable you to understand and address potential risks. Through this consolidated approach, you can efficiently prioritize your remediation efforts by focusing on the most critical exposure findings first,.

Exposure findings are formatted in the Open Cybersecurity Schema Framework (OCSF) schema, an open-source standard that enables security tools to share data seamlessly. The adoption of OCSF by Security Hub has several advantages. As an open, standardized schema that is part of the Linux Foundation, OCSF enables interoperability across multiple security tools and services, both within and outside of the AWS environment. It provides enhanced data normalization with consistent field naming and categorization, making it more straightforward to integrate with third-party security tools.

Partners who already support or intend to support the OCSF schema to receive findings from Security Hub include companies such as Arctic Wolf; CrowdStrike; DataBee, a Comcast company; Datadog; DTEX Systems; Dynatrace; Fortinet; IBM; Netskope; Orca Security; Rapid7; Securonix; SentinelOne; Splunk, a Cisco Company; Sumo Logic; Tines; Trellix; and Wiz. Additionally, service partners such as Accenture, Caylent, Deloitte, IBM, and Optiv can help you adopt Security Hub and the OCSF schema.

Prioritizing security risks

When you navigate to Security Hub, you will see the summary dashboard, which includes an exposure summary widget, as shown in Figure 1. This widget shows your exposures by severity and frequency. Security Hub assigns each exposure finding a default severity of Critical, High, Medium, or Low. Exposure findings with a severity of Informational are not published.

Security Hub calculates exposure finding severity by analyzing and correlating multiple security traits across AWS services. Instead of evaluating these factors in isolation, Security Hub uses a contextual approach, assigning a severity rating based on how these factors are correlated. For example, a resource with an identified vulnerability might receive a higher severity rating if it’s exploitable from the internet or has access to sensitive data.

Security Hub uses several factors to determine the default severity of an exposure finding:

  • Ease of discovery – The availability of automated tools, such as port scans or internet searches to discover the resource at risk.
  • Ease of exploit – The ease with which a threat actor can exploit the risk. For example, if there are open network paths or misconfigured metadata, a threat actor can more quickly exploit the risk.
  • Likelihood of exploit – Security Hub uses both external signals, such as the Exploit Prediction Scoring System (EPSS)—a data-driven scoring system that estimates the probability of a vulnerability being exploited—and internal threat intelligence to determine the probability that the risk is exploited. This comprehensive approach applies to exposure findings for Amazon Elastic Compute Cloud (EC2) instances and AWS Lambda functions.
  • Awareness – The extent to which the risk is not merely theoretical but has publicly available or automated exploits. This factor applies to exposure findings for EC2 instances and Lambda functions.
  • Impact – The potential harm if the exploit is carried out. For example, an exposure could lead to loss of confidentiality from data exposure, loss of integrity from data corruption, loss of availability, or loss of accountability.

The list of risks in this widget is limited to the eight highest risks with the greatest number of critical findings. If two or more risks have an equal number of critical findings, the list automatically groups those findings behind more recent critical findings.

Figure 1 : Exposure summary widget

Figure 1 : Exposure summary widget

From the widget, you can pivot to the exposure dashboard to see to a pre-filtered view of your exposures for continued analysis of potential security issues. You can filter by severity by selecting the number associated with each severity, view a specific exposure by selecting from the list, or select View all exposure findings to see a dashboard of new exposures that are currently open, as shown in Figure 2.

Figure 2: Exposure dashboard

Figure 2: Exposure dashboard

The exposure console shows findings by their title and ranked by decreasing severity. It’s organized by the filter criteria and grouped by finding title. On the left-hand side, Quick filters provide a fast way to filter through exposures based on severity, the top 10 attributes based on the most common values across your findings, top 10 accounts, and top 10 resource types, as shown in Figure 2. In addition to using filters, you can use the Group by dropdown to group exposure findings by a specific attribute, such as AWS account ID, resource type, or product name.

To review the exposure, expand the findings, as shown in Figure 3 for the correlation of resources, status, attributes, and traits such as software vulnerabilities, misconfigurations, and reachability. These are also referred to as trait types. For a particular exposure finding, a trait can be associated with one or more signals, and a signal can contain one or more indicators.

Figure 3: Exposure findings

Figure 3: Exposure findings

As shown in Figure 3, the Potential Credential Stealing: Internet reachable EC2 instance with administrative instance profile has network-exploitable software vulnerabilities with a high likelihood of exploitation finding indicates that there are misconfigurations, vulnerabilities, and reachability (indication of an open network path to a resource) associated with the instance. To find out more about the signal, select anywhere in the line associated with the risk, and you will see an overview panel, as shown in Figure 4.

Figure 4: Exposure finding overview

Figure 4: Exposure finding overview

This example highlights a critical-severity finding for an internet-reachable EC2 instance with software vulnerabilities in the us-east-1 Region. This visualization is powerful because the Potential attack path diagram helps you see what matters by mapping out how potential threat actors could exploit these vulnerabilities to access your resources. The finding also includes critical metadata such as the resource identifier, creation time, reachability, vulnerability, and misconfigurations.

Using the finding, you can quickly understand complex security relationships, assess risk context, and determine remediation priorities, so you can better protect your workloads in the cloud and make more informed security decisions. To prioritize your security response efforts, you can also set finding severity levels and update status, and export findings in OCSF format.

To understand why an exposure is present, you can select the Traits tab, as shown in Figure 5. This will list traits such as Misconfiguration or Vulnerability. If you select By signal, in the Traits tab, you have a full list of the signals associated with the exposure finding. These signals are the underlying findings that were created from different services, such as Security Hub CSPM and Amazon Inspector, that were correlated together to determine the risk associated with the exposure finding.

Figure 5: Exposure finding traits

Figure 5: Exposure finding traits

If you select the Resources tab, you will see the resources associated with the exposure finding, as shown in Figure 6.

Figure 6: Exposure finding resources

Figure 6: Exposure finding resources

For this example, we have an EC2 instance, but you might have a combination of resources such as an EC2 instance, Amazon Simple Storage Service (Amazon S3) bucket, and AWS Identity and Access Management (IAM) role. This list of resources will help you determine what needs to be remediated in your environment to mitigate the risk attributed to this finding.

Finally, with the Create ticket option, Security Hub helps streamline the incident management process through its native integrations with popular ticketing systems such as Jira and ServiceNow. This integration minimizes the need for manual ticket creation and reduces the time between finding and fixing security issues. Organizations can use a Security Hub Automation Rule to automatically create and track tickets for security findings directly from the Security Hub console, helping to make sure that no critical security exposure goes unaddressed. Integration with these widely-used ticketing systems helps maintain a consistent workflow, enables better tracking of remediation efforts, and improves collaboration between security and operations teams. This can help you make your security operations more efficient by providing a streamlined path from detection to resolution.

Conclusion

The enhanced exposure findings capabilities in Security Hub represent a significant advancement in how organizations can secure their cloud environments. By automatically correlating and analyzing security signals across multiple AWS services, Security Hub helps you prioritize your most critical security issues confidently and respond at scale. The intuitive visualization of potential attack paths, combined with intelligent severity rankings and comprehensive trait analysis, enables security teams to make data-driven decisions about risk prioritization.

Security Hub exposure findings help organizations move from reactive to proactive security postures by:

  • Automatically discovering and evaluating publicly accessible resources
  • Providing clear visibility into security capabilities and configurations
  • Correlating multiple security signals to identify critical risks
  • Delivering actionable remediation guidance
  • Offering intuitive filtering and grouping options for efficient analysis

As cloud environments continue to grow in complexity, exposure findings provide the automation, intelligence, and context needed to stay ahead of potential security issues. This enables security teams to focus their valuable time on addressing the most critical risks first, ultimately helping organizations maintain a stronger security posture across their cloud environment.

Whether you’re managing a small deployment or a large enterprise environment, exposure findings in Security Hub provide the insights needed to effectively protect your AWS workloads and maintain a robust security position in an ever-evolving landscape.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, start a new thread on AWS Security, Identity, and Compliance re:Post or contact AWS Support.

Shahna Campbell

Shahna Campbell

Shahna is a solutions architect at AWS, working within the specialist organization with a focus on security. Previously, Shahna worked within the healthcare field clinically and as an application specialist. Shahna is passionate about cybersecurity and analytics. In her free time, she enjoys hiking, traveling, and spending time with family.

Author

Marshall Jones

Marshall is a Worldwide Security Specialist Solutions Architect at AWS. His background is in AWS consulting and security architecture and focused on a variety of security domains including edge, threat detection, and compliance. Today, he’s focused on helping enterprise AWS customers adopt and operationalize AWS security services to increase security effectiveness and reduce risk.

Kimberly Dickson

Kimberly is a Security Specialist Solutions Architect at AWS based in Singapore. She is passionate about working with customers on technical security solutions that help them build confidence and operate securely in the cloud.

Amazon Linux 2023 achieves FIPS 140-3 validation

Post Syndicated from Mahak Arora original https://aws.amazon.com/blogs/compute/amazon-linux-2023-achieves-fips-140-3-validation/

AWS announced that Amazon Linux 2023 (AL2023) has achieved Federal Information Processing Standards (FIPS) 140-3 Level 1 validation of our cryptographic modules, marking a significant milestone in our commitment to providing secure, compliant operating system options for regulated workloads. FIPS certified modules are particularly important for US and Canadian government workloads, healthcare applications requiring HIPAA compliance, financial services, defense contractors, and other regulated industries. FIPS 140-3, which supersedes FIPS 140-2, represents the latest government security standard for cryptographic modules, jointly validated by the National Institute of Standards and Technology (NIST) and the Canadian Centre for Cyber Security (CCCS) through the Cryptographic Module Validation Program (CMVP). The validation follows the rigorous requirements outlined in the FIPS 140-3 standard and encompasses critical cryptographic modules including the OpenSSL, Linux Kernel Cryptographic API, NSS, GnuTLS, and Libgcrypt.

These modules have been extensively tested to have robust security capabilities such as approved cryptographic algorithms, secure key management, strong entropy generation, and protected memory boundaries. The validation process was conducted by a NIST-accredited lab, and further reviewed by the Cryptographic Module Validation Program (CMVP). Additionally, the certificate details can be verified on the CMVP Active Validation List.

In order to enable FIPS mode on AL2023, customers can refer to our FIPS Mode enablement guide on AL2023. Amazon Linux maintains its compliance information through AWS Compliance Programs portal for FIPS- 140-3 and official NIST Guidelines and Compliance FAQs, for meeting global regulatory requirements. For regular updates and best practices, follow the AWS Security Blog, FIPS related FAQs on Amazon Linux 2 and Amazon Linux 2023 providing detailed configuration steps and operational guidance for regulated environments. You can also reach out to your AWS account team for help finding the resources you need.

If you have questions about this post, contact AWS Support.

Empower AI agents with user context using Amazon Cognito

Post Syndicated from Abrom Douglas original https://aws.amazon.com/blogs/security/empower-ai-agents-with-user-context-using-amazon-cognito/

Amazon Cognito is a managed customer identity and access management (CIAM) service that enables seamless user sign-up and sign-in for web and mobile applications. Through user pools, Amazon Cognito provides a user directory with strong authentication features, including passkeys, federation to external identity providers (IdPs), and OAuth 2.0 flows for secure machine-to-machine (M2M) authorization.

Amazon Cognito issues standard JSON Web Tokens (JWTs) and supports the customization of identity and access tokens for user authentication by using the pre token generation Lambda trigger. Learn more about this in How to customize access tokens in Amazon Cognito user pools. Amazon Cognito has extended token customization capabilities to support access token customization for M2M and the ability to pass metadata from the client during M2M authorization. Application builders can use these two features to support multiple use cases, including customizing access tokens based on unique runtime policies, entitlements, environment, or passed metadata. This can simplify and enrich M2M authentication and authorization scenarios and opens up new possibilities for emerging use cases, such as identity and access management for AI agents.

This post demonstrates how Amazon Cognito enables AI agents to perform authorized actions on behalf of users through user-contextualized access tokens for OAuth 2.0-enabled resource servers. AI agents represent a class of autonomous services that require robust identity management and precise access control, especially when acting on behalf of users. By using the Amazon Cognito client credentials flow with access token customization, you can establish distinct identities for AI agents that carry critical information about their capabilities, scope of access, and intended use cases. This approach provides a foundation for more secure, auditable AI agent operations while maintaining clear boundaries around their authorized activities.

The identity of an AI agent can be represented within Amazon Cognito as an app client. The AI agent obtains an access token (JSON Web Token (JWT)) through an OAuth 2.0 client credentials grant. This JWT can be customized to contain claims that represent the authenticated human user whom the AI agent is acting on behalf of. This token can then be used to authorize access to other services that has established trust with the Amazon Cognito user pool by trusting the issuer and audience of the token. For example, this third-party service could be a claims processor, a travel agency service, or a scheduling service acting on behalf of a user. The focus of this post is on foundational building blocks using Amazon Cognito for AI agents and how to obtain a customized access token with user context.

Solution overview and reference architecture

Looking at an example architecture (Figure 1), a user signs in to a web or mobile application using an Amazon Cognito user pool, and tokens for the user are returned to the client. Here, the application could be a serverless digital assistant using an Amazon Bedrock agent that needs to gather and process data residing in a third-party cross-domain service. The AI agent obtains its own access token by performing an OAuth 2.0 client credentials grant while passing the user’s access token as context using the aws_client_metadata request parameter. The AI agent receives the user contextualized access token and calls an external, third-party, or cross-domain service that trusts the issuer and audience of the AI agent’s access token issued from an Amazon Cognito user pool. The cross-domain service can obtain the JSON Web Key Set (JWKS) to verify the token and extract claims presenting both the AI agent and most importantly, the underlying user. Authorization takes place within the cross-domain service using the claims of the customized access token and for fine-grain authorization, Amazon Verified Permissions is used. See Figure 1 for a detailed flow of this example.

Figure 1: AI agent identity reference architecture

Figure 1: AI agent identity reference architecture

  1. The user navigates to the application through the client.
  2. There is no existing session or token for the user, so the user authentication flow with the Amazon Cognito user pool begins.
  3. After a successful sign-in, Amazon Cognito returns access, ID, and refresh tokens to the client for the user.
  4. As the user interacts with AI agent through the application, the client sends the user’s access token to an Amazon API Gateway endpoint.
  5. The API gateway integrates with the AI agent, which is using an Amazon Bedrock agent. As an example, this can use several AWS Lambda functions interacting with an Amazon Bedrock Knowledge Base or a Retrieval-Augmented Generation (RAG) process.
  6. The AI agent obtains its own access token from an Amazon Cognito user pool using an OAuth 2.0 client credentials grant. The user’s access token, obtained in step 1, is sent with the token request in the aws_client_metadata request parameter.

Note: You can use different Amazon Cognito user pools for user authentication and for agent (machine) authentication. This promotes separation and provides the ability to apply different settings and controls on each user pool if needed to meet security requirements.

  1. Amazon Cognito validates the client ID and secret from the AI agent and invokes the pre token generation Lambda trigger to customize the access token for the AI agent.

Note: Within the pre token generation Lambda trigger, the user’s access token is verified before returning a customized access token to the AI agent using the aws-jwt-verify library.

  1. The customized access token is returned to the AI agent, including custom claims representing the user.
  2. The AI agent, using its own access token, calls the cross-domain service to perform the requested action on behalf of the user. For example, this can be a third-party reservation system or a photo sharing service.
  3. The resource server in the cross-domain service verifies that the access token from the AI agent is valid. The resource server must be pre-configured to trust the user pool that issued the agent access token.
  4. Coarse- and fine-grained authorization can happen either locally in the service code or using Verified Permissions.
  5. A response from the cross-domain service flows back to the AI agent, if necessary.
  6. A response from the AI agent to the user application or client is returned, if necessary.
  7. Actions that take place throughout the flow are logged in AWS CloudTrail, providing end-to-end logging and auditing.

