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How to use the AWS Workload Credentials Provider for cross-account secret retrieval and prefetching secrets

1 July 2026 at 17:56

If you manage secrets across multiple AWS accounts or need faster secret access for latency-sensitive applications, this post shows you how to meet those requirements using two new features of the AWS Workload Credentials Provider (provider). You will learn how to configure role chaining for cross-account secret retrieval and prefetching of secrets to reduce cold-start latency.

By using role chaining, you can access secrets across AWS accounts through a single provider instance by assuming AWS Identity and Access Management (IAM) roles. Prefetching populates the provider’s in-memory cache with secrets at startup so your application can retrieve secrets without waiting for the first request to trigger a network call at runtime.

What is the AWS Workload Credentials Provider?

AWS Secrets Manager stores and rotates credentials, API keys, and other secrets. The AWS Workload Credentials Provider is a client-side HTTP service that retrieves and caches secrets locally. This reduces latency, improves availability during transient failures, and lowers costs. It supports post-quantum TLS by default, requires no language-specific SDK, and works across Amazon Elastic Compute Cloud (Amazon EC2), Amazon Elastic Container Service (Amazon ECS), Amazon Elastic Kubernetes Service (Amazon EKS), and AWS Lambda. For more details, see the Workload Credentials Provider documentation and GitHub repository.

Security considerations

The Server-Side Requst Forger (SSRF) token prevents unauthorized processes from accessing the provider’s HTTP endpoint. Only applications that can read the token file can retrieve secrets through the provider.

Any identity that can access the provider’s endpoint and SSRF token can retrieve secrets through role chaining. This means users with compute environment access can retrieve cross-account secrets when role assumption is configured. Scope the target role’s permissions to only the secrets required by following the principle of least privilege.

For prefetching, secrets are loaded into the provider’s in-memory cache at startup. Any process that can reach the provider’s localhost endpoint and provide a valid SSRF token can retrieve prefetched secrets from the cache.

Cross-account secret retrieval with role chaining

Organizations might store secrets in a dedicated AWS account, or need to share one secret across applications in different accounts. Until now, cross-account retrieval through the provider required attaching resource-based policies directly to each secret. Some customers prefer IAM role assumption. Before this feature, you had to deploy multiple provider instances with different credentials or build custom credential-switching logic. The provider now supports both approaches: resource-based policies and IAM role assumption. While role assumption is especially useful for cross-account scenarios, it also helps within the same account when secrets are protected by different customer-managed KMS keys.

When you include the roleArn query parameter in a request, the provider uses AWS Security Token Service (AWS STS) AssumeRole to obtain temporary credentials for the specified role and retrieves the secret with those credentials. The provider creates and caches a separate client for each role ARN, so subsequent requests to the same role reuse the existing client. Each role client maintains its own independent cache.

Note: The source account runs the Workload Credentials Provider and your application. The target account contains the secret you want to retrieve. A single provider instance in the source account can assume roles in one or more target accounts.

Prerequisites

  • A Workload Credentials Provider built and installed in your environment (see the README for build instructions)
  • AWS credentials configured in your compute environment with permission to call sts:AssumeRole on the target role ARN
    • If you also retrieve secrets from the source account through the provider, the credentials need secretsmanager:GetSecretValue and secretsmanager:DescribeSecret permissions for those secrets
  • A secret in a target AWS account that you want to retrieve
  • An IAM role in the target account with a trust policy that allows the provider’s identity to assume it

To build the Workload Credentials Provider

The provider is written in Rust and compiles to a single executable. The following steps are for an RPM-based system such as Amazon Linux 2023:

  1. Install build dependencies:
    sudo yum -y groupinstall "Development Tools"
  2. Install Rust:
    curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
    source "$HOME/.cargo/env"
  3. Clone the repository and build the provider (use the latest tag available):
    git clone --branch <git tag> https://github.com/aws/aws-workload-credentials-provider.git
    cd aws-workload-credentials-provider
    cargo build --release

The compiled binary is at target/release/aws-workload-credentials-provider.

To install the Workload Credentials Provider on Amazon EC2

After building the provider, install it as a system service on your EC2 instance and configure access to the SSRF token.