Implementation details

Let’s take a deeper look into the three core components of this scenario:

  1. The AI agent obtaining its own OAuth 2.0 access token
  2. The Amazon Cognito pre token generation Lambda trigger used to enrich the AI agent’s access token with user context
  3. The cross-domain resource server performing fine-grained authorization

AI agent

Figure 2: AI agent obtaining a user access token from the frontend application through API Gateway

Figure 2: AI agent obtaining a user access token from the frontend application through API Gateway


Amazon Bedrock Agents is used in this solution with a
custom orchestration configured to use Lambda. When the application interacts with the Amazon Bedrock agent, the custom orchestrator initiation begins with the agent passing the user’s access token to a Lambda function as part of the custom orchestration (shown in Figure 2). The Lambda function validates the user’s token to verify that it’s not expired and hasn’t been tampered with. This custom orchestrator begins the process for the agent to obtain its own OAuth access token and to access downstream and cross-domain resources on behalf of the user. The human user’s access token is included in the call from the application through the client. To learn more about Amazon Bedrock Agents custom orchestrator, see
Getting started with Amazon Bedrock Agents custom orchestrator. The following is an example of what a human user’s decoded access token provided through an API Gateway REST API might look like.

{
  sub: "user-identity-4e4c-example-7cede8e609a2",
  cognito:groups: 
    [
    "exampleChatApplicationAccess"
    ]
  ,
  iss: https://cognito-idp.<region>.amazonaws.com/<region>_example,
  version: 2,
  client_id: "1example23456789",
  origin_jti: "",
  token_use: "access",
  scope: "openid profile email",
  auth_time: 499192140,
  exp: 1445444940,
  iat: 499192140,
  jti: "",
  username: "my-example-username"
}

The following is a Node.js code sample that an AI agent can use to obtain its own access token from Amazon Cognito. This can be the Lambda function part of the custom orchestration for the Amazon Bedrock agent. Notice the clientMetadata variable being set, which will be passed to the Cognito /token endpoint using the aws_client_metadata request parameter. This request parameter is where the user’s access token is provided. In the following code example, you will find an attribute called callerApp, which is set to ExampleChatApplication, which serves as a unique identifier for the application. The callerApp value is preconfigured in the backend of the solution. This unique application identifier is included in the customized access token for the agent and used for additional authorization checks later. It’s a security best practice to use AWS Secrets Manager to store the client ID and client secret and obtain these credentials at runtime. As a security best practice, the user’s access token should be verified prior to passing it to the AI agent backend.

async function getAccessToken() {
    const clientId = 'exampleAiAgentClientId'; // use Secrets Manager
    const clientSecret = 'exampleAiAgentClientSecret'; // use Secrets Manager
    const tokenEndpoint = 'https://mydomain.auth.<region>.amazoncognito.com/oauth2/token';
    const scope = 'crossDomainService/read userData/read';
    const clientMetadata = '{"onBehalfOfToken":"<HUMAN-USER-ACCESS-TOKEN>", "callerApp":"ExampleChatApplication"}';
  
    const basicAuth = Buffer.from(`${clientId}:${clientSecret}`).toString('base64');
  
    const body = new URLSearchParams({
      grant_type: 'client_credentials',
      scope,
      aws_client_metadata: clientMetadata
    });
  
    const res = await fetch(tokenEndpoint, {
      method: 'POST',
      headers: {
        'Authorization': `Basic ${basicAuth}`,
        'Content-Type': 'application/x-www-form-urlencoded'
      },
      body
    });
  
    if (!res.ok) {
      const error = await res.text();
      throw new Error(`Token request failed: ${res.status} ${error}`);
    }
  
    const { access_token } = await res.json();
    console.log('Access Token:', access_token);
  
    return access_token;
  }
  
  getAccessToken().catch(err => console.error('Error:', err.message));

The access token for the AI agent is returned only if the client ID and secret are correct and the provided user access token is valid. However, before it’s returned, the AI agent’s access token is customized by the Amazon Cognito pre token generation Lambda trigger.

Amazon Cognito pre token generation Lambda trigger

Figure 3: AI agent access token customization with Cognito pre token generation Lambda trigger

Figure 3: AI agent access token customization with Cognito pre token generation Lambda trigger

After the AI agent’s action calls the Amazon Cognito /token endpoint with a valid client ID and secret, Cognito invokes the pre token generation Lambda trigger. The following is an example Lambda function that takes the aws_client_metadata request parameter, which contains the access token of the user and the callerApp attribute that was defined while the user was authenticating. In the following Lambda function, the access token provided from the user is verified (shown in Figure 3). The aws-jwt-verify library is used to verify the token is not expired, the token has not been tampered with by verifying the signature, and it’s making sure that an access token was provided. The Lambda function is also pre-configured to accept user tokens from a specific issuer and audience, this protects against malicious context injection risks. This is also an opportunity to perform additional authorization. For example, check if the user is a member of certain groups.

After the token is verified, the Lambda function customizes the access token to be returned to the AI agent.

import { CognitoJwtVerifier } from "aws-jwt-verify";

// Initialize the JWT verifier to verify the user’s access token
// Provide the user pool ID, token use, and client ID 
const jwtVerifier = CognitoJwtVerifier.create({
  userPoolId: process.env.USER_POOL_ID,  // user pool for user authentication
  clientId: process.env.CLIENT_ID,
  // groups: "exampleChatApplicationAccess", // optional group membership authorization
  tokenUse: 'access'
});

export const handler = async function(event, context) {
  try {
    const onBehalfOfToken = event.request.clientMetadata?.onBehalfOfToken || '';
    // It’s recommended that the provided “callerApp” value from the application is authorized for use with the app client for the AI agent
    const callerApp = event.request.clientMetadata?.callerApp || '';

    // The below console log will display the authenticated user’s JWT
    // Keep this logging with caution in a production environment
    console.log('Original event:', event);

    // Verify the access token from the human user
    // You could optionally also perform some authorization checks here as well
    // Example: check for the membership of a group
    let decodedJWT;
    if (onBehalfOfToken) {
      try {
        decodedJWT = await jwtVerifier.verify(onBehalfOfToken);
        console.log('Decoded JWT:', decodedJWT);
      } catch (err) {
        console.error('Token verification failed:', err);
        throw new Error('Token verification failed');
      }
    }

    // Create the onBehalfOf claim structure
    const behalfOfClaim = decodedJWT ? {
      sub: decodedJWT.sub,
      username: decodedJWT.username,
      groups: decodedJWT['cognito:groups'] || []
    } : {};

    // Customized token returned to client
    event.response = {
      "claimsAndScopeOverrideDetails": {
        "accessTokenGeneration": {
          "claimsToAddOrOverride": {
            "onBehalfOf": behalfOfClaim,
            "callerApp": callerApp
          },
        }
      }
    };

    return event;

  } catch (error) {
    console.error('Error in Lambda execution:', error);
    throw error;
  }
};

Notice in the preceding Lambda function that two custom claims are being dynamically created within the event.response: onBehalfOf and callerApp. The onBehalfOf claim contains nested claims that were extracted from the human user’s access token. The callerApp is carried forward from the frontend application and provided alongside the user access token. It’s recommended for the callerApp value to also be verified against some custom logic to add additional layer of protection. The return AI agent’s access token would look like the following JWT.


{    
	"sub": "agent-identity-4e4c-example-7cede8e609a2",
	"onBehalfOf": {
		"sub": "user-identity-4e4c-example-7cede8e609a2",
		"username": "my-example-username",
		"groups": [
			"readaccess"        
				]    
		},    
		"iss": "https://cognito-idp..amazonaws.com/_example",
		"version": 2,
		"client_id": "1example23456789",
		"callerApp": "ExampleChatApplication",
		"token_use": "access",
		"scope": "crossDomainService123/read userData/read",
		"auth_time": 499192140,
		"exp": 1445444940,
		"iat": 499192140,
		"jti": "aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee"
}

Cross-domain resource server authorization check

At this point, shown in Figure 4, the human user has successfully authenticated to the web application, the human user’s access token was sent as context to the backend, an AI agent obtained its own customized access token containing the human user context, and now the agent is ready to call an external cross-domain service.

Figure 4: Cross-domain resource server performing fine-grained authorization with Amazon Verified Permissions

Figure 4: Cross-domain resource server performing fine-grained authorization with Amazon Verified Permissions

As shown in Figure 4, the cross-domain service is the resource server and therefore needs to perform an authorization check. For this example, we’ll keep things straightforward and make sure that three core things are verified:

  1. The AI agent’s OAuth access token is valid
  2. The AI agent is authorized to access this service
  3. The AI agent is authorized to interact with the user data

Depending on your use case and requirements, you might also need to verify that the user’s consent has been obtained prior to the AI agent acting on their behalf. Ultimately, you want to verify that the AI agent can access a user’s data on their behalf and only for the purpose for which consent has been provided by the user.

For the token verification, use the aws-jwt-verify library again. The following is a Node.js example to verify the AI agent’s access token.

import { CognitoJwtVerifier } from "aws-jwt-verify";

// add custom logic to verify that AI agent is authorized to perform this action on behalf of the user

// Verifier that expects valid access tokens:
const verifier = CognitoJwtVerifier.create({
  userPoolId: "<user_pool_id>", // user pool for AI agent authentication
  tokenUse: "access",
  clientId: "<client_id>",
});

try {
  const payload = await verifier.verify(
    "eyJraWQeyJhdF9oYXNoIjoidk..." //this will be the AI agent's access token
  );
  console.log("Token is valid. Payload:", payload);
} catch {
  console.log("Token not valid!");
}

Fine-grained authorization with Verified Permissions

As a security best practice, the zero trust principle of enforcing fine-grained identity-based authorization should take place using Verified Permissions. The preceding Node.js code sample is a basic validation of the AI agents access token that can happen within the application logic. Instead of keeping authorization logic within the resource server, you can use Verified Permissions to offload the authorization policies to a managed service. The following is an example Cedar policy for this use case.

permit(
    principal == Agent::"agent-identity-4e4c-example-7cede8e609a2",
    action == Action::"readOnly",
    resource == Resource::"crossDomainService123::userData"
)
when {
    resource.scope == Scope::"crossDomainService123/read" &&
    resource.owner == User::" user-identity-4e4c-example-7cede8e609a2" &&
    context.onBehalfOf.sub == " user-identity-4e4c-example-7cede8e609a2" &&
    context.callerApp == "ExampleChatApplication"
};

With the preceding Cedar policy example, you are permitting the AI agent to read userData from the crossDomainService123 resource. This is only permitted when the AI agent’s access token contains the crossDomainService/read scope and when the resource owner and the onBehalfOf user (from the access token) are the same—the human user in this case. There’s also an additional when clause in the policy to make sure that this interaction initiated from ExampleChatApplication.

The cross-domain resource server would use the AI agent’s access token and call the Verified Permissions IsAuthorizedWithToken API. To learn more, see Simplify fine-grained authorization with Amazon Verified Permissions and Amazon Cognito.

The following is a Node.js example using the IsAuthorizedWithToken API from Verified Permissions using the AWS SDK for JavaScript v3.

import { VerifiedPermissionsClient, IsAuthorizedWithTokenCommand } from "@aws-sdk/client-verifiedpermissions";

const client = new VerifiedPermissionsClient({ region: "<region>" });

// Dynamically provided token 
const jwtToken = "eyJraWQiOiJrMWtleSIsInR..."; //AI agent's access token

async function checkAccess() {
  const input = {
    policyStoreId: "ps-abc123example", // your AVP policy store ID
    accessToken: jwtToken,
    action: {
      actionType: "Action",
      actionId: "readOnly"
    },
    resource: {
      entityType: "crossDomainService123",
      entityId: "userData"
    }
  };

  const command = new IsAuthorizedWithTokenCommand(input);

  try {
    const response = await client.send(command);
    console.log("Authorization Decision:", response.decision);
  } catch (err) {
    console.error("Authorization error:", err);
  }
}

Based on the preceding examples of the AI agent’s access token (with user context), the Cedar policy, and the IsAuthorizedWithToken API call, the resource server would get an Allow decision for this action to take place. The following is an example of the authorization decision response.

{
    "decision": "Allow",
    "determiningPolicies": [{
        "determiningPolicyId": "ps-abc123example"
    }],
    "errors": []
}

Before this policy can be evaluated, you must define a schema that includes the relevant entity types (Agent, User, Resource, Scope, and so on), and create corresponding entities in your policy store that match the IDs used in the policy and request.

Bringing it all together, the requested data from the AI agent, on behalf of the user, is returned from the cross-domain service to the AI agent. This additional data can now be used within the context of the AI agent workload. The entire solution can be used for a chat application, such as the one described in Protect sensitive data in RAG applications with Amazon Bedrock.

Conclusion

Amazon Cognito M2M access token customization and support for passing client metadata provides you the extensibility to solve complex use cases and enables emerging ones like AI agent identity and access management. For example, passing contextual client metadata and customizing access tokens at runtime can help software as a service (SaaS) and multi-tenant service providers scale to an unlimited number of resource servers, because these can be dynamically determined at runtime. As organizations increasingly explore the use of AI agents, having a secure, scalable identity management solution becomes crucial for maintaining control and accountability. By using these new features, you can build more secure and scalable solutions with Amazon Cognito to prepare for the future of autonomous AI agent use cases.

Use the comments section to leave feedback about this post. If you have questions about this post, start a new thread on Amazon Cognito re:Post or contact AWS Support.

Abrom Douglas

Abrom Douglas III

Abrom is a Senior Solutions Architect within AWS Identity with nearly 20 years of software engineering and security experience, specializing in the identity and access management space. He loves speaking with customers about how identity and access management can provide secure outcomes that enable both business and technology initiatives. In his free time, he enjoys cheering for Arsenal FC, photography, travel, volunteering, and competing in duathlons.

Amazon GuardDuty expands Extended Threat Detection coverage to Amazon EKS clusters

Post Syndicated from Esra Kayabali original https://aws.amazon.com/blogs/aws/amazon-guardduty-expands-extended-threat-detection-coverage-to-amazon-eks-clusters/

Today, I’m happy to announce Amazon GuardDuty Extended Threat Detection with expanded coverage for Amazon Elastic Kubernetes Service (Amazon EKS), building upon the capabilities we introduced in our AWS re:Invent 2024 announcement of Amazon GuardDuty Extended Threat Detection: AI/ML attack sequence identification for enhanced cloud security.

Security teams managing Kubernetes workloads often struggle to detect sophisticated multistage attacks that target containerized applications. These attacks can involve container exploitation, privilege escalation, and unauthorized movement within Amazon EKS clusters. Traditional monitoring approaches might detect individual suspicious events, but often miss the broader attack pattern that spans across these different data sources and time periods.

GuardDuty Extended Threat Detection introduces a new critical severity finding type, which automatically correlates security signals across Amazon EKS audit logs, runtime behaviors of processes associated with EKS clusters, malware execution in EKS clusters, and AWS API activity to identify sophisticated attack patterns that might otherwise go unnoticed. For example, GuardDuty can now detect attack sequences in which a threat actor exploits a container application, obtains privileged service account tokens, and then uses these elevated privileges to access sensitive Kubernetes secrets or AWS resources.

This new capability uses GuardDuty correlation algorithms to observe and identify sequences of actions that indicate potential compromise. It evaluates findings across protection plans and other signal sources to identify common and emerging attack patterns. For each attack sequence detected, GuardDuty provides comprehensive details, including potentially impacted resources, timeline of events, actors involved, and indicators used to detect the sequence. The findings also map observed activities to MITRE ATT&CK® tactics and techniques and remediation recommendations based on AWS best practices, helping security teams understand the nature of the threat.

To enable Extended Threat Detection for EKS, you need at least one of these features enabled: EKS Protection or Runtime Monitoring. For maximum detection coverage, we recommend enabling both to enhance detection capabilities. EKS Protection monitors control plane activities through audit logs, and Runtime Monitoring observes behaviors within containers. Together, they create a complete view of your EKS clusters, enabling GuardDuty to detect complex attack patterns.

How it works
To use the new Amazon GuardDuty Extended Threat Detection for EKS clusters, go to the GuardDuty console to enable EKS Protection in your account. From the Region selector in the upper-right corner, select the Region where you want to enable EKS Protection. In the navigation pane, choose EKS Protection. On the EKS Protection page, review the current status and choose Enable. Select Confirm to save your selection.

After it’s enabled, GuardDuty immediately starts monitoring EKS audit logs from your EKS clusters without requiring any additional configuration. GuardDuty consumes these audit logs directly from the EKS control plane through an independent stream, which doesn’t affect any existing logging configurations. For multi-account environments, only the delegated GuardDuty administrator account can enable or disable EKS Protection for member accounts and configure auto-enable settings for new accounts joining the organization.

To enable Runtime Monitoring, choose Runtime Monitoring in the navigation pane. Under the Configuration tab, choose Enable to enable Runtime Monitoring for your account.