  1. After configuring your config.toml file (see Configuration options section), run the install script to deploy the provider as a systemd service and generate the SSRF token:
    cd aws_workload_credentials_provider_common/configuration
    sudo ./install --config config.toml
  2. Add your application user to the aws-wcp-token group. This grants your application permission to read the SSRF token file, which is required for all secret retrieval requests:
    sudo usermod -aG aws-wcp-token <APP_USER>

To install on Amazon ECS, Amazon EKS, or Lambda, see the installation instructions in the GitHub repository.

To verify the installation

  1. Check that the provider is running:
    curl -v -H \
        "X-Aws-Parameters-Secrets-Token: $(</var/run/awssmatoken)" \
        'http://localhost:2773/secretsmanager/get?secretId=<YOUR_SECRET_ID>'
  2. You’ll receive a JSON response with the secret value. If you see a connection refused error, check that the provider process is running. If you see a 401 or 403 error, verify the SSRF token file is readable and that the provider’s IAM credentials have secretsmanager:GetSecretValue and secretsmanager:DescribeSecret permissions.

Required permissions

The provider’s base IAM identity requires:

  • sts:AssumeRole on the target role ARN

The target role requires:

  • secretsmanager:GetSecretValue
  • secretsmanager:DescribeSecret

To configure the target account IAM role

Create an IAM role in the target account with a trust policy that allows the provider’s identity in the source account to assume it. Then attach a policy that grants access to the required secrets.

  1. Create an IAM role in the target account with a trust policy that allows the provider’s identity in the source account to assume it.
    {
        "Version": "2012-10-17",
        "Statement": [
            {
                "Effect": "Allow",
                "Principal": {
                    "AWS": "arn:aws:iam::111111111111:role/WCProviderRole"
                },
                "Action": "sts:AssumeRole"
            }
        ]
    }
    
  2. Attach a policy to this role that grants access to the secret:
{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "secretsmanager:GetSecretValue",
                "secretsmanager:DescribeSecret"
            ],
            "Resource": "arn:aws:secretsmanager:us-east-1:222222222222:secret:MyDatabaseSecret"
        }
    ]
}

To configure the source account IAM role

Before the provider can assume the role you created in the target account, grant it permission to call sts:AssumeRole. Attach the following policy to the provider’s IAM role in the source account:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": "sts:AssumeRole",
            "Resource": "arn:aws:iam::222222222222:role/CrossAccountSecretAccessRole"
        }
    ]
}

To retrieve the cross-account secret

Call the Workload Credentials Provider endpoint with the roleArn parameter. The following curl example shows how to retrieve a secret using a different IAM role:

curl -v -H "X-Aws-Parameters-Secrets-Token: $(</var/run/awssmatoken)" 'http://localhost:2773/secretsmanager/get?secretId=MyDatabaseSecret&roleArn=arn:aws:iam::222222222222:role/CrossAccountSecretAccessRole'

The following Python example shows the same operation:

import requests

def get_secret_cross_account():
    role_arn = "arn:aws:iam::222222222222:role/CrossAccountSecretAccessRole"
    url = f"http://localhost:2773/secretsmanager/get?secretId=MyDatabaseSecret&roleArn={role_arn}"

    with open('/var/run/awssmatoken') as fp:
        token = fp.read()

    headers = {
        "X-Aws-Parameters-Secrets-Token": token.strip()
    }

    response = requests.get(url, headers=headers)

    if response.status_code == 200:
        return response.text
    else:
        raise Exception(f"Status code {response.status_code} - {response.text}")

You can configure the maximum number of simultaneous assumed roles with the max_roles option in the provider’s TOML configuration file. The default is 20, and the range is 1–20.

Prefetching secrets at startup

By default, the Workload Credentials Provider populates its cache lazily—the first request for a secret triggers a network call to Secrets Manager. Prefetching reduces this cold-start latency by loading secrets at startup.

How prefetching works

You can configure prefetching by adding a [capabilities.secrets_manager.prefetch] section to the provider’s TOML configuration file. You can specify secrets to prefetch in two ways:

  • Explicit secrets – List specific secret IDs or ARNs using [[capabilities.secrets_manager.prefetch.secrets]] entries.
  • Tag-based discovery – Discover secrets by tag key using [[capabilities.secrets_manager.prefetch.filter_tags]] entries. The provider calls BatchGetSecretValue with tag key filters to find and cache all matching secrets.

You can use both methods together. Each entry optionally accepts a role_arn field for cross-account prefetching through role chaining.

Required permissions

The following permissions are required on the IAM role that performs the prefetch, depending on whether the secrets are in the source account or a target account.

  • secretsmanager:BatchGetSecretValue – Required on the source account role for source-account secrets, or on the target role for cross-account secrets
  • secretsmanager:ListSecrets – Required when using tag-based discovery (filter_tags), on whichever role is performing the discovery

Configuration options

You can tune prefetch behavior with the following options in the [capabilities.secrets_manager.prefetch] section of your TOML configuration file:

  • cache_buffer_ratio – The maximum fraction of the cache to fill per caching client during prefetch, in the range 0.1–1.0. The default is 0.8. For example, if your cache holds 100 secrets, a ratio of 0.8 prefetches up to 80, leaving room for 20 on-demand secrets to be cached.
  • max_jitter_seconds – The maximum random delay in seconds before starting the prefetch task, in the range 0–10. The default is 0 (no jitter). Use this to prevent fleet-wide synchronized API calls when deploying across many instances.

Example: Prefetch with explicit secrets

The following configuration prefetches two secrets at startup, one from the source account and one from a different account using role chaining:

[capabilities.secrets_manager.prefetch]
secrets = [
    { secret_id = "arn:aws:secretsmanager:us-east-1:111111111111:secret:MySecret-AbCdEf" },
    { secret_id = "cross-account-secret", role_arn = "arn:aws:iam::222222222222:role/CrossAccountSecretAccessRole" }
]

Example: Prefetch with tag-based discovery

The following configuration discovers and caches all secrets tagged with the Environment key, and all secrets tagged with the Team key in a different account:

[capabilities.secrets_manager.prefetch]
filter_tags = [
    { key = "Environment" },
    { key = "Team", role_arn = "arn:aws:iam::222222222222:role/CrossAccountSecretAccessRole" },
]

Example: Full configuration

The following example shows a complete provider configuration that combines both features:

[logging]
log_level = "info"

[capabilities.secrets_manager]
http_port = 2773
region = "us-east-1"

[capabilities.secrets_manager.cache]
ttl_seconds = 300

[capabilities.secrets_manager.prefetch]
cache_buffer_ratio = 0.6
max_jitter_seconds = 5
secrets = [
    { secret_id = "arn:aws:secretsmanager:us-east-1:111111111111:secret:MySecret-AbCdEf" },
    { secret_id = "arn:aws:secretsmanager:us-east-1:222222222222:secret:CrossAccount-AbCdEf", role_arn = "arn:aws:iam::222222222222:role/CrossAccountSecretAccessRole" },
]
filter_tags = [
    { key = "Environment" },
    { key = "Team", role_arn = "arn:aws:iam::222222222222:role/CrossAccountSecretAccessRole" },
]

Start the provider with your configuration file:

./aws-workload-credentials-provider sm start --config config.toml

Conclusion

This post showed you how to use role chaining for cross-account secret retrieval and prefetching to reduce cold-start latency. Role chaining simplifies multi-account architectures—a single provider instance can retrieve secrets across accounts using IAM role assumption. Prefetching reduces cold-start latency by populating the provider’s cache before your application makes its first request. Combined, these features let you run the Workload Credentials Provider across multiple accounts with faster secret access.

Further reading

Submit feedback in the comments below, or contact AWS Support with questions.


Derik Wang

Derik Wang

Derik is a Software Engineer on the AWS Secrets Manager team.

Paras Dhawan

Paras Dhawan

Paras is a Software Development Manager for AWS Secrets Manager, based in Seattle. Paras joined AWS in 2017 and has spent his career across AWS Identity, AWS Cryptography, and Credentials Distribution Systems. He is passionate to innovate, solve and simplify customer problems related to security, access, authorization and beyond.

Security posture improvement in the AI era

1 May 2026 at 22:58

It’s only been a few weeks since Anthropic announced the Claude Mythos Preview model and launched Project Glasswing with AWS and other leading organizations. This has generated a lot of discussion about the future of cybersecurity and what the ever-increasing capabilities of foundation models mean to organizations.

As AWS CISO Amy Herzog pointed out in the Project Glasswing announcement, “At AWS, we build defenses before threats emerge, from our custom silicon up through the technology stack. Security isn’t a phase for us; it’s continuous and embedded in everything we do.”