Now, you can view from the Summary dashboard the attack sequences and critical findings specifically related to Kubernetes cluster compromise. You can observe that GuardDuty identifies complex attack patterns in Kubernetes environments, such as credential compromise events and suspicious activities within EKS clusters. The visual representation of findings by severity, resource impact, and attack types gives you a holistic view of your Amazon EKS security posture. This means you can prioritize the most critical threats to your containerized workloads.

The Finding details page provides visibility into complex attack sequences targeting EKS clusters, helping you understand the full scope of potential compromises. GuardDuty correlates signals into a timeline, mapping observed behaviors to MITRE ATT&CK® tactics and techniques such as account manipulation, resource hijacking, and privilege escalation. This granular level of insight reveals exactly how attackers progress through your Amazon EKS environment. It identifies affected resources like EKS workloads and service accounts. The detailed breakdown of indicators, actors, and endpoints provides you with actionable context to understand attack patterns, determine impact, and prioritize remediation efforts. By consolidating these security insights into a cohesive view, you can quickly assess the severity of Amazon EKS security incidents, reduce investigation time, and implement targeted countermeasures to protect your containerized applications.

The Resources section of the Finding details page shows context about the specific assets affected during an attack sequence. This unified resource list provides you with visibility into the exact scope of the compromise—from the initial access to the targeted Kubernetes components. Because GuardDuty includes detailed attributes such as resource types, identifiers, creation dates, and namespace information, you can rapidly assess which components of your containerized infrastructure require immediate attention. This focused approach eliminates guesswork during incident response, so you can prioritize remediation efforts on the most critical affected resources and minimize the potential blast radius of Amazon EKS targeted attacks.

Now available
Amazon GuardDuty Extended Threat Detection with expanded coverage for Amazon EKS clusters provides comprehensive security monitoring across your Kubernetes environment. You can use this capability to detect sophisticated multistage attacks by correlating events across different data sources, identifying attack sequences that traditional monitoring might miss.

To start using this expanded coverage, enable EKS Protection in your GuardDuty settings and consider adding Runtime Monitoring for enhanced detection capabilities.

For more information about this new capability, refer to the Amazon GuardDuty Documentation.

— Esra

Secure your Express application APIs in minutes with Amazon Verified Permissions

Post Syndicated from Trevor Schiavone original https://aws.amazon.com/blogs/security/secure-your-express-application-apis-in-minutes-with-amazon-verified-permissions/

Today, Amazon Verified Permissions announced the release of @verifiedpermissions/authorization-clients-js, an open source package that developers can use to implement external fine-grained authorization for Express.js web application APIs in minutes when using Verified Permissions.

Express is a minimal and flexible Node.js web application framework that provides a robust set of features for web and mobile applications. By using this standardized integration with Verified Permissions, developers can externalize authorization using up to 90 percent less code compared to writing their own custom integrations, saving them time and effort and improving application security posture by reducing the amount of custom integration code.

Why externalize authorization?

Traditionally, developers implemented authorization within their application by embedding authorization logic directly into application code. This embedded authorization logic is designed to support a few permissions, but as applications evolve, there is often a need to incrementally update the embedded authorization logic to support more complex use cases, resulting in code that is complex and difficult to maintain. As code complexity increases, further evolving the security model and performing audits of permissions becomes more challenging, resulting in an application that becomes more difficult to maintain over its lifecycle.

By externalizing authorization, you can decouple authorization logic from your application. This yields multiple benefits including freeing up development teams to focus on application logic and simplifying software audits.

One approach to externalize authorization from your application code is to use Cedar. Cedar is an open source language and software development kit (SDK) for writing and enforcing authorization policies for your applications. You specify fine-grained permissions as Cedar policies, and your application authorizes access requests by calling the Cedar SDK. For example, if you’re building a pet store application, you can use the following Cedar policy to control that only a user with a jobLevel of employee can access the POST /pets API.


permit (
	principal,
	action in [Action::"POST /pets"], 
	resource
) when {
	principal.jobLevel = "employee"
};

One option for using Cedar is to self-manage the implementation; you can find an example for this pattern in another post: Secure your application APIs in 5 minutes with Cedar.

Self-managed Cedar provides the benefits of externalizing authorization but requires ongoing operational management. Organizations are responsible for Cedar version upgrades, applying security patches, managing policies, and auditing authorizations. Another option for using Cedar is to use Verified Permissions. Verified Permissions removes these operational requirements by providing a managed service for Cedar. Verified Permissions manages scaling, simplifies policy governance by supporting centralized policy management, and logs policy changes and authorization requests to simplify auditing.

This post describes how web application developers can use the new Express package to simplify the integration of Express web applications with Verified Permissions. The step-by-step guide uses a sample Pet Store application to show how access to APIs can be restricted based on user groups. You can find the sample Pet Store application in the verifiedpermissions repository on GitHub.

Pet Store application API overview

The Pet Store application is used to manage a pet store. The pet store is built using Express with Node.js and exposes the APIs in the following table.

API Description
GET /api/pets Returns the list of available pets
GET /api/pets/{petId} Returns the specified pet found
POST /api/pets Adds a pet to the pet store
PUT /api/pets/{petId} Updates an existing pet
DELETE /api/pets/{petId} Removes a pet from the pet store

This application doesn’t allow all users to access all APIs. Instead, it enforces the following rules:

  • Administrators: Full access to pets and management functions
  • Employees: Can view, create, and update pets
  • Customers: Can view pets and create new pets

Implementing authorization for the Pet Store APIs

Let’s walk through how to secure your application APIs using Verified Permissions and the new package for Express. The initial application, with no authorization, can be found in the start folder; use this to follow along with the post. You can find a completed version of the application in the finish folder.

When completed, you’ll have implemented the application architecture shown in Figure 1. A React frontend application that uses Amazon Cognito for authentication. The application then includes the identity token returned from Cognito as an authorization header to the Express backend APIs. The Express backend, using the new Verified Permissions authorization middleware package, calls Verified Permissions to authorize the user request.

Figure 1: Architecture of the Pet Store application

Figure 1: Architecture of the Pet Store application

Prerequisites

Before you get started, make sure you have the following prerequisites in place.

Step 1: Set up the AWS CLI

Some of the commands require the AWS Command Line Interface (AWS CLI). See Installing or updating to the latest version of the AWS CLI and Configuring settings for the AWS CLI.

Step 2: Set up an OpenID Connect identity provider and a database

The Pet Store application uses an OpenID Connect (OIDC) identity provider to manage users. For this example, you use an Amazon Cognito user pool called PetStoreUserPool with three users, one Admin, one Employee, and one Customer.

The application also uses a Amazon DynamoDB database to store the pets.

You can set up Amazon Cognito and DynamoDB in your AWS account by running the following command in the /start directory.

./scripts/setup-infrastructure.sh

The setup script will prompt you to set passwords for the three users (passwords must be at least 8 characters and require at least one number, one uppercase letter, and one lowercase letter).

Note the outputs of running this script because you’ll use them in step 5 of Integrate Verified Permissions.

Note: In your own applications, you can set up Amazon Cognito by following the instructions in Create a new application in the Amazon Cognito console, or you can bring your own OIDC identity provider.

Step 3 (optional): Run the application

Now that the infrastructure is set up, you can run the application. In two separate terminals, run the following commands in the /start directory:

./scripts/run-backend-dev.sh
./scripts/run-frontend-dev.sh

Test the application by creating some pets.

Integrate Verified Permissions

With the prerequisites in place, the next step is to integrate Verified Permissions. Verified Permissions can be integrated into an Express application in six steps:

  1. Create a Verified Permissions policy store
  2. Add the Cedar and Verified Permissions authorization middleware packages
  3. Create and deploy a Cedar schema
  4. Create and deploy Cedar policies
  5. Connect the Verified Permissions policy store to your OIDC identity provider
  6. Update the application code to call Verified Permissions to authorize API access

The Verified Permissions integration happens with the Express web application backend. All commands in the section should be run in the /start/backend directory.

Step 1: Create a Verified Permissions policy store 

  1. Create a policy store in Verified Permissions using the AWS CLI by running the following command
    aws verifiedpermissions create-policy-store  --validation-settings "mode=STRICT"
    

    Example successful command output:

    {
        "policyStoreId": "AAAAbbbbCCCCdddd",
        "arn": "arn:aws:verifiedpermissions::111122223333:policy-store/AAAAbbbbCCCCdddd",
        "createdDate": "2025-06-05T19:30:37.896119+00:00",
        "lastUpdatedDate": "2025-06-05T19:30:37.896119+00:00"
    }
    

  2. Save the policyStoreId value from the command output to use in step 3.

Step 2: Add the Cedar and Verified Permissions authorization middleware packages

  • Run the following command to add two new dependencies on @verifiedpermissions/authorization-clients and @cedar-policy/authorization-for-expressjs
    npm i --save @verifiedpermissions/authorization-clients
    npm i --save @cedar-policy/authorization-for-expressjs
    

Step 3: Create and deploy the Cedar schema 

A Cedar schema defines the authorization model for an application, including the entity types in the application and the actions users are allowed to take. You attach your schema to your Verified Permissions policy stores, and when policies are added or modified, the service automatically validates the policies against the schema.

The @cedar-policy/authorization-for-expressjs package can analyze the OpenAPI specification of your application and generate a Cedar schema. Specifically, the paths object in the OpenAPI schema is required in your specification.

If you don’t have an OpenAPI spec, you can generate one using the tool of your choice. There are several open source libraries that you can use to do this for Express; you might need to add some code to your application, generate the OpenAPI spec, and then remove the code. Alternatively, some generative AI based tools such as the Amazon Q Developer CLI are effective at generating OpenAPI spec documents. Regardless of how you generate the spec, be sure to validate the correct output from the tool.

For the sample application an OpenAPI spec document has been included and is named openapi.json.

  1. Run the following command to generate the Cedar schema.
    npx @cedar-policy/authorization-for-expressjs generate-schema --api-spec schemas/openapi.json --namespace PetStoreApp --mapping-type SimpleRest
    

    Example successful command output:

    Cedar schema successfully generated. Your schema files are named: v2.cedarschema.json, v4.cedarschema.json.
    v2.cedarschema.json is compatible with Cedar 2.x and 3.x
    v4.cedarschema.json is compatible with Cedar 4.x and required by the nodejs Cedar plugins.
    

  2. Next, format the Cedar schema for use with the AWS CLI. The specific format required is described in the documentation Amazon Verified Permissions policy store schema. To format the Cedar schema run the following command.
    ../scripts/prepare-cedar-schema.sh v2.cedarschema.json v2.cedarschema.forAVP.json
    

    Example successful command output:

    Cedar schema prepared successfully: v2.cedarschema.forAVP.json
    You can now use it with AWS CLI:
    

  3. After the schema is formatted, run the following command to upload the schema to Verified Permissions. Note that you need to replace <policy store id> with the actual policy store ID, which is provided as an output from the command in step 1.
    aws verifiedpermissions put-schema --definition file://v2.cedarschema.forAVP.json --policy-store-id <policy store id>
    

    Example successful command output:

    {
        "policyStoreId": "AAAAbbbbCCCCdddd",
        "namespaces": [
            "PetStoreApp"
        ],
        "createdDate": "2025-06-03T20:19:33.480528+00:00",
        "lastUpdatedDate": "2025-06-05T19:42:45.198325+00:00"
    }
    

Step 4: Create and deploy Cedar policies

If no policies are configured, Cedar denies authorization requests. The next step is to create policies that will allow specific user groups access to specific resources. The Express framework integration helps bootstrap this process by generating example policies based on the previously generated schema. You can then then customize these policies based on your use cases.

  1. Run the following command to generate sample Cedar policies.
    npx @cedar-policy/authorization-for-expressjs generate-policies --schema v2.cedarschema.json
    

    Example successful command output:

    Cedar policy successfully generated in policies/policy_1.cedar
    Cedar policy successfully generated in policies/policy_2.cedar
    

    Two sample policies are generated in the /policies directory: policy_1.cedar and policy_2.cedar.

    policy_1.cedar provides permissions for users in the admin user group to perform any action on any resource.

    
    // policy_1.cedar
    // Allows admin usergroup access to everything
    permit (
    	principal in PetStoreApp::UserGroup::"admin",
    	action,
    	resource
    );
    

    policy_2.cedar provides more access to the individual actions defined in the Cedar schema with a place holder for a specific group.

    // policy_2.cedar
    // Allows more granular user group control, change actions as needed
    permit (
        principal in PetStoreApp::UserGroup::"ENTER_THE_USER_GROUP_HERE",
        action in
            [PetStoreApp::Action::"GET /pets",
             PetStoreApp::Action::"POST /pets",
             PetStoreApp::Action::"GET /pets/{petId}",
             PetStoreApp::Action::"PUT /pets/{petId}",
             PetStoreApp::Action::"DELETE /pets/{petId}"],
        resource
    );
    

    Note that if you specified an operationId in the OpenAPI specification, the action names defined in the Cedar Schema will use that operationId instead of the default <HTTP Method> /<PATH> format. In this case, make sure that the naming of your actions in your Cedar policies matches the naming of your actions in your Cedar schema.

    For example, if you want to call your action AddPet instead of POST /pets, you could set the operationId in your OpenAPI specification to AddPet. The resulting action in the Cedar policy would be PetStoreApp::Action::"AddPet"

    Create a third policy file called policy_3.cedar and then replace the contents of each file with the following policies. Replace <userpoolId> in each policy with the Cognito User Pool Id copied earlier.

    Note: In a real use case, consider renaming your Cedar policy files based on their contents, for example, allow_customer_group.cedar.

    // Defines permitted administrator user group actions
    permit (
        principal in PetStoreApp::UserGroup::"<userPoolId>|administrator",
        action,
        resource
    );
    

    // Defines permitted employee user group actions
    permit (
        principal in PetStoreApp::UserGroup::"<userPoolId>|employee",
        action in
            [PetStoreApp::Action::"GET /pets",
             PetStoreApp::Action::"POST /pets",
             PetStoreApp::Action::"GET /pets/{petId}",
             PetStoreApp::Action::"PUT /pets/{petId}"],
        resource
    );
    

    // Defines permitted customer user group actions
    permit (
        principal in PetStoreApp::UserGroup::"<userPoolId>|customer",
        action in
            [PetStoreApp::Action::"GET /pets",
             PetStoreApp::Action::"POST /pets",
             PetStoreApp::Action::"GET /pets/{petId}"],
        resource
    );
    

  2. The policies need to be formatted so that they work with the AWS CLI for Verified Permissions. The specific format is described in the AWS CLI Verified Permissions documentation. Run the following command to format the policies.
    ../scripts/convert_cedar_policies.sh
    

    Example successful command output:

    Converting policies/policy_1.cedar to policies/json/policy_1.json
    Created policies/json/policy_1.json
    Converting policies/policy_2.cedar to policies/json/policy_2.json
    Created policies/json/policy_2.json
    Converting policies/policy_3.cedar to policies/json/policy_3.json
    Created policies/json/policy_3.json
    Conversion complete. JSON policy files are in ../policies/json/
    

    The formatted policies will be output to the backend/policies/json/ directory.

  3. After formatting the policies, run the following three commands, one for each policy, to upload them to Verified Permissions. The policy store ID is returned after completing step 2. Replace <policy store id> with the actual policy store ID.
    aws verifiedpermissions create-policy  --definition file://policies/json/policy_1.json --policy-store-id <policy store id>
    aws verifiedpermissions create-policy  --definition file://policies/json/policy_2.json --policy-store-id <policy store id>
    aws verifiedpermissions create-policy  --definition file://policies/json/policy_3.json --policy-store-id <policy store id>
    

    Example successful command output:

    {
        "policyStoreId": "AAAAbbbbCCCCdddd",
        "policyId": "8AmzZYMw6Ux5DGBoX7w24m",
        "policyType": "STATIC",
        "principal": {
            "entityType": "PetStoreApp::UserGroup",
            "entityId": "<userPoolId>|administrator"
        },
        "createdDate": "2025-06-05T19:46:45.848602+00:00",
        "lastUpdatedDate": "2025-06-05T19:46:45.848602+00:00",
        "effect": "Permit"
    }
    

Alternatively, you can also copy and paste Cedar policies into Verified Permissions in the AWS Management Console.

Step 5: Connect the Verified Permissions policy store to your OIDC identity provider

By default, the Verified Permissions authorizer middleware reads a JSON Web Token (JWT) provided within the authorizationheader of the API request to get user information. Verified Permissions can validate the token in addition to performing authorization policy evaluation.

  1. To do this, create an identity source in Verified Permissions policy store. To simplify formatting in the AWS CLI command, we’ve defined the identity source configuration in identity-source-configuration.txtReplace the <userPoolArn> and <clientId> parameters in the following code block based on the outputs of running the setup-infrastructure.sh script in Step 2 of the prerequisites.
    // identity-source-configuration.txt
    {
        "cognitoUserPoolConfiguration": {
            "userPoolArn": "<userPoolArn>",
            "clientIds":["<clientId>"] ,
            "groupConfiguration": {
                  "groupEntityType": "PetStoreApp::UserGroup"
            }
        }
    }
    

  2. After you update the file, run the following command to update the Verified Permissions policy store. Replace <policy store id> with the actual policy store ID.
    aws verifiedpermissions create-identity-source --configuration file://identity-source-configuration.txt --policy-store-id <policy store id> --principal-entity-type PetStoreApp::User
    

Example successful command output:

{
    "createdDate": "2025-06-05T20:02:53.992782+00:00",
    "identitySourceId": "DTLvwdiKfdPmk2RWzSVfu2",
    "lastUpdatedDate": "2025-06-05T20:02:53.992782+00:00",
    "policyStoreId": "AAAAbbbbCCCCdddd"
}

Step 6: Update the application code to call Verified Permissions to authorize API access 

You now need to update the application to use the @verifiedpermissions/authorization-clients and @cedar-policy/authorization-for-expressjs dependencies. This will allow the application to call Verified Permissions to authorize the API requests.

  1. Add the dependencies and define the CedarAuthorizerMiddleware and AVPAuthorizer in the application by adding the following block of code to line 13 (directly after the import statements) of backend/app.ts. Replace <policystoreId> in the following code block with your actual Verified Permissions policy store ID.
    const { ExpressAuthorizationMiddleware } = require('@cedar-policy/authorization-for-expressjs');
    
    const { AVPAuthorizationEngine } = require('@verifiedpermissions/authorization-clients');
    
    const avpAuthorizationEngine = new AVPAuthorizationEngine({
        policyStoreId: <policyStoreId>,
        callType: 'identityToken'
    });
    
    const expressAuthorization = new ExpressAuthorizationMiddleware({
        schema: {
            type: 'jsonString',
            schema: fs.readFileSync(path.join(__dirname, '../v4.cedarschema.json'), 'utf8'),
        },
        authorizationEngine: avpAuthorizationEngine,
        principalConfiguration: { type: 'identityToken' },
        skippedEndpoints: [],
        logger: {
            debug: (s: any) => console.log(s),
            log: (s: any) => console.log(s),
        }
    });
    

  2. Configure the Express application to use the authorization middleware that you just defined. To do this, add the following line of code to the end of the block of app.use(..) statements that begin after the comment // Configure security and performance middleware (approximately line 48 depending on how you pasted the previous block of code).
    app.use(expressAuthorization.middleware);
    

You’ve now successfully set up authorization in your application by creating a Verified Permissions policy store, writing Cedar policies to define your authorization, and integrating your application with Verified Permissions.

Validating API security

You can use the frontend web application to verify that authorization has been applied to the APIs. In two separate terminals run the following commands in the /start directory

./scripts/run-backend-dev.sh
./scripts/run-frontend-dev.sh

In a browser navigate to http://localhost:3001 and sign in with one of the Amazon Cognito users you created earlier. Validate that the permissions policies are working as expected:

  • Administrators: Can view, create, update, and delete pets.
  • Employees: Can view, create, and update pets.
  • Customers: Can view pets and create new pets.

In the terminal for the Express application, you can see log output that provides additional details about the authorization decisions. For example, following an unauthorized action the terminal outputs the following:

Authorization result: {"type":"deny"}

Conclusion

The new @verifiedpermissions/authorization-clients-js package allows Express developers to integrate their application with Verified Permissions to decouple authorization logic from code. By decoupling your authorization logic and integrating your application with the Verified Permissions, you can improve developer productivity and simplify permissions and access audits.

To support analyzing and auditing permissions when writing cedar policies the open source Cedar project also recently open sourced the Cedar Analysis CLI to help developers perform policy analysis on their policies. You can learn more about this new tool in Introducing Cedar Analysis: Open Source Tools for Verifying Authorization Policies.

The framework packages are open source and available on GitHub under the Apache 2.0 license, with distribution through NPM. To learn more, see Amazon Verified Permissions and Cedar.

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

Trevor Schiavone

Trevor Schiavone

Trevor is a Senior Solutions Architect at AWS. He works with customers to build secure, scalable, and innovative architectures. When not at work he’s usually out running, cycling, or travelling to new countries.

Rickard Lofstrom

Rickard Löfström

Ricard guides enterprises in building secure cloud environments as a Specialist Solution Architect in the AWS EMEA Security & Compliance team. He advises customers on implementing AWS security services, focusing on identity management, data protection, and infrastructure security controls. Rickard translates complex security requirements into technical solutions that enable organizations to meet their security objectives while maintaining operational efficiency.

Improve your security posture using Amazon threat intelligence on AWS Network Firewall

Post Syndicated from Amit Gaur original https://aws.amazon.com/blogs/security/improve-your-security-posture-using-amazon-threat-intelligence-on-aws-network-firewall/

Today, customers use AWS Network Firewall to safeguard their workloads against common security threats. However, they often have to rely on third-party threat feeds and scanners that have limited visibility in AWS workloads to protect against active threats. A self-managed approach to cloud security through traditional threat intelligence feeds and custom rules can result in delayed responses, leaving customers exposed to active threats that are relevant to AWS workloads. Customers are looking for an automated approach to analyzing threats and deploying mitigations across multiple enforcement points to establish consistent defenses and want a unified, AWS-native solution that can rapidly protect against active threats across their entire cloud infrastructure.

This post introduces active threat defense, a new Network Firewall managed rule group that offers protection against active threats relevant to workloads in AWS. Active threat defense uses the AWS global infrastructure visibility and extensive threat intelligence to deliver automated, intelligence-driven security measures. The feature uses the Amazon threat intelligence system MadPot, which continuously tracks attack infrastructure, including malware hosting URLs, botnet command and control servers, and crypto mining pools, identifying indicators of compromise (IOCs) for active threats.

Active threat defense comes as a rule group AttackInfrastructure, which protects against malicious network traffic by blocking communications with detected attack infrastructure. After the managed rule group is configured in your firewall policy, Network Firewall now automatically blocks suspicious traffic to malicious IPs, domains, and URLs for indicator categories such as command-and-control (C2s), malware staging hosts, sinkholes, out-of-band testing (OAST), and mining-pools. It implements comprehensive filtering of both inbound and outbound traffic for various protocols, including TCP, UDP, DNS, HTTPS, and HTTP, and uses specific, verified threat indicators to facilitate high accuracy and minimize false positives.

Network Firewall with active threat defense protects AWS workloads using the following mechanisms:

  • Threat prevention: Automatically blocks malicious traffic using Amazon threat intelligence to identify and prevent active threats targeting workloads in AWS
  • Rapid protection: Continuously updates Network Firewall rules based on newly discovered threats, enabling immediate protection against them
  • Streamlined operations: Findings in GuardDuty marked with the threat list name “Amazon Active Threat Defense” can now be automatically blocked when active threat defense is enabled on Network Firewall
  • Collective defense: Deep threat inspection (DTI) enables shared threat intelligence, improving protection for active threat defense managed rule group users

Figure 1 illustrates the use of the active threat defense managed rule group with Network Firewall. It shows the automatic creation of stateful rules in the AWS managed rule group using threat data collected from MadPot.

Figure 1: Network Firewall with active threat defense

Figure 1: Network Firewall with active threat defense

Getting started

The active threat defense managed rule group can be enabled directly within Network Firewall using the AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDK. You can then associate the managed rule group with the Network Firewall policy. The rule group receives regular updates with new threat indicators and signatures, while automatically removing inactive or aged-out signatures.

Prerequisites

To get started with Network Firewall with active threat defense, visit the Network Firewall console or see the AWS Network Firewall Developers Guide. Active threat defense is supported in all AWS Regions where Network Firewall is available today, including the AWS GovCloud (US) Regions and China Regions.

If this is your first time using Network Firewall, make sure to complete the following prerequisites. If you already have a firewall policy and a firewall, you can skip this section.

  1. Create a firewall policy
  2. Create a firewall

Set up the active threat defense managed rule group

With the prerequisites in place, you can set up and use the active threat defence managed rule group.

To set up the managed rule group:

  1. In the AWS Network Firewall console, choose Firewall policies in the navigation pane.
  2. Select an existing firewall policy or the policy that you created as part of the prerequisites.

    Figure 2: Select the Network Firewall policy

    Figure 2: Select the Network Firewall policy

  3. Scroll down to Stateful rule groups. On the right-hand side, choose Actions and select Add managed stateful rule groups.

    Figure 3: Add a rule group

    Figure 3: Add a rule group

  4. On the Add managed stateful rule groups page, scroll down to active threat defense. Select the rule group AttackInfrastructure. Based on your requirements for Deep threat inspection, you can opt out if you don’t want Network Firewall to process service logs. Choose Add to policy.

    Figure 4: Add the rule group to the policy

    Figure 4: Add the rule group to the policy

  5. You can verify on the next page the managed rule group was added to the policy.

    Figure 5: Verify that the managed rule group was added to the policy

    Figure 5: Verify that the managed rule group was added to the policy

Pricing

For active threat defense pricing, see AWS Network Firewall pricing.

Considerations

The first consideration is to understand how Network Firewall is more effective in detecting and mitigating threats associated with HTTPS traffic when the TLS inspection feature is used alongside the active threat defense managed rule group. TLS inspection enables active threat defense to analyze the actual content of encrypted connections, allowing it to identify and block malicious URLs that might otherwise pass undetected. This process involves decrypting traffic, inspecting the contents for known malicious URL patterns or behaviors, and then re-encrypting the traffic if it’s deemed safe. For more information on the considerations on TLS inspection, see Considerations for TLS inspection. Organizations must balance the security benefits with potential latency introduction and make sure that they have proper controls in place to handle sensitive decrypted data.

Another consideration is the mitigation of false positives. When you use this managed rule group in your firewall policy, you can edit rule group alert settings to help identify false-positives as part of a mitigation strategy. For more information, see mitigating false-positives.

The final consideration is how the use of managed rule groups count against the limit of stateful rules for each policy. For more information, see AWS Network Firewall quotas and Setting rule group capacity in AWS Network Firewall.

Conclusion

In this post, you learned how to use the AWS Network Firewall active threat defense managed rule group to safeguard workloads against active threats.

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

Amit Gaur

Amit Gaur

Amit, a Cloud Infrastructure Architect at AWS, brings his passion for technology and knowledge-sharing to the networking community. Specializing in network architecture design, he helps customers build highly scalable and resilient environments on AWS. Through technical guidance and architectural expertise, Amit enables customers to accelerate their cloud adoption journey while making sure their systems are built for scale and reliability.

Tim Sutton

Tim Sutton

Tim is a Senior Cloud Infrastructure Architect at AWS with over 20 years of experience in technology and brings extensive experience in cloud technologies, enterprise architecture, and business transformation. Tim is passionate about helping customers architect and implement scalable cloud solutions and achieve their business objectives through technology, as well as mentoring the next generation of cloud professionalst.

Prashanth Kalika

Prashanth Kalika

Prashanth has over 20 years of experience developing innovative and scalable solutions for networking, security, and cloud use cases. He currently focuses on developing advanced threat intelligence capabilities for AWS Firewall so customers can better protect their cloud workloads. Prashanth is passionate about building security solutions that help organizations stay ahead of evolving cyberthreats while maintaining robust network defenses.

Saleem Muhammad

Saleem Muhammad

Saleem is a Senior Manager of Product Management in AWS Network & Application Protection. He is passionate about building solutions that help customers to secure mission critical workloads. Before AWS, Saleem worked on incubation projects at multi-$B IT product and services organizations in the San Francisco Bay area.

How AWS is simplifying security at scale: Four keys to faster innovation from AWS re:Inforce 2025

Post Syndicated from Amy Herzog original https://aws.amazon.com/blogs/security/how-aws-is-simplifying-security-at-scale-four-keys-to-faster-innovation-from-aws-reinforce-2025/

When I began my career in security, most people accepted as fact that protecting systems came at the expense of productivity. That didn’t have to be true then, and it’s definitely not true now. The cloud, and specifically the AWS Cloud, is a big reason why. But as technology evolves and systems become more complex, operating at scale demands a fresh approach to security. We take our customers’ security seriously, and that means building guardrails that give organizations the confidence to innovate boldly and scale rapidly.

In my new role as AWS CISO, I see this playing out daily. As I meet with customers, their excitement about technologies like generative AI comes hand in hand with questions about securing complex environments and managing new types of risk. They’re excited about innovation, but they need confidence that their security foundations can keep pace with their ambitions. They want to move fast without compromising security.

Today at re:Inforce, I shared how AWS is working backward from these needs to fundamentally transform how security scales in the cloud. It all starts with a security foundation built on four key pillars: identity and access management, data and network security, monitoring and incident response, and the continuous work of migration, modernization, and patching. Organizations with mature security models across these pillars are the ones moving fastest. Across each of these areas, we’re focused on delivering security capabilities that help customers adopt new technologies and experiment with confidence.

Scaling identity for the cloud

As our customers rapidly scale their cloud operations, they’ve told us that managing identity and access across complex environments becomes increasingly challenging. They need solutions that can grow with their business while maintaining strong security. Identity and access management underpins every aspect of cloud security, and success in this area requires both rigorous authentication controls and comprehensive visibility into access permissions.

I was excited to announce new internal access findings for AWS IAM Access Analyzer today. This capability transforms how organizations manage access to sensitive data at scale, addressing the complexities our customers face as they grow. Using automated reasoning technology, it analyzes complex permission layers across diverse policy types, giving security teams comprehensive visibility into who within their organizations has access to what resources. With daily monitoring and notifications of new access granted, we’re helping teams implement least-privilege access with confidence in even the most complex environments. This provides our customers visibility to strengthen access controls on their critical resources while maintaining the agility their business demands as they scale in the cloud.

Empowering transformation through data and network security

Our customers are eager to transform their businesses, but they need confidence that their security can keep pace with rapid innovation. This is especially true when it comes to protecting their networks and data at scale. During the keynote, Noopur Davis, CISO of Comcast, shared how her organization protects their vast network and customer data while enabling rapid innovation. With millions of customers relying on their services, Comcast’s approach resonated with me: security shouldn’t just defend, it should enable transformation.

We’re delivering on this vision with new capabilities that simplify security at scale. Today, I announced that AWS Certificate Manager now allows you to export ACM-issued public certificates and their private keys for use inside or outside of AWS, giving you automated certificate management with the flexibility to help secure your workloads. We’re also expanding AWS Shield with enhanced network and application protection that performs a network security analysis to identify configuration issues and provides remediation recommendations. You can even use AWS generative AI powered assistant Amazon Q Developer to gain actionable insights using simple natural language. These innovations help teams protect their data and stay ahead of evolving threats even as their environments grow more complex.

Elevating threat detection and response

Our customers have shared their challenges in keeping pace with the evolving threat landscape, especially as they scale their cloud operations. While traditional automation helps manage growing complexity, AI represents an even more powerful opportunity to transform security operations. When implemented thoughtfully, AI dramatically improves our ability to spot complex attack patterns, reduce false positives, and automate responses at massive scale.

Today at re:Inforce, I announced two key security innovations: expanded capabilities in Amazon GuardDuty Extended Threat Detection and enhanced AWS Security Hub that directly address these needs. Together, these services help simplify security at scale. GuardDuty uses AWS-trained AI and machine learning (AI/ML) models to detect sophisticated multi-stage threats and provide actionable insights, while Security Hub prioritizes critical security issues by automatically analyzing and correlating security signals into clear, prioritized actions. This approach gives teams the confidence to scale their operations, knowing they can detect and respond to security risks efficiently across their entire AWS environment.

Accelerating the journey to better security

While advanced capabilities like AI and automation help strengthen security operations, the foundation matters most. Moving to the cloud represents a transformative opportunity to build on a fundamentally stronger security foundation than most organizations can ever hope to achieve with on-premises environments. When migrating to AWS, you reduce the need to manage physical infrastructure security while gaining access to built-in protections that are continuously updated and maintained.