Read more from Amy about this in Building AI defenses at scale: Before the threats emerge.

While the discussion around the future of cybersecurity is important, the only thing we know for certain is that organizations need to be able to react quickly to the rapid changes AI is bringing to technology and business in general. And you can’t react quickly if your security fundamentals aren’t dialed in.

The security hygiene gap

It’s easy to assume you have the foundational security elements covered, or to overlook some completely. Basic security use cases like identity management, threat detection, vulnerability management, data protection, and network security can be inconsistently implemented across cloud environments. While AI is reshaping the security landscape, strong security fundamentals continue to be essential for every organization, regardless of size or industry.

These are the security basics that matter whether or not you’re adopting AI: patching consistently, enforcing least-privilege access, enabling logging and monitoring, encrypting data at rest and in transit, and reviewing security configurations regularly. When these fundamentals are in place, you’re better positioned to take advantage of AI-driven tools and respond to newly discovered vulnerabilities, wherever they come from.

While the concepts that drive security fundamentals are universal, implementing them in your environment is best done with an understanding of the context unique to your organization. That’s why we have a multitude of freely available materials—like the AWS Well-Architected Framework—that you can use to help ask the right questions and implement changes in your environment. We also offer programs like the Security Health Improvement Program (SHIP) to help you improve your security posture through prescriptive guidance and continuous improvement.

What is the Security Health Improvement Program (SHIP)?

SHIP is a no-cost program available to every AWS customer, regardless of support tier. SHIP provides a proven, data-driven methodology to:

  • Assess your current security posture using data from your AWS environment
  • Identify specific opportunities to improve across 10 core security use cases
  • Build a prioritized action plan tailored to your environment
  • Establish a mechanism for continuous security improvement

The program is led by AWS Solutions Architects and Technical Account Managers who take you through a personalized report, contextualize findings for your environment, and help you build a prioritized action plan.

Why SHIP matters in the AI era

Project Glasswing highlights an important shift: AI-powered tools are accelerating the pace of vulnerability discovery, which means organizations need to be prepared to assess and respond to findings and changing situations faster than before. In addition to external factors, as organizations adopt AI—whether deploying foundation models, building agentic workflows, or using AI-powered services—how they implement their security controls must change as well. A strong security foundation is what makes confident AI adoption possible.

Here’s how SHIP helps:

Address foundational security gaps proactively

SHIP uses a data-driven methodology to identify opportunities to improve and optimize across 10 core security use cases: threat detection, cloud security posture management, application security testing, configuration management, access governance, vulnerability management, application protection, network security, encryption, and secrets management. The program includes a SHIP assessment to identify critical security findings related to your current security posture, so your team can build a prioritized roadmap for improvement tailored to your environment.

Establish the security baseline AI workloads require

Before you deploy your first model on Amazon Bedrock or build agentic workflows with Amazon Bedrock AgentCore, you need confidence that your underlying infrastructure follows security best practices. SHIP uses actual data from your environment to provide prescriptive, specific guidance rather than generic security recommendations. This is especially relevant as AI-driven vulnerability discovery tools become more widely available: organizations with strong baselines will be able to act on new findings quickly and effectively.

Build a mechanism for continuous security improvement

As AI capabilities evolve, organizations benefit from having a repeatable process to assess and strengthen their security posture over time. SHIP establishes the methodology and mechanisms for your team to continuously assess, prioritize, and improve. By building this operational capability, you’re strengthening your organization’s ability to adapt and contributing to broader industry resilience. As the cybersecurity community integrates AI into defense strategies, SHIP helps you maintain foundational best practices so you can adopt these innovations effectively and with confidence.

Getting started is straightforward

SHIP is available today, at no cost, to every AWS customer. Here’s how to get started:

  1. Talk to your AWS account team. Ask about scheduling a SHIP engagement, or request one directly on the SHIP page.
  2. Attend a SHIP Activation Day. AWS regularly hosts hands-on workshops where you can run the SHIP assessment with AWS Solutions Architects and start building your improvement plan.
  3. Explore the prescriptive guidance. Consult the AWS Well-Architected Framework – Security Lens for documentation, reference architectures, and implementation guides you can start using today.

Take the next step together

AWS is committed to being the most secure cloud, from our participation in Project Glasswing to the security embedded in every layer of our infrastructure. Security is a shared responsibility, and programs like SHIP give customers the tools, guidance, and support to strengthen their security foundations so they can build confidently, no matter what comes next.

Ready to improve your security posture? Contact your AWS account team to schedule a SHIP engagement, or visit the SHIP resources page to learn more.

Celeste Bishop

Celeste Bishop

Celeste is a Senior Security Specialist at AWS, based in Austin, Texas. Over the past five years, she has held a range of security-focused roles spanning field and product marketing, developer relations, and executive engagement. She partners closely with customers, security leaders, and field teams to help organizations operate securely in the cloud. Celeste holds a Bachelor’s in Economics from the University of Texas at Austin.

Protecting your secrets from tomorrow’s quantum risks

24 April 2026 at 20:53

As outlined in the AWS post-quantum cryptography (PQC) migration plan, addressing the risk of harvest now, decrypt later (HNDL) attack is an important part of your post-quantum plan. Upgrading the client-side of your workloads to support quantum-resistant confidentiality is an important aspect of your side of the PQC shared responsibility model. Timelines to plan and execute your PQC upgrades vary by region and by industry and will depend on your own business risk profile. To learn more, see the AWS PQC frequently asked questions.

AWS Secrets Manager uses SSL/TLS to communicate with AWS resources, currently supporting TLS 1.2 and 1.3 in all AWS Regions. The service supports using TLS 1.3 with hybrid post-quantum key exchange for clients that support this capability. The hybrid post-quantum approach establishes TLS connections by combining traditional cryptography (such as X25519) with post-quantum algorithms (ML-KEM), and helps to protect your secrets against both current classical attacks and future quantum computer threats. Regardless of how your workload accesses Secrets Manager, this client-side software upgrade is the only action you need to take to address risk to secrets from HNDL. Your secrets at rest are already encrypted using keys managed by AWS Key Management Service (AWS KMS). Properly implemented symmetric encryption is considered quantum-resistant; asymmetric cryptography faces quantum threats. To learn more, watch AWS re:Inforce 2025 – Post-Quantum Cryptography Demystified.

To reduce builder effort for client-side upgrades, we’re pleased to announce the following Secrets Manager clients now enable and prefer post-quantum TLS when initiating connections to Secrets Manager: Secrets Manager Agent (v2.0.0 or later), the AWS Lambda extension (v19 or later) and the Secrets Manager CSI Driver (v2.0.0 or later). For SDK-based clients, hybrid post-quantum key exchange is available in supported AWS SDKs. Enablement requirements vary by language, version, and operating system. See the following table for your SDK client.

This launch is part of the ongoing commitment AWS has made to migrate systems to post-quantum cryptography and making it straightforward for our customers to do the same. See Post-Quantum Cryptography to learn more.

Client hybrid post-quantum key exchange requirements

The following table summarizes the behavior for each client. When the client is upgraded to support hybrid post-quantum key exchange, the Secrets Manager service endpoint automatically selects it during the TLS handshake. Upgrading to the versions listed in the table is the only action you need to take for your workload to begin using hybrid post-quantum key exchange when calling Secrets Manager APIs.

Client Requirements
Secrets Manager Agent Hybrid PQ key exchange in TLS preferred by default (v2.0.0 and later)
AWS Lambda extension Hybrid PQ key exchange in TLS preferred by default (Version 19 and later)
Secrets Manager CSI Driver Hybrid PQ key exchange in TLS preferred by default (v2.0.0 and later)
AWS SDK for Rust Hybrid PQ key exchange in TLS preferred by default (releases after August 29, 2025)
AWS SDK for Go Hybrid PQ key exchange in TLS preferred by default (Go v1.24 and later)
AWS SDK for Node.js Hybrid PQ key exchange in TLS preferred by default (Node.js v22.20 and v24.9.0 and later)
AWS SDK for Kotlin Hybrid PQ key exchange in TLS preferred by default on Linux (v1.5.78 and later)
AWS SDK for Python The AWS SDK for Python (boto3) uses the OS-provided OpenSSL for TLS.
Hybrid PQ key exchange in TLS requires running on a system with OpenSSL 3.5 or later installed.
AWS SDK for Java v2 AWS SDK for Java v2 requires an AWS CRT HTTP client that supports PQ TLS when configured using postQuantumTlsEnabled.
Secrets Manager caching clients The Secrets Manager caching libraries are built on the AWS SDKs and inherit their TLS behavior. Note for Java: The JDBC driver flag and Java Caching flag must be set to enable Hybrid PQ key exchange in TLS.