Successful cloud adoption means going beyond simple lift-and-shift. Modernization is key to realizing these benefits. By moving solutions further up the stack to use managed services like AWS Lambda, Amazon Simple Storage Service (Amazon S3), or AWS Key Management Service (AWS KMS), you benefit from security controls that are built in rather than bolted on. These services are continuously patched and maintained by AWS, freeing your teams to focus on innovating for your customers. After all, the fastest path to better security is the one where core protections are already built in.

Partnering for security success

Security transformation isn’t a journey organizations need to take alone. Throughout my career, I’ve seen how the right partnerships can accelerate success, bringing fresh perspectives and deep expertise to complex challenges. Our security partners help customers across the four pillars we discussed today, from implementing identity solutions to modernizing security operations. They understand both the technical complexities and the business realities of scaling security in the cloud, often bringing valuable industry-specific experience that helps organizations move faster with confidence.

Looking ahead

As you scale your operations in the cloud, our goal is to give you the confidence to move quickly while maintaining strong security controls. When security scales naturally with your business, teams can focus on building what’s next instead of managing infrastructure.

To dive deeper into how AWS designs, builds, and operates security at unprecedented scale, I encourage you to join our Innovation Talks at re:Inforce. These hour-long sessions explore the key pillars of modern cloud security: secure foundations, resilient architectures, AI-powered innovations, and large-scale threat intelligence.

As I step into my role as AWS CISO, I’m energized by the opportunity ahead. For nearly 20 years, AWS has maintained a unique culture of security that enables us to innovate rapidly while shipping securely. As we navigate the landscape of generative AI and rapid technological change, earning your trust means not just keeping pace with innovation, but helping to make it even more successful. I couldn’t be more excited to carry this mission forward.

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

Amy Herzog

Amy Herzog

Amy is Vice President and Chief Information Security Officer (CISO) at AWS where she leads a global organization of cloud security professionals in a company in which security is the top priority. Prior to joining AWS, Amy served as CISO for Amazon’s Devices and Services, Media and Entertainment, and Advertising businesses, overseeing the security of consumer technology offerings such as Alexa+ and Ring, and playing a key role in the secure development of Project Kuiper, Amazon’s initiative to provide fast, reliable broadband to customers and communities around the world through low earth orbit satellites. Amy’s career spans more than two decades at the intersection of cybersecurity, innovation, and enterprise transformation. She spent 15 years at the MITRE Corporation, developing cutting-edge solutions for complex security challenges across government and industry. She also held leadership roles at Pivotal Software, VMware and Travelers Insurance, and co-founded two startups focused on technology-driven business transformation. Amy holds a BA in Mathematics from Pomona College and an MBA from MIT’s Sloan School of Management. She is also the author of several publications and holds two patents.

Unify your security with the new AWS Security Hub for risk prioritization and response at scale (Preview)

Post Syndicated from Donnie Prakoso original https://aws.amazon.com/blogs/aws/unify-your-security-with-the-new-aws-security-hub-for-risk-prioritization-and-response-at-scale-preview/

AWS Security Hub has been a central place for you to view and aggregate security alerts and compliance status across Amazon Web Services (AWS) accounts. Today, we are announcing the preview release of the new AWS Security Hub which offers additional correlation, contextualization, and visualization capabilities. This helps you prioritize critical security issues, respond at scale to reduce risks, improve team productivity, and better protect your cloud environment.

Here’s a quick look at the new AWS Security Hub.

With this new enhancement, AWS Security Hub integrates security capabilities like Amazon GuardDuty, Amazon Inspector, AWS Security Hub Cloud Security Posture Management (CSPM), Amazon Macie, and other AWS security capabilities to help you gain visibility across your cloud environment through centralized management in a unified cloud security solution. 

Getting started with the new AWS Security Hub
Let me walk you through how to get started with AWS Security Hub.

If you’re a new customer to AWS Security Hub, you need to navigate to the AWS Security Hub console to enable AWS security capabilities and capabilities and start assessing risk across your organization. You can learn more on the Documentation page.

After you have AWS Security Hub enabled, it will automatically consume data from supporting security capabilities you’ve enabled, such as Amazon GuardDuty, Amazon Inspector, Amazon Macie, and AWS Security Hub CSPM. You can navigate to the AWS Security Hub console to view these findings and benefit from insights created through correlation of findings across these capabilities.

As security risks are uncovered, they’re presented in a redesigned Security Hub summary dashboard. The new Security Hub summary dashboard provides a comprehensive, unified view of your AWS security posture. The dashboard organizes security findings into distinct categories, making it easier to identify and prioritize risks.

The new Exposure summary widget helps you identify and prioritize security exposures by analyzing resource relationships and signals from Amazon Inspector, AWS Security Hub CSPM, and Amazon Macie. These exposure findings are automatically generated and are a key part of the new solution, highlighting where your critical security exposures are located. You can learn more about exposure on the Documentation page.

AWS Security Hub now provides a Security coverage widget designed to help you identify potential coverage gaps. You can use this widget to identify where you’re missing coverage by the security capabilities that power Security Hub. This visibility helps you identify which capabilities, accounts, and features you need to address to improve your security coverage.

As you can see on the navigation menu, AWS Security Hub is organized into five key areas to streamline security management:

  • Exposure: Provides visibility into all exposure findings, a security vulnerability or misconfiguration that could potentially expose an AWS resource or system to unauthorized access or compromise, generated by Security Hub, helping you identify resources that might be accessible from outside your environment
  • Threats: Consolidates all threat findings generated by Amazon GuardDuty, showing potential malicious activities and intrusion attempts
  • Vulnerabilities: Displays all vulnerabilities detected by Amazon Inspector, highlighting software flaws and configuration issues
  • Posture management: Shows all posture management findings from AWS Security Hub Cloud Security Posture Management (CSPM), helping provide compliance with security best practices
  • Sensitive data: Presents all sensitive data findings identified by Amazon Macie, helping you track and protect your sensitive information

When you navigate to the Exposure page, you’ll see findings grouped by title, with severity levels clearly indicated to help you focus on critical issues first.

To explore specific exposures, you can select any finding to see affected resources. The panel includes key information about the implicated resource, account, Region, and when the issue was detected.

In this panel, you’ll also find an attack path visualization that is particularly useful for understanding complex security relationships. For network exposure paths, you can see all components involved in the path—including virtual private clouds (VPCs), subnets, security groups, network access control lists (ACLs), and load balancers—helping you identify exactly where to implement security controls. The visualization also highlights Identity and Access Management (IAM) relationships, showing how permission configurations might allow privilege escalation or data access. Resources with multiple contributing traits are clearly marked so you can quickly identify which components represent the greatest risk.

The Threats dashboard provides actionable insights into potential malicious activities detected by Amazon GuardDuty, organizing findings by severity so you can quickly identify critical issues like unusual API calls, suspicious network traffic, or potential credential compromises. The dashboard includes GuardDuty Extended Threat Detection findings, with all “Critical” severity threats representing these Extended Threat Detections that require immediate attention.

Similarly, the Vulnerabilities dashboard from Amazon Inspector provides a comprehensive view of software vulnerabilities and network exposure risks. The dashboard highlights vulnerabilities with known exploits, packages requiring urgent updates, and resources with the highest numbers of vulnerabilities.

Another valuable new feature is the Resources view, which provides an inventory of all resources deployed in your organization covered by AWS Security Hub. You can use this view to quickly identify which resources have findings against them and filter by resource type or finding severity. Selecting any resource provides detailed configuration information without needing to pivot to other consoles, streamlining your investigation workflow.

The new Security Hub also offers integration capabilities to help you comprehensively monitor your cloud environments and connect with third-party security solutions. This gives you the flexibility to create a unified security solution tailored to your organization’s specific needs.

For example, with integration capability, when viewing a security finding, you can select the Create ticket option and choose your preferred ticketing integration.

Additional things to know
Here are a couple of things to note:

  • Availability – During this preview period, the new AWS Security Hub is available in following AWS Regions: US East (N. Virginia, Ohio), US West (N. California, Oregon), Africa (Cape Town), Asia Pacific (Hong Kong, Jakarta, Mumbai, Osaka, Seoul, Singapore, Sydney, Tokyo), Canada (Central), Europe (Frankfurt, Ireland, London, Milan, Paris, Stockholm), Middle East (Bahrain), and South America (São Paulo).
  • Pricing – The new AWS Security Hub is available at no additional charge during the preview period. However, you will still incur costs for the integrated capabilities including Amazon GuardDuty, Amazon Inspector, Amazon Macie, and AWS Security Hub CSPM.
  • Integration with existing AWS security capabilities – Security Hub integrates with Amazon GuardDuty, Amazon Inspector, AWS Security Hub CSPM, and Amazon Macie, providing a comprehensive security posture without additional operational overhead.
  • Enhanced data interoperability – The new Security Hub uses the Open Cybersecurity Schema Framework (OCSF), enabling seamless data exchange across your security capabilities with normalized data formats.

To learn more about the enhanced AWS Security Hub and join the preview, visit the AWS Security Hub product page.

Happy building!

— Donnie

Beyond compute: Shifting vulnerability detection left with Amazon Inspector code security capabilities

Post Syndicated from Nirali Desai original https://aws.amazon.com/blogs/security/shifting-vulnerability-detection-left-with-amazon-inspector-code-security-capabilities/

Since launch, Amazon Inspector has helped customers automate vulnerability management for their running workloads on Amazon Elastic Compute Cloud (Amazon EC2), container workloads, and AWS Lambda functions. Today, we’re taking a step forward into more proactive security with the latest addition to Amazon Inspector: code security capabilities. By using this powerful new feature you can get a proactive view of the security health of your code. With native integration to source code managers (SCM) such as GitHub and GitLab, Amazon Inspector helps you identify and prioritize security vulnerabilities and misconfigurations across your application source-code, dependencies, and infrastructure as code (IaC).

Even if you make no changes to your code, there can be vulnerabilities in libraries that it depends on, creating risks for you and your users. By scanning repositories, you can continually monitor the security of your code and its dependencies. With Amazon Inspector, you can define consistent security controls throughout your software development lifecycle, so your security and development teams can collaborate effectively while reducing risk and remediation costs.

Overview of Amazon Inspector code security capabilities

Amazon Inspector now provides three additional security analysis capabilities: static application security testing (SAST), software composition analysis (SCA), and infrastructure as code (IaC) scanning. To use these features, you must establish a connection with your SCM tool (as shown in Figure 1). If you use GitHub, you can get started by installing and configuring the Amazon Inspector App from the GitHub Marketplace, which enables automated code analysis and delivers security findings directly within pull requests. If you use a self-managed GitLab, implementation is straightforward using a personal access token with the necessary permissions.

Figure 1: Code security landing page for Amazon Inspector

Figure 1: Code security landing page for Amazon Inspector

Static application security testing

Static application security testing (SAST) is the process of analyzing source code to identify insecure patterns or methods without needing to compile or execute the code. Amazon Inspector SAST scans analyze your source code to identify potential security vulnerabilities such as hardcoded secrets, cross-site scripting, or injection attacks across a wide range of programming languages including, JavaScript, Python, C#. The service also analyzes Bash shell scripts, extending security coverage beyond application code to include deployment and configuration scripts.

Software composition analysis

Software composition analysis (SCA) helps you understand and manage risks related to software dependencies. Every programming language has its own method of finding, importing, and updating contributed libraries. For example, PyPI for Python, NPM for NodeJS, and Cargo for Rust. Sometimes vulnerabilities are discovered in libraries distributed through the language-specific package distributions, or sometimes a library that you’re using depends on another library, and that dependency has the vulnerability. Amazon Inspector supports the major environments for Python, .Net, PHP, JavaScript, Java, Ruby, Rust, and Go. It automatically analyzes dependencies to identify known vulnerabilities and show you which code is affected. When vulnerabilities are detected, Amazon Inspector provides detailed information about the impact, available fixes, and upgrade paths to help you quickly remediate issues.

Infrastructure as code security

Just as applications are constructed from code, cloud infrastructure can be deployed and managed through code-based methods. Amazon Inspector now also analyzes IaC templates (as shown in Figure 2) to identify potential security misconfigurations, for example, the use of AWS Identity and Access Management (IAM) wildcards in action statements or disabled Glue Data Catalog encryption. This way identified risks can be fixed before the code is executed and the incorrect infrastructure is deployed. The new feature analyzes AWS CloudFormation, Terraform, and AWS CDK, helping you maintain secure infrastructure definitions throughout their development process. This capability helps make sure that security best practices are followed, and potential issues are caught before the infrastructure is deployed.

Figure 2: Amazon Inspector scan analysis configuration showing SAST, IaC, and SCA scan types

Figure 2: Amazon Inspector scan analysis configuration showing SAST, IaC, and SCA scan types

For the most up-to-date list of programming languages supported across Amazon Inspector code security capabilities, see the online documentation.

Improved security governance and visibility

Amazon Inspector lets you choose which scan types to run across which repositories (as shown in Figure 3). You can initiate a scan based on any of the following:

  • On-demand: Initiates an immediate scan of the selected repository
  • Change based: Initiates a scan on push to main branch, or on a pull request or merge request
  • Scheduled: Initiates a scan weekly or monthly
Figure 3: Overview of scan configurations

Figure 3: Overview of scan configurations

Amazon Inspector integrates code security findings into a unified dashboard that you can use to manage and enforce scanning policies across repositories using customizable scan configurations. As part of the integration workflow with the SCM platform, you can set up a default scan configuration that can be applied to existing or new repositories. Alternatively, you also have an option to create custom scan configurations that match specific existing repositories through inclusions tags.

Upon successful scheduled or event-based scans, Amazon Inspector generates detailed findings that pinpoint specific lines of code within repositories, including commit IDs and file locations where vulnerabilities are detected. Amazon Inspector empowers your security teams with customizable filtering through intelligent suppression rules. By using these options, you can tailor your security view to match your organization’s unique priorities, showing exactly what matters most to your team while preserving findings data for reporting and auditing. Through native Amazon EventBridge integration, these detailed security findings can be automatically routed into existing security workflows, enabling alerting and response capabilities.

Code fix recommendations

Amazon Inspector streamlines security remediation by providing specific code fix recommendations directly where developers work. The two-way integration with your SCM automatically suggests fixes as comments within pull requests (PRs) and merge requests (MRs) for Critical and High findings, alerting developers to the most important vulnerabilities to address without disrupting their workflow. Simultaneously, security teams benefit from a consolidated dashboard in the Amazon Inspector console that aggregates findings from scheduled or event-based scans across in-scope repositories. Each finding comes with tailored remediation guidance based on scan type (as shown in Figure 4): specific code suggestions for IAC and SAST findings, or recommended version upgrades and dependency update paths for SCA findings.

Figure 4: Code fix recommendation on a finding in the Amazon Inspector dashboard

Figure 4: Code fix recommendation on a finding in the Amazon Inspector dashboard

Conclusion

These expanded security capabilities now deliver end-to-end visibility of the security health of your cloud applications, from initial code development through to production deployment. Security teams can use the unified dashboard in Amazon Inspector to track and manage vulnerabilities across repositories and application components, facilitating consistent security controls throughout the software lifecycle. Meanwhile, development teams receive immediate, actionable feedback within their source code repositories, creating a seamless security experience that bridges both security and development workflows. This approach is designed to help you maintain robust security practices while keeping development velocity high.

To get started with the new capabilities of Amazon Inspector, visit the Amazon Inspector console. For pricing details and implementation guidance, see documentation. These new features are now available in 10 AWS commercial Regions.

Nirali Desai

Nirali Desai

Nirali is a product leader in cloud security, currently driving Application Security initiatives at Amazon Web Services (AWS). Before joining AWS, she held key roles at Palo Alto Networks, Zscaler, and Cisco Tetration, where she focused on building Secure Access Secure Edge (SASE), end-user security, workload protection, and zero-trust security solutions. She is passionate about building scalable security products that defend against evolving cyber threats.

Danny Cortegaca

Danny Cortegaca

Danny is a Security Specialist Solutions Architect and co-leads the Application Security focus area within the AWS Security and Compliance Technical Field Community. He joined AWS in 2021 and partners with some of the largest organizations in the world to help them navigate complex security and regulatory environments. He loves talking about application security with customers and has helped many adopt threat modeling into their practices.