If you’re using the Secrets Manager Agent, the Lambda extension, or the CSI Driver, upgrade to the listed version to use hybrid post-quantum key exchange in TLS as the default. Customers using the AWS SDK for Rust, Go, or Node.js at the versions listed in the table are already upgraded and no additional action is required. The SDK will select the hybrid post-quantum key exchange for API calls. For customers using the AWS SDK for Python, hybrid post-quantum key exchange in TLS requires OpenSSL 3.5 or later to be present on the host system. Guidance on verifying and enabling this is available in the AWS Secrets Manager documentation. For customers using the AWS SDK for Java v2, hybrid post-quantum key exchange in TLS requires using the AWS CRT HTTP client. The postQuantumTlsEnabled(true) must be set on the CRT client to enable hybrid post-quantum key exchange in TLS.

After your client versions meet the requirements listed in the table, you can verify that your connections are actively using hybrid post-quantum key exchange.

How to verify your connection uses hybrid post-quantum key exchange

With hybrid post-quantum key exchange using ML-KEM now enabled by default for Secrets Manager clients (see the preceding table), most customers will not need ongoing monitoring to verify correct behavior or detect regressions. However, security teams and compliance officers might want to confirm that their Secrets Manager API calls are negotiating the hybrid key exchange. On the server side, you can confirm hybrid post-quantum key exchange in TLS by using AWS CloudTrail. On the client side, you can inspect TLS handshake details using a utility like Wireshark or by using developer tools built into major web browsers.

Verification is a two-step process: first, fetch a secret using your Secrets Manager client to generate a GetSecretValue API call, then confirm in AWS CloudTrail that the call negotiated hybrid post-quantum key exchange.

Fetch your secret using your Secrets Manager client

The following examples show how to retrieve your secret using the Secrets Manager Agent, Lambda extension, and CSI Driver—each of which will automatically negotiate hybrid post-quantum key exchange when calling the GetSecretValue API.

To verify hybrid post-quantum TLS with Secrets Manager Agent on EC2 instance:
Install the agent on your Amazon Elastic Compute Cloud (Amazon EC2) instance and use it as a client to fetch your secret.

  1. Follow the instructions for AWS Secrets Manager Agent.
  2. Ensure that your EC2 instance profile has the permission for secretsmanager:GetSecretValue to fetch the secret.
  3. Connect to your private EC2 instance.
  4. Install the agent on your EC2 instance.
  5. Use the agent to fetch your secret.
    curl -H “X-Aws-Parameters-Secrets-Token: $(</tmp/awssmatoken)” localhost:2773/secretsmanager/get?secretId=<YOUR-SECRET-ARN>
  6. Wait for about 5 minutes for CloudTrail to deliver the logs.
  7. Go to the CloudTrail event history and search for the event GetSecretValue.

To verify hybrid post-quantum TLS with Lambda extension:
Use the AWS parameters and Secrets Manager Lambda extension to create a Lambda function that will consume your secrets from Secrets Manager using direct API calls.

  1. Follow Using the AWS parameters and secrets Lambda extension to create the Lambda layer and the Lambda function.
  2. Select the latest extension version.
  3. Wait for about 5 minutes for CloudTrail to deliver the logs.
  4. Go to the CloudTrail event history and search for the event GetSecretValue.

To verify hybrid post-quantum TLS with CSI driver on Amazon EKS:
On your Amazon Elastic Kubernetes Service (Amazon EKS) cluster, use the AWS Secrets Store CSI Driver provider to fetch secrets from Secrets Manager in Kubernetes pods:

  1. Confirm the installed add-on version is 2.0.0 or later.
    eksctl get addon --cluster <CLUSTER-NAME> --name aws-secrets-store-csi-driver-provider
  2. Trigger a secret retrieval by restarting a pod that mounts a secret, or deploying a new one.
  3. Wait for about 5 minutes for CloudTrail to deliver the logs.
  4. Go to the CloudTrail event history and search for the event GetSecretValue.