Daniel Beghimer

Daniel Beghimer

Daniel is a Senior Security Engineer specializing in cloud security and incident response solutions. He co-leads the Application Security focus area within the AWS Security and Compliance Technical Field Community, holds all AWS certifications, and authored Automated Security Helper (ASH), an open-source code scanning tool. In his free time, Daniel enjoys gadgets, video games, and traveling.

AWS Backup adds new Multi-party approval for logically air-gapped vaults

Post Syndicated from Veliswa Boya original https://aws.amazon.com/blogs/aws/aws-backup-adds-new-multi-party-approval-for-logically-air-gapped-vaults/

Today, we’re announcing the general availability of a new capability that integrates AWS Backup logically air-gapped vaults with Multi-party approval to provide access to your backups even when your AWS account is inaccessible due to inadvertent or malicious events. AWS Backup is a fully managed service that centralizes and automates data protection across AWS services and hybrid workloads. It provides core data protection features, ransomware recovery capabilities, and compliance insights and analytics for data protection policies and operations.

As a backup administrator, you use AWS Backup logically air-gapped vaults to securely share backups across accounts and organizations, logically isolate your backup storage, and support direct restore to help reduce recovery time following an inadvertent or malicious event. However, if a bad or unintended actor gains root access to your backup account or the management account of your organization, your backups suddenly become inaccessible, even though they’re still safely stored in the logically air-gapped vault. While traditional account recovery involved working through support channels, AWS Backup with Multi-party approval delivers immediate access to recovery tools, empowering you with faster resolution times and greater control over your recovery timeline.

Multi-party approval for AWS Backup logically air-gapped vaults adds an additional layer of protection for you to recover your application data even when your AWS account becomes completely inaccessible. Using Multi-party approval, you can create approval teams which consist of highly trusted individuals in your organization, then associate them with your logically air-gapped vault. If you get locked out of your AWS accounts due to inadvertent or malicious actions, you can request your own approval team to authorize sharing of your vault from any account, even those outside your AWS Organizations account. Once approved, you gain authorized access to your backups and can begin your recovery process.

How it works
Multi-party approval for AWS Backup logically air-gapped vaults combines the security of logically air-gapped vaults with the governance of Multi-party approval to create a recovery mechanism that works even when your AWS account is compromised. Here’s how it works:

1. Approval team creation
First, you create an approval team in your AWS Organizations management account. If the management account is new, first create an AWS Identity and Access Management (IAM) Identity Center instance before creating the approval team. The approval team consists of trusted individuals (IAM Identity Center users) who will be authorized to approve vault sharing requests. Each approver receives an invitation to join the approval team through a new Approval portal.

2. Vault association
When your approval team is active, you share it with accounts that own logically air-gapped vaults using AWS Resource Access Manager (AWS RAM) to safeguard against requests for approval from arbitrary accounts. Backup administrators can then associate this approval team with new or existing logically air-gapped vaults.

3. Protection against compromise
If your AWS account becomes compromised or inaccessible, you can request access to your backups from a different account (a clean recovery account). This request includes the Amazon Resource Name (ARN) of the logically air-gapped vault in the format arn:aws:backup:<region>:<account>:backup-vault:<name> and an optional vault name and comment.

4. Multi-party approval
The request is sent to the approval team, who review it through the approval portal. When the minimum required number of approvers authorize the request, the vault is automatically shared with the requesting account. All requests and approvals are comprehensively logged in AWS CloudTrail.

5. Recovery process
With access granted, you can immediately start restoring or copying your data in the new recovery account without waiting for your compromised account to be remediated.

This approach provides an entirely separate authentication path to access and recover your backups, completely independent of your AWS account credentials. Even if the bad actor has root access to your account, they can’t prevent the approval team-based recovery process.

1. Create a new logically air-gapped vault
To create a new logically air-gapped vault, provide a name, tags (optional), and vault lock properties.

2. Assign an approval team
When the vault has been created, choose Assign approval team to assign it with an existing approval team.

Choose an existing approval team from the drop-down menu then select Submit to finalize the assignment.

Now your approval team is assigned to your logically air-gapped vault.

Good to know
It’s essential to test your recovery process before an actual emergency:

  1. From a different AWS account, use the AWS Backup console or API to request sharing of your logically air-gapped vault by providing the vault ID and ARN.
  2. Request approval of your request from the approval team.
  3. Once approved, verify that you can access and restore backups from the vault in your testing account.

As a best practice, monitor the health of your approval team regularly using AWS Backup Audit Manager to ensure they have sufficient active participants to meet your approval threshold.

Multi-party approval for enhanced cloud governance
Today, we’re also announcing the general availability of a new capability that AWS account administrators can use to add Multi-party approval to their product offerings. As highlighted in this post, AWS Backup is the first service to integrate this capability. With Multi-party approval, administrators can enable application owners to guard sensitive service operations with a distributed review process.

Good to know
Multi-party approval provides several significant security advantages:

  • Distributed decision-making, eliminating single points of failure
  • Full auditability through AWS CloudTrail integration
  • Protection against compromised credentials
  • Formal governance for compliance-sensitive operations
  • Consistent approval experience across integrated services

Now available

Multi-party approval is available today in all AWS Regions where AWS Organizations is available. Multi-party approval for AWS Backup logically air-gapped vaults is available in all AWS Regions where AWS Backup is available.

– Veliswa.

New AWS Shield feature discovers network security issues before they can be exploited (Preview)

Post Syndicated from Esra Kayabali original https://aws.amazon.com/blogs/aws/new-aws-shield-feature-discovers-network-security-issues-before-they-can-be-exploited-preview/

Today, I’m happy to announce AWS Shield network security director (preview), a capability that simplifies identification of configuration issues related to threats such as SQL injections and distributed denial of service (DDoS) events, and proposes remediations. This feature identifies and analyzes network resources, connections, and configurations. It compares them against AWS best practices to create a network topology that highlights resources requiring protection.

Organizations today face significant challenges in maintaining a robust network security posture. Security teams often struggle to efficiently discover all resources in their environments, understand how these resources are interconnected, and identify which security services are currently configured. Additionally, they find determining how well resources are configured relative to AWS best practices requires considerable expertise and effort. Many teams find it difficult to identify which network security services and rule sets would best protect their applications from common and emerging threats.

AWS Shield network security director addresses these challenges through three key capabilities. First, it performs comprehensive analysis to discover resources across your AWS accounts, identify connectivity between resources, and determine which network security services and configurations are currently in place. Second, it prioritizes resources by severity level based on AWS network security best practices and threat intelligence. Finally, it provides specific remediation recommendations such as step-by-step instructions for implementing the right AWS security services, including AWS WAF, Amazon Virtual Private Cloud (Amazon VPC) security groups, and Amazon VPC network access control lists (ACLs) to protect your resources.

The service supports critical network security use cases, including protecting applications against internet-born threats and controlling human access to resources based on port, protocol, or IP address range. It provides network analysis to discover assets and delivers analysis that eliminates time-consuming manual processes for identifying resources that need protection. The service offers resource prioritization by assigning security findings a severity level based on network context and adherence to AWS best practices, helping you focus on what matters most. Additionally, it supplies actionable recommendations with specific guidance on which services and configurations will address each security gap. You can also get answers, in natural language, from AWS Shield network security director from within Amazon Q Developer in the AWS Management Console and chat applications.

Getting started with AWS Shield network security director
To use AWS Shield network security director, I need to initiate a network analysis of my AWS resources. I go to the AWS WAF & Shield console and choose Getting started under AWS Shield network security director in the navigation pane. I choose Get started, which takes me to the configuration page. On this page, I can choose how to perform my first network analysis: I can assess findings from across all supported Regions or from my current Region only. I select Start network analysis.

After the analysis is completed, the dashboard page shows a breakdown of resource types by severity level and the most common categories of network security findings associated with their resources. Resources are categorized by type and severity level (critical, high, medium, low, informational), making it easy to identify which areas need immediate attention.

Next, I explore the Resources section to understand the distribution of my assets and filter by severity level in my environment. I can use Resource overview to review a specific severity level, which will redirect me to the Resources under Network security director with the associated severity level filter. I choose the resources that have Medium severity level.

I choose a specific resource to view its network topology map showing how it connects to other resources and associated findings. This visualization helps me understand the potential impact of security configurations and identify exposed paths. I review detailed findings such as “Allows unrestricted inbound access (0.0.0.0/0) on all ports” with severity ratings.

Next, I go to Findings under Network security director, which shows common configuration issues. For each finding, I receive detailed information and recommended remediation steps. The service rates the severity of findings (high, medium, low) to help me prioritize my response. Critical-severity findings such as “CloudFront origin is also internet accessible without CloudFront protections” or high-severity findings such as “Allows unrestricted inbound access (0.0.0.0/0) on all ports” are presented first, followed by medium- and low-severity issues.

You can analyze your network security configurations, in natural language, with AWS Shield network security director within Amazon Q Developer in the AWS Management Console and chat applications. For example, you can say “Do I have any network security issues on my CloudFront distributions?” or “Are any of my resources vulnerable to bots and scrapers?” This integration helps security teams quickly understand their security posture and receive guidance on implementing best practices without having to navigate through extensive documentation.

To explore this capability, I ask “What are my most critical network security issues?” in the Explore with Amazon Q section. Amazon Q analyzes my network security configuration and generates a response based on the security assessment of my AWS environment.

With this comprehensive view of your network security, you can now make data-driven decisions to strengthen your defenses against emerging threats.

Join the preview
AWS Shield network security director is available in the US East (N. Virginia) and Europe (Stockholm) Regions. The Amazon Q Developer capability to analyze network security configurations is available in preview in US East (N. Virginia). To begin strengthening your network security, visit the AWS Shield network security director console and initiate your first network security analysis.

For more information, visit the AWS Shield product page.

— Esra

AWS Certificate Manager introduces exportable public SSL/TLS certificates to use anywhere

Post Syndicated from Channy Yun (윤석찬) original https://aws.amazon.com/blogs/aws/aws-certificate-manager-introduces-exportable-public-ssl-tls-certificates-to-use-anywhere/

Today, we’re announcing exportable public SSL/TLS certificates from AWS Certificate Manager (ACM). Prior to this launch, you can issue your public certificates or import certificates issued by third-party certificate authorities (CAs) at no additional cost, and deploy them with integrated AWS services such as Elastic Load Balancing (ELB), Amazon CloudFront distribution, and Amazon API Gateway.

Now you can export public certificates from ACM, get access to the private keys, and use them on any workloads running on Amazon Elastic Compute Cloud (Amazon EC2) instances, containers, or on-premises hosts. The exportable public certificate are valid for 395 days. There is a charge at time of issuance, and again at time of renewal. Public certificates exported from ACM are issued by Amazon Trust Services and are widely trusted by commonly used platforms such as Apple and Microsoft and popular web browsers such as Google Chrome and Mozilla Firefox.

ACM exportable public certificates in action
To export a public certificate, you first request a new exportable public certificate. You cannot export previously created public certificates.

To get started, choose Request certificate in the ACM console and choose Enable export in the Allow export section. If you select Disable export, the private key for this certificate will be disallowed for exporting from ACM and this cannot be changed after certificate issuance.

You can also use the request-certificate command to request a public exportable certificate with Export=ENABLED option on the AWS Command Line Interface (AWS CLI).

aws acm request-certificate \
--domain-name mydomain.com \
--key-algorithm EC_Prime256v1 \
--validation-method DNS \
--idempotency-token <token> \
--options \
CertificateTransparencyLoggingPreference=DISABLED \
Export=ENABLED

After you request the public certificate, you must validate your domain name to prove that you own or control the domain for which you are requesting the certificate. The certificate is typically issued within seconds after successful domain validation.

When the certificate enters status Issued, you can export your issued public certificate by choosing Export.

Export your public certificate

Enter a passphrase for encrypting the private key. You will need the passphrase later to decrypt the private key. To get the public key, Choose Generate PEM Encoding.

You can copy the PEM encoded certificate, certificate chain, and private key or download each to a separate file.

Download PEM keys

You can use the export-certificate command to export a public certificate and private key. For added security, use a file editor to store your passphrase and output keys to a file to prevent being stored in the command history.

aws acm export-certificate \
     --certificate-arn arn:aws:acm:us-east-1:<accountID>:certificate/<certificateID> \
     --passphrase fileb://path-to-passphrase-file \
     | jq -r '"\(.Certificate)\(.CertificateChain)\(.PrivateKey)"' \
     > /tmp/export.txt

You can now use the exported public certificates for any workload that requires SSL/TLS communication such as Amazon EC2 instances. To learn more, visit Configure SSL/TLS on Amazon Linux in your EC2 instances.

Things to know
Here are a couple of things to know about exportable public certificates:

  • Key security – An administrator of your organization can set AWS IAM policies to authorize roles and users who can request exportable public certificates. ACM users who have current rights to issue a certificate will automatically get rights to issue an exportable certificate. ACM admins can also manage the certificates and take actions such as revoking or deleting the certificates. You should protect exported private keys using secure storage and access controls.
  • Revocation – You may need to revoke exportable public certificates to comply with your organization’s policies or mitigate key compromise. You can only revoke the certificates that were previously exported. The certificate revocation process is global and permanent. Once revoked, you can’t retrieve revoked certificates to reuse. To learn more, visit Revoke a public certificate in the AWS documentation.
  • Renewal – You can configure automatic renewal events for exportable public certificates by Amazon EventBridge to monitor certificate renewals and create automation to handle certificate deployment when renewals occur. To learn more, visit Using Amazon EventBridge in the AWS documentation. You can also renew these certificates on-demand. When you renew the certificates, you’re charged for a new certificate issuance. To learn more, visit Force certificate renewal in the AWS documentation.

Now available
You can now issue exportable public certificates from ACM and export the certificate with the private keys to use other compute workloads as well as ELB, Amazon CloudFront, and Amazon API Gateway.

You are subject to additional charges for an exportable public certificate when you create it with ACM. It costs $15 per fully qualified domain name and $149 per wildcard domain name. You only pay once during the lifetime of the certificate and will be charged again only when the certificate renews. To learn more, visit the AWS Certificate Manager Service Pricing page.

Give ACM exportable public certificates a try in the ACM console. To learn more, visit the ACM Documentation page and send feedback to AWS re:Post for ACM or through your usual AWS Support contacts.

— Channy

Verify internal access to critical AWS resources with new IAM Access Analyzer capabilities

Post Syndicated from Micah Walter original https://aws.amazon.com/blogs/aws/verify-internal-access-to-critical-aws-resources-with-new-iam-access-analyzer-capabilities/

Today, we’re announcing a new capability in AWS IAM Access Analyzer that helps security teams verify which AWS Identity and Access Management (IAM) roles and users have access to their critical AWS resources. This new feature provides comprehensive visibility into access granted from within your Amazon Web Services (AWS) organization, complementing the existing external access analysis.

Security teams in regulated industries, such as financial services and healthcare, need to verify access to sensitive data stores like Amazon Simple Storage Service (Amazon S3) buckets containing credit card information or healthcare records. Previously, teams had to invest considerable time and resources conducting manual reviews of AWS Identity and Access Management (IAM) policies or rely on pattern-matching tools to understand internal access patterns.

The new IAM Access Analyzer internal access findings identify who within your AWS organization has access to your critical AWS resources. It uses automated reasoning to collectively evaluate multiple policies, including service control policies (SCPs), resource control policies (RCPs), and identity-based policies, and generates findings when a user or role has access to your S3 buckets, Amazon DynamoDB tables, or Amazon Relational Database Service (Amazon RDS) snapshots. The findings are aggregated in a unified dashboard, simplifying access review and management. You can use Amazon EventBridge to automatically notify development teams of new findings to remove unintended access. Internal access findings provide security teams with the visibility to strengthen access controls on their critical resources and help compliance teams demonstrate access control audit requirements.

Let’s try it out

To begin using this new capability, you can enable IAM Access Analyzer to monitor specific resources using the AWS Management Console. Navigate to IAM and select Analyzer settings under the Access reports section of the left-hand navigation menu. From here, select Create analyzer.

Screenshot of creating an Analyzer in the AWS Console

From the Create analyzer page, select the option of Resource analysis – Internal access. Under Analyzer details, you can customize your analyzer’s name to whatever you prefer or use the automatically generated name. Next, you need to select your Zone of trust. If your account is the management account for an AWS organization, you can choose to monitor resources across all accounts within your organization or the current account you’re logged in to. If your account is a member account of an AWS organization or a standalone account, then you can monitor resources within your account.

The zone of trust also determines which IAM roles and users are considered in scope for analysis. An organization zone of trust analyzer evaluates all IAM roles and users in the organization for potential access to a resource, whereas an account zone of trust only evaluates the IAM roles and users in that account.

For this first example, we assume our account is the management account and create an analyzer with the organization as the zone of trust.

Screenshot of creating an Analyzer in the AWS Console

Next, we need to select the resources we wish to analyze. Selecting Add resources gives us three options. Let’s first examine how we can select resources by identifying the account and resource type for analysis.

Screenshot of creating an Analyzer in the AWS Console

You can use Add resources by account dialog to choose resource types through a new interface. Here, we select All supported resource types and select the accounts we wish to monitor. This will create an analyzer that monitors all supported resource types. You can either select accounts through the organization structure (shown in the following screenshot) or paste in account IDs using the Enter AWS account ID option.

Screenshot of creating an Analyzer in the AWS Console

You can also choose to use the Define specific resource types dialog, which you can use to pick from a list of supported resource types (as shown in the following screenshot). By creating an analyzer with this configuration, IAM Access Analyzer will continually monitor both existing and new resources of the selected type within the account, checking for internal access.

Screenshot of creating an Analyzer in the AWS Console

After you’ve completed your selections, choose Add resources.

Screenshot of creating an Analyzer in the AWS Console

Alternatively, you can use the Add resources by resource ARN option.

Screenshot of creating an Analyzer in the AWS Console

Or you can use the Add resources by uploading a CSV file option to configure monitoring a list of specific resources at scale.

Screenshot of creating an Analyzer in the AWS Console

After you’ve completed the creation of your analyzer, IAM Access Analyzer will analyze policies daily and generate findings that show access granted to IAM roles and users within your organization. The updated IAM Access Analyzer dashboard now provides a resource-centric view. The Active findings section summarizes access into three distinct categories: public access, external access outside of the organization (requires creation of a separate external access analyzer), and access within the organization. The Key resources section highlights the top resources with active findings across the three categories. You can see a list of all analyzed resources by selecting View all active findings or Resource analysis on the left-hand navigation menu.

Screenshot of Access Analyzer findings

On the Resource analysis page, you can filter the list of all analyzed resources for further analysis.

Screenshot of creating an Analyzer in the AWS Console

When you select a specific resource, any available external access and internal access findings are listed on the Resource details page. Use this feature to evaluate all possible access to your selected resource. For each finding, IAM Access Analyzer provides you with detailed information about allowed IAM actions and their conditions, including the impact of any applicable SCPs and RCPs. This means you can verify that access is appropriately restricted and meets least-privilege requirements.

Screenshot of creating an Analyzer in the AWS Console

Pricing and availability

This new IAM Access Analyzer capability is available today in all commercial Regions. Pricing is based on the number of critical AWS resources monitored per month. External access analysis remains available at no additional charge. Pricing for EventBridge applies separately.

To learn more about IAM Access Analyzer and get started with analyzing internal access to your critical resources, visit the IAM Access Analyzer documentation.

Introducing the new console experience for AWS WAF

Post Syndicated from Harith Gaddamanugu original https://aws.amazon.com/blogs/security/introducing-the-new-console-experience-for-aws-waf/

Protecting publicly facing web applications can be challenging due to the constantly evolving threat landscape. You must defend against sophisticated threats, including zero-day vulnerabilities, automated events, and changing compliance requirements. Navigating through consoles and selecting the protections best suited to your use case can be complicated, requiring not only security expertise but also a deep understanding of the applications you want to protect.

Today, we’re excited to share that AWS WAF has launched a new console experience designed to simplify security configuration. This enhanced interface provides an integrated security solution that provides comprehensive protection across your application landscape, featuring a streamlined single-page workflow that can reduce deployment time from hours to minutes. AWS WAF now provides pre-configured rule packs for specific workloads, automated security recommendations, and a unified dashboard for clear visibility into security status. The new console also offers flexible protection levels and integrated partner solutions to help you scale security operations effectively.

In this post, we walk you through the features of the enhanced console experience for AWS WAF. You can now select your workload type to automatically apply expert-curated protection packs, helping to maintain comprehensive protection across your workloads.

Reduce web application security implementation steps by 80 percent

The simplified interface consolidates the configuration steps into a single page, reducing the need to navigate through multiple pages. This consolidation creates an intuitive workflow that significantly reduces setup complexity. You can complete configurations that previously took hours within minutes, representing an 80 percent reduction in implementation time.

The new experience offers pre-configured security defaults and documentation, helping users of all technical abilities to effectively secure applications. When starting the setup process, you select the application category and feature focus to protect an API or web application, and AWS WAF automatically customizes the protection parameters accordingly.

AWS WAF now also integrates with AWS Marketplace through a dedicated page for direct deployment of partner solutions.

This streamlined approach, shown in Figure 1, transforms what was previously a complex, time-consuming process into a straightforward, efficient workflow that maintains robust security standards while dramatically reducing implementation time and potential configuration errors.

Figure 1: Workload specific protection

Figure 1: Workload specific protection

Simplified AWS WAF rule deployment through protection packs

AWS WAF simplifies security deployment through three configuration options, each based on AWS security expertise and ready for immediate implementation. These protection packs provide comprehensive configuration optimized for various application types.

  • Recommended: Enables recommended protections for the selected application categories and traffic sources
  • Essentials: Enables essential protections for the selected application categories and traffic sources
  • You build it: Select and customize protections from the available options to fit your needs

Implementation requires a single step: selecting the appropriate protection pack based on your security needs, as shown in Figure 2. This approach minimizes complex configurations while maintaining security standards.

Figure 2: Choosing a rule package during AWS WAF onboarding

Figure 2: Choosing a rule package during AWS WAF onboarding

Real-time monitoring, automated recommendations, and protection activity visualization

The new console features an outcome-driven dashboard, shown in Figure 3, that simplifies security monitoring by consolidating threat detection metrics, rule performance analytics, and actionable insights into a single view. Security teams can now respond to threats faster without having to navigate through multiple screens.

Figure 3: Resources and protections dashboard

Figure 3: Resources and protections dashboard

AWS Threat Intelligence enhances monitoring capabilities by analyzing two weeks of allowed traffic patterns to proactively identify potential vulnerabilities. The service examines critical traffic dimensions including IP reputation, distributed denial of service (DDoS) attacks, bot activities, anonymous IP sources, and vulnerable application traffic. When AWS WAF detects vulnerabilities, it recommends specific AWS Managed Rules to strengthen your security posture, as shown in Figure 4.

Figure 4: Automated recommendations dashboard

Figure 4: Automated recommendations dashboard

The new real-time monitoring dashboard, as shown in Figure 5, offers comprehensive security insights at a glance. It displays request counts for traffic within your specified time range and summarizes protection rules with their corresponding termination actions. A standout feature is the Sankey visualization, which maps protection activity to AWS WAF actions, helping security teams track traffic flow, identify rule interaction patterns, and optimize configurations.

Figure 5: Summary and protection activity visualization dashboard

Figure 5: Summary and protection activity visualization dashboard

Outcome driven dashboards for actionable insights

The new dashboard, shown in Figure 6, displays security metrics based on business impact. The left panel contains four main categories: traffic, bot, rule, and CAPTCHA characteristics. The right panel shows metrics within each category. Under Traffic characteristics, you can view metrics by countries, attack types, and device types.

Figure 6: New, outcome-driven dashboard

Figure 6: New, outcome-driven dashboard

Bot characteristics include detection ratio, categories, token information, signals, session thresholds, IP token reuse thresholds, and coordinated activity. Rule characteristics highlight the top 10 managed rules, while CAPTCHA characteristics show solved, abandoned, and unsolved puzzle metrics. This organized structure helps you analyze data effectively, starting with category selection and progressing to rule evaluation. You can combine categories and metrics to visualize patterns, investigate incidents, and make informed decisions. Interactive features, such as IP blocking on hover, enable immediate action. The new console experience allows you to quickly identify threats, optimize WAF rules, and maintain effective security controls based on specific needs.

Query logs from the console

The new AWS WAF console features an integrated log explorer. You can access two analysis options from the bottom of the new console page: sampled requests for immediate review or log explorer for detailed analysis. The log explorer, shown in Figure 7, requires Amazon CloudWatch logging and provides pre-built filters for rule actions and time frames, enabling quick pattern identification and trend analysis. If CloudWatch logging isn’t enabled, you can still analyze security events through sampled requests.

Figure 7: New log explorer view for traffic analysis

Figure 7: New log explorer view for traffic analysis

Availability and pricing

Starting today, these dashboards are available by default in the AWS WAF console at no additional cost to you and require no additional setup to be completed.

Customer success

Early adopters are already seeing significant benefits. Sarah Chen, Security Engineer at National Retail Corporation, reports: “With the new console, we configured protection for our PHP applications in under 10 minutes. The rule recommendations helped us identify and block sophisticated attacks targeting our applications, reducing our security incidents by 60 percent in the first month.”

Conclusion

By combining intelligent monitoring, guided configuration, and straightforward access to specialized solutions, our enhanced console helps organizations to maintain robust security postures without the complexity traditionally associated with advanced security management.

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

Harith Gaddamanugu

Harith Gaddamanugu

Harith is a Sr Edge Specialist Solutions Architect at AWS, where he architects critical infrastructure and security solutions that serve millions of users globally. With a decade of expertise in cloud perimeter protection and web acceleration, he guides large enterprises building resilient architectures. Outside work, Harith enjoys hiking and landscape photography with his family.

How AWS improves active defense to empower customers

Post Syndicated from Stephen Goodman original https://aws.amazon.com/blogs/security/how-aws-improves-active-defense-to-empower-customers/

At AWS, security is the top priority, and today we’re excited to share work we’ve been doing towards our goal to make AWS the safest place to run any workload. In earlier posts on this blog, we shared details of our internal active defense systems, like MadPot (global honeypots), Mithra (domain graph neural network), and Sonaris (network mitigations). We’re still inventing new ways to improve the effectiveness of threat intelligence and automated response to detect and help prevent attacks. Today we’ll share advancements in active defense related to malware, software vulnerabilities, and AWS resource misconfigurations. Like the other posts we linked to, these are constantly improving capabilities that our customers get just for being on the AWS network. We’ll discuss these topics in more depth at re:inforce 2025 during Innovation Talk SEC302.

Stopping malware from spreading

Financially motivated threat actors try to gain access to a wide array of networked assets. The more resources they control, the more places they can hide, and the longer they can profit from their abusive operations. As such, threat actor malware often contains modules to scan for new targets, replicate binaries over the network, and then repeat. If left unchecked, such rapidly spreading behavior can lead to network congestion, service availability loss, and data destruction. We want to help prevent this behavior to the greatest degree possible.

One effective strategy we employ is identifying the threat actor’s key infrastructure where malware is centrally controlled. We use a variety of techniques to identify, verify, track, and disrupt threat infrastructure. Using network traffic logs, honeypot interactions, and malware samples from an array of sensor positions, we mitigate botnets, abusive proxies, and peer-to-peer malware. Over the past 12 months, AWS helped prevent over 4 million malware infection attempts across 315 thousand distinct Amazon Elastic Compute Cloud (Amazon EC2) instances. By protecting workloads from these malware infections, we not only protect our network and our customers, but also the broader internet from further malware expansion.

Advancements in threat hunting and mitigating software vulnerabilities

At Amazon, we’re proud to support software vulnerability research with programs for bug bounty, vulnerability disclosure, and open source contribution. We’ve also become a more active participant in the CVE process by becoming a CVE Numbering Authority (CNA) for the software and services provided by Amazon. Thanks to the public CVE database, we see vulnerability research accelerating as reported CVEs have grown by 21 percent year-over-year since 2013, with over 40 thousand CVEs published in 2024. This virtuous cycle of finding and resolving vulnerabilities improves cyber security over time, but AWS sees threat actors searching for unresolved vulnerabilities to gain unauthorized access to resources.

We’ve expanded MadPot and Sonaris to identify and stop a broader range of malicious vulnerability scanning and exploitation activity, protecting every AWS customer from vulnerability exposure. We’ve added hundreds of new detections and MadPot service emulations to identify real attacks. As we’ve expanded our visibility, we’ve continued blocking hundreds of millions of CVE exploit attempts daily across the AWS network.

As we’ve made these active defense systems better at stopping CVE exploit attacks, the total number of attacks has gone down by over 55 percent in the last 12 months, as shown in Figure 1. There are many factors outside our control in this observation, but we’re happy to see fewer CVE exploit attacks. This trend coincides with the detection, regionalization, latency, and guardrail improvements we’ve made in 2025. No system can block everything, so fewer exploit attempts mean less risk across a wide range of workloads.

Figure 1: Chart showing the decrease in global malicious vulnerability exploit attempts

Figure 1: Chart showing the decrease in global malicious vulnerability exploit attempts

This work to identify known exploits in the wild directly benefits users of vulnerability intelligence in Amazon Inspector, which provides an Amazon Inspector score for customers to prioritize where to spend security hardening resources. This includes the most recent date of observed exploitation attempts, the MITRE ATT&CK techniques associated with the exploit activity, and the industries targeted.

Protecting architectures built on AWS

AWS actively defends compute and network resources for our customers; we also defend the distinct AWS-native resources that customers rely on. AWS access key credentials are a critical resource that allow access to customer accounts. The AWS Identity and Access Management best practices share proven techniques for customers to keep their credentials from being abused. Through active defense, we do even more to help customers who haven’t yet adopted these best practices.

Each day, AWS helps prevent an average of 167 million malicious scanning connections seeking unintentionally exposed AWS access key pairs. In case access keys are discovered through other means, we’ve expanded our protection of customer-managed IAM credentials. When our threat intelligence analytics show that a customer-managed credential is known by a threat actor, we put mitigations in place to restrict access to highly privileged operations. We also send customized notifications to help customers identify how the credential was exposed. These efforts are paying off for our customers every day; the following response is a good example of what we hear regularly:

This is a key that we already rotated a few weeks ago based on another alarm from you. It turned out that the new rotated key happened to be in your second alarm to us. So it meant that the app that the key was linked to was still leaking it.

So on Monday we sat down with the dev team, found where the app was leaking some secrets from, we patched it, I rotated all the exposed secrets (it was more than the IAM key) and we plugged in the extra security in the app.

So thanks again for those alerts, they are very precious.
– AWS Customer

In a specific case of threat activity in November and December of 2024, customers reported ransomware activity against their objects in Amazon Simple Storage Service (Amazon S3) storage. We saw that these ransom threats were highly correlated with exposed customer-managed IAM keys. We applied quarantines to the exposed keys, taking care to make sure that normal customer operations could continue safely. We re-sent our proactive notifications to customers about keys that were likely exposed, because the risk of an attack was elevated. During this period, we worked together with customers to deactivate over 30 thousand exposed credentials. Since this threat activity began, AWS has helped prevent over 943 million malicious attempts to encrypt customer Amazon S3 objects.

These credential exposure detections flow into Amazon GuardDuty Extended Threat Detection, simplifying threat detection and response operations for modern cloud environments.

Better together

The approach AWS takes to active defense shows how security can be improved by layering protections across the infrastructure stack and using threat intelligence to drive risk reduction. By building active defense into our services at no extra cost, AWS helps our customers stay protected from a wide range of threats.

While we continue to constantly improve our protections for our customers, some of our work is by nature probabilistic, because we never see inside customer workloads. We don’t apply active defense in situations where the detection is ambiguous, because that might impact our customers’ production systems. To stay secure, customers should never let down their own defenses. AWS security services like AWS Identity and Access Management (IAM), AWS Shield Advanced, AWS WAF, AWS Network Firewall, Amazon GuardDuty, and Amazon Inspector provide prevention, detection, and response that customers can configure for their unique needs. The good news is that by working together, we’re making the internet safer for everyone.

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

Stephen Goodman

Stephen Goodman

As a senior manager for Amazon active defense, Stephen leads data-driven programs to protect AWS customers and the internet from threat actors.

Tom Scholl

Tom Scholl

AWS VP and Distinguished Engineer, Tom collaborates with networks across the globe to stop cyberattacks by tracking traffic from bad actors at its source.

How to create post-quantum signatures using AWS KMS and ML-DSA

Post Syndicated from Jake Massimo original https://aws.amazon.com/blogs/security/how-to-create-post-quantum-signatures-using-aws-kms-and-ml-dsa/

As the capabilities of quantum computing evolve, AWS is committed to helping our customers stay ahead of emerging threats to public-key cryptography. Today, we’re announcing the integration of FIPS 204: Module-Lattice-Based Digital Signature Standard (ML-DSA) into AWS Key Management Service (AWS KMS). Customers can now create and use ML-DSA keys through the same familiar AWS KMS APIs they use today for digital signatures, including CreateKey, Sign, and Verify operations. This new feature is generally available and you can use ML-DSA in the following AWS Regions: US West (N. California), and Europe (Milan) with the remaining commercial Regions to follow in the coming days. This launch is part of our broader AWS post-quantum cryptography migration plan, which we covered in our recent blog post. In this post, we guide you through creating ML-DSA keys and post-quantum signatures with AWS KMS.

Many organizations use AWS KMS to cryptographically sign firmware, operating systems, applications, or other artifacts. With ML-DSA support in AWS KMS, you can now generate and use post-quantum keys for signing operations within FIPS-140-3 Level 3 certified HSMs. By implementing ML-DSA signatures now, you can help make sure that your systems remain secure throughout their operational lifetime, even if cryptographically relevant quantum computers become available. This is especially important for manufacturers who install long-lived roots of trust during production—whether embedded directly in hardware or in devices that might remain offline for extended periods. In both cases, cryptographic signatures cannot be easily updated after deployment, making post-quantum readiness critical for the entire operational lifetime of these systems.

What’s new

AWS KMS offers three new AWS KMS key specs: ML_DSA_44, ML_DSA_65, and ML_DSA_87, which you can use with the new post-quantum SigningAlgorithm ML_DSA_SHAKE_256. Like our other signing algorithms, this name includes the hash function that’s used within the signature scheme to digest messages before signing or verification. In this case, the hash function used is SHAKE256—part of the SHA-3 family of hash functions standardized by NIST in FIPS 202.

Table 1 shows the details for each key spec, including their NIST security categories and corresponding key sizes in bytes. Each ML-DSA key spec represents a balance between security strength and resource requirements. ML-DSA-44 is suitable for applications requiring security comparable to classical 128-bit encryption, while ML-DSA-65 and ML-DSA-87 provide progressively stronger security levels equivalent to classical 192-bit and 256-bit encryption, respectively. As you move up in security levels, you’ll notice corresponding increases in key and signature sizes, enabling you to choose the key spec that best matches your security needs and engineering constraints.

Key spec NIST security Level Public key (B) Private key (B) Signature (B)
ML_DSA_44 1 (equivalent to 128-bit security) 1312 2560 2420
ML_DSA_65 3 (equivalent to 192-bit security) 1952 4032 3309
ML_DSA_87 5 (equivalent to 256-bit security) 2592 4896 4627

When using the AWS KMS Sign API with a RAW MessageType, the message to be signed is limited to 4096 bytes. For messages larger than 4096 bytes, pre-processing the message outside of AWS KMS to create what’s known as µ (mu) is required to generate a smaller-sized message input to the KMS Sign API. This external mu process pre-digests the message using the public key of the ML-DSA signing key pair to create a message size of 64 bytes. To support this launch, we’ve added a new message type in the KMS Sign API—EXTERNAL_MU—that can be used with ML-DSA signing or verification calls to indicate when a message has been pre-processed using µ (mu) before submitted to AWS KMS.

In the following sections, we include more information about constructing external mu and demonstrate basic AWS KMS operations with ML-DSA. We cover key creation, signature generation and verification, and both RAW and EXTERNAL_MU signing modes. Note that the produced RAW or EXTERNAL_MU ML-DSA signatures are identical when the same message and signing key are used.

Creating ML-DSA keys

To start, create an asymmetric AWS KMS key using the AWS Command Line Interface (AWS CLI) example command:

aws kms create-key --key-spec ML_DSA_65 --key-usage SIGN_VERIFY

This command will return a response similar to the following:

{
    "KeyMetadata": {
        "Origin": "AWS_KMS",
        "KeyId": "1234abcd-12ab-34cd-56ef-1234567890ab",
        "MultiRegion": false,
        "Description": "",
        "KeyManager": "CUSTOMER",
        "Enabled": true,
        "SigningAlgorithms": [
            "ML_DSA_SHAKE_256"
        ],
        "CustomerMasterKeySpec": "ML_DSA_65",
        "KeyUsage": "SIGN_VERIFY",
        "KeySpec": "ML_DSA_65",
        "KeyState": "Enabled",
        "CreationDate": 1748371316.734,
        "Arn": "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab",
        "AWSAccountId": "111122223333"
    }
}

Make note of the KeyId or Arn value from the response; you’ll need this to reference your key in subsequent signing operations. The response confirms that the creation of an ML_DSA_65 key configured for SIGN_VERIFY operations, which will use the ML_DSA_SHAKE_256 signing algorithm for signature operations.

Signing

In this section, we include some examples of ML-DSA signing and verifying a JSON Web Token (JWT) commonly used to transfer claims between parties for web authorization. In 2021, we described how to sign and verify JWTs with Elliptic Curve Digital Signature Algorithm (ECDSA), a classic asymmetric cryptographic algorithm (see How to verify AWS KMS signatures in decoupled architectures at scale). In the following examples, the token is instead signed with an ML-DSA private key managed by AWS KMS and verified either within AWS KMS or externally using OpenSSL.

The JWT content to be signed is from section 3.1 of RFC7519. More specifically, the JWT header is:

{"typ":"JWT",
 "alg":"ML-DSA-65"}

And the JWT claim set is:

{"iss":"joe",
 "exp":1748952000,
 "http://example.com/is_root":true}

You can produce the JWT message to be signed by using the Base64URL encoding of the header and payload as:

echo -n -e '{"typ":"JWT",\015\012 "alg":"ML-DSA-65"}' | \
	basenc --base64url -w 0 | \
	sed 's/=//g' ; echo -n "." ; echo -n -e '{"iss":"joe",\015\012 "exp":1748952000,\015\012 "http://example.com/is_root":true}' | \
	basenc --base64url -w 0 | sed 's/=//g' ; echo ""

This command will output the following Base64 to be signed with ML-DSA:

eyJ0eXAiOiJKV1QiLA0KICJhbGciOiJNTC1EU0EtNjUifQ.eyJpc3MiOiJqb2UiLA0KICJleHAiOjE3NDg5NTIwMDAsDQogImh0dHA6Ly9leGFtcGxlLmNvbS9pc19yb290Ijp0cnVlfQ

Note that the following examples output the ML-DSA signature produced on the message by using the ML-DSA private key managed by AWS KMS in a binary format. You need to convert them to Base64URL to use them in JWT, but various data encryption and signing formats can use these signatures. These include Cryptographic Message Syntax (CMS), CBOR Object Signing and Encryption (COSE), or image signing encodings for UEFI and Open Titan. While converting between binary and these formats is straightforward, support for the new algorithms might not be available in common cryptographic implementations of these signing formats at the time of this writing.

RAW ML-DSA signing (no external mu)

To sign a message of less than 4096 bytes in AWS KMS with ML-DSA, you can use the AWS CLI:aws kms sign \

aws kms sign \
    --key-id <1234abcd-12ab-34cd-56ef-1234567890ab> \
    --message ' eyJ0eXAiOiJKV1QiLA0KICJhbGciOiJNTC1EU0EtNjUifQ.eyJpc3MiOiJqb2UiLA0KICJleHAiOjE3NDg5NTIwMDAsDQogImh0dHA6Ly9leGFtcGxlLmNvbS9pc19yb290Ijp0cnVlfQ' \
    --message-type RAW \
    --signing-algorithm ML_DSA_SHAKE_256 \
    --output text \
    --query Signature | base64 --decode > ExampleSignature.bin

Make sure to replace the target-key-id value of <1234abcd-12ab-34cd-56ef-1234567890ab> with your KeyId. This command will produce a signature and write it to disk as ExampleSignature.bin.

After producing the signature, you can create the complete JWT (consisting of header, payload, and signature) with a single command:

echo -n "eyJ0eXAiOiJKV1QiLA0KICJhbGciOiJNTC1EU0EtNjUifQ.eyJpc3MiOiJqb2UiLA0KICJleHAiOjE3NDg5NTIwMDAsDQogImh0dHA6Ly9leGFtcGxlLmNvbS9pc19yb290Ijp0cnVlfQ." ; \
	basenc --base64url -w 0 ExampleSignature.bin | \
	sed 's/=//g' ; echo ""

This command will output a ready-to-use JWT in the format required by RFC 7519 and signed using AWS KMS:

eyJ0eXAiOiJKV1QiLA0KICJhbGciOiJNTC1EU0EtNjUifQ.eyJpc3MiOiJqb2UiLA0KICJleHAiOjE3NDg5NTIwMDAsDQogImh0dHA6Ly9leGFtcGxlLmNvbS9pc19yb290Ijp0cnVlfQ.<base64url of the signature as per RFC7519>

External mu ML-DSA signing

Note that AWS KMS imposes a 4096-byte limit on the size of the raw message when using the Sign API to minimize the latency of the response. In cases where the message to be signed is larger than 4096 bytes or if pre-digesting the external mu has performance advantages you need, you must use the EXTERNAL_MU message type instead of RAW in AWS KMS.

Before using the EXTERNAL_MU message type with the AWS KMS Sign API, you must locally perform a pre-hash calculation on your message. So, first, retrieve the public key from AWS KMS, and convert it to DER format using the following command (replace the example key ID with a valid key ID from your AWS account):

aws kms get-public-key \
    --key-id <1234abcd-12ab-34cd-56ef-1234567890ab> \
    --output text \
    --query PublicKey | base64 --decode > public_key.der

To construct the external mu digest:

  1. Construct a message prefix (M`): M` = (domain separator || context length || context || Message).

    In this example, set the domain separator value and context length as zero; this sets the context used in the signature as the empty string, which is the default.

  2. Hash the public key then prepend it to the message prefix:
    (SHAKE256(pk) || M’).
  3. Hash to produce a 64-byte mu:
    Mu = SHAKE256(SHAKE256(pk) || M’)

You can use a single OpenSSL 3.5 command to construct the digest:

{
    openssl asn1parse -inform DER -in public_key.der -strparse 17 -noout -out - 2>/dev/null |
    openssl dgst -provider default -shake256 -xoflen 64 -binary;
    printf '\x00\x00';
    echo -n "eyJ0eXAiOiJKV1QiLA0KICJhbGciOiJNTC1EU0EtNjUifQ.eyJpc3MiOiJqb2UiLA0KICJleHAiOjE3NDg5NTIwMDAsDQogImh0dHA6Ly9leGFtcGxlLmNvbS9pc19yb290Ijp0cnVlfQ"
} | openssl dgst -provider default -shake256 -xoflen 64 -binary > mu.bin

Now you can call AWS KMS to sign the 64-byte digest to produce the ML-DSA signature in file ExampleSignature.bin, making sure to set the MessageType to EXTERNAL_MU:

aws kms sign \
    --key-id 1234abcd-12ab-34cd-56ef-1234567890ab \
    --message fileb://mu.bin \
    --message-type EXTERNAL_MU \
    --signing-algorithm ML_DSA_SHAKE_256 \
    --output text \
    --query Signature | base64 --decode > ExampleSignature.bin

The final signed JWT token is identical to the one produced previously in RAW mode.

Signature verification using AWS KMS

In this section, we show you how to verify ML-DSA signatures using AWS KMS or locally in your own environment. We assume that you have an ML-DSA signature in ExampleSignature.bin, produced on the JWT content with the private key in AWS KMS and identified with KEY_ARN.

Note that, although the following examples demonstrate signature verification using public keys directly from AWS KMS, these same principles extend to certificate-based systems, such as a private PKI, in which public keys are embedded in end-entity certificates (of the signer). In such scenarios, verifiers would first verify the identity of the signer by validating the certificate chain ties to a trusted root, then use the public key of the end-entity certificate to verify the ML-DSA signature of the content. The IETF is standardizing ML-DSA for use in X.509 certificates through RFC draft draft-ietf-lamps-dilithium-certificates.

RAW ML-DSA verification

To verify the signature using AWS KMS, you can call the following command, replacing the example key-id with the same one you used to sign.

aws kms verify \
    --key-id <1234abcd-12ab-34cd-56ef-1234567890ab> \
    --message "eyJ0eXAiOiJKV1QiLA0KICJhbGciOiJNTC1EU0EtNjUifQ.eyJpc3MiOiJqb2UiLA0KICJleHAiOjE3NDg5NTIwMDAsDQogImh0dHA6Ly9leGFtcGxlLmNvbS9pc19yb290Ijp0cnVlfQ" \
    --message-type RAW \
    --signing-algorithm ML_DSA_SHAKE_256 \
    --signature fileb://ExampleSignature.bin

The response will return:

{
    "KeyId": "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab",
    "SignatureValid": true,
    "SigningAlgorithm": "ML_DSA_SHAKE_256"
}

The verification result is stored in the SignatureValid field.

External mu ML-DSA verification

If you have the external mu digest of the JWT content in mu.bin along with the signature and the corresponding keypair in AWS KMS, you can use the digest without having access to the entire message or calculating the digest again.

aws kms verify \
    --key-id <1234abcd-12ab-34cd-56ef-1234567890ab> \
    --message fileb://mu.bin \
    --message-type EXTERNAL_MU \
    --signing-algorithm ML_DSA_SHAKE_256 \
    --signature fileb://ExampleSignature.bin

To regenerate the external mu mu.bin from the message and the public key, see the External mu ML DSA signing section above.

Local signature verification using OpenSSL 3.5

If you want to reduce AWS KMS API consumption costs and better control the use of API quotas while keeping the security of AWS KMS-generated and stored keys for ML-DSA signature generation, you can verify ML-DSA signatures locally, outside of AWS KMS.

In this example, you use OpenSSL 3.5 to verify the signature in ExampleSignature.bin. You first must fetch the DER-encoded public key from AWS KMS in file public_key.der as shown in the External mu ML DSA signing section. OpenSSL 3.5 can then verify the signature on the message by using the public key.

echo -n "eyJ0eXAiOiJKV1QiLA0KICJhbGciOiJNTC1EU0EtNjUifQ.eyJpc3MiOiJqb2UiLA0KICJleHAiOjE3NDg5NTIwMDAsDQogImh0dHA6Ly9leGFtcGxlLmNvbS9pc19yb290Ijp0cnVlfQ" | \
	openssl dgst -verify public_key.der -signature ExampleSignature.bin

Successful verification will output: Verified OK

Conclusion

Today’s launch of ML-DSA support in AWS KMS marks an important milestone in our commitment to post-quantum cryptography. With three different security levels of ML-DSA in both raw and external digest modes, you have flexible options to meet your security requirements while preparing for the quantum computing era. The seamless integration with existing AWS KMS APIs makes it straightforward to incorporate quantum-resistant signatures into your applications today. This implementation is particularly valuable if you need to:

  • Meet FIPS 140-3 compliance requirements when using post-quantum cryptography.
  • Sign code, artifacts, documents or other data that need to remain trusted and verifiable for many years into the future, including the period after cryptographically relevant quantum computers exist.
  • Start post-quantum cryptography testing as part of your application development process using a cryptographic service such as AWS KMS that has previously been approved for use.

Learn more about post-quantum cryptography in general and the overall AWS plan to migrate to post-quantum cryptography.

Jake Massimo

Jake Massimo

Jake is an Applied Scientist on the AWS Cryptography team, where he bridges Amazon with the global cryptographic community through active participation in international conferences, academic research, and standards organizations. His work focuses on advancing the adoption of post-quantum cryptographic technology at cloud scale. Currently, he leads the development of optimized and formally verified post-quantum algorithms within the AWS cryptographic library.

Panos Kampanakis

Panos Kampanakis

Panos has extensive experience with cyber security, applied cryptography, security automation, and vulnerability management. In his professional career, he has trained and presented on various security topics at technical events for numerous years. He has co-authored cybersecurity publications and participated in various security standards bodies to provide common interoperable protocols and languages for security information sharing, cryptography, and PKI.

Mayank Ambaliya

Mayank Ambaliya

Mayank is a Software Development Manager at AWS Key Management Service (AWS KMS), where he leads development of AWS KMS cryptographic APIs and custom key stores. Mayank has experience developing customer facing cryptographic APIs and cryptographic SDKs for AWS CloudHSM. Recently, he has been working on post-quantum algorithm support in AWS KMS and adding new cryptographic APIs in AWS KMS.t