Confirm hybrid post-quantum key exchange using CloudTrail

CloudTrail logs include a tlsDetails field for Secrets Manager API calls. When hybrid post-quantum key exchange in TLS is active, the keyExchange field in tlsDetails will show X25519MLKEM768. Each CloudTrail record includes a tlsDetails field that contains the cipher suite and, where available, the key exchange group negotiated during the TLS handshake.

You can work with CloudTrail event history using the AWS Management Console for CloudTrail or the AWS Command Line Interface (AWS CLI).

To look up CloudTrail events using the console:

  1. Verify you are in the correct AWS Region.
  2. Open the CloudTrail console and select Event History.
  3. Under Lookup attributes filter, select Event name and GetSecretValue.
    Figure 1: Search CloudTrail event history by event name

    Figure 1: Search CloudTrail event history by event name

  4. Select your event.
    Figure 2: Select the event

    Figure 2: Select the event

  5. View the output in the Event Record section of the page.
    Figure 3: CloudTrail - GetSecretValue event

    Figure 3: CloudTrail – GetSecretValue event

To look up CloudTrail events using AWS CLI :
Using AWS CLI, select the last events and look at the output.

aws cloudtrail lookup-events \
--lookup-attributes AttributeKey=EventName,AttributeValue=GetSecretValue \
--max-results 5 \
--region <YOUR-REGION> \
--query 'Events[0].CloudTrailEvent' \
--output text

Example of CloudTrail Event for GetSecretValue API call:

In the following example, the userAgent field reflects what it used as a client to connect to Secrets Manager.

Note: The userAgent value depends on the client you use.

{
    "eventVersion": "1.11",
    "userIdentity": {
        "type": "AssumedRole",
        "principalId": "AROA123456789EXAMPLE:i-0c1a23fc456b7ab89",
        "arn": "arn:aws:sts::111122223333:assumed-role/YOUR-EC2-INSTANCE-PROFILE/i-0c1a23fc456b7ab89",
        "accountId": "111122223333",
        "accessKeyId": "ASIAIOSFODNN7EXAMPLE",
        "sessionContext": {
            "sessionIssuer": {
                "type": "Role",
                "principalId": "AROA123456789EXAMPLE",
                "arn": "arn:aws:iam::111122223333:role/YOUR-EC2-INSTANCE-PROFILE",
                "accountId": "111122223333",
                "userName": "YOUR-EC2-INSTANCE-PROFILE"
            },
            "attributes": {
                "creationDate": "2026-03-27T17:08:37Z",
                "mfaAuthenticated": "false"
            },
            "ec2RoleDelivery": "2.0"
        },
        "inScopeOf": {
            "issuerType": "AWS::EC2::Instance",
            "credentialsIssuedTo": "arn:aws:ec2:eu-west-2:111122223333:instance/i-0c1a23fc456b7ab89"
        }
    },
    "eventTime": "2026-03-27T17:12:54Z",
    "eventSource": "secretsmanager.amazonaws.com",
    "eventName": "GetSecretValue",
    "awsRegion": "eu-west-2",
    "sourceIPAddress": "1.2.3.4",
    "userAgent": "aws-sdk-rust/1.3.14 os/linux lang/rust/1.94.1 aws-secrets-manager-agent/2.0.0",
    "requestParameters": {
        "secretId": "arn:aws:secretsmanager:eu-west-2:111122223333:secret:your-secret"
    },
    "responseElements": null,
    "requestID": "027507ea-f377-43d9-bf2f-646d4dc19223",
    "eventID": "f9c3ed0f-81f5-450b-a561-2b9e54fa9e73",
    "readOnly": true,
    "resources": [
        {
            "accountId": "111122223333",
            "type": "AWS::SecretsManager::Secret",
            "ARN": "arn:aws:secretsmanager:eu-west-2:111122223333:secret:your-secret"
        }
    ],
    "eventType": "AwsApiCall",
    "managementEvent": true,
    "recipientAccountId": "111122223333",
    "eventCategory": "Management",
    "tlsDetails": {
        "tlsVersion": "TLSv1.3",
        "cipherSuite": "TLS_AES_128_GCM_SHA256",
        "clientProvidedHostHeader": "secretsmanager.eu-west-2.amazonaws.com",
        "keyExchange": "X25519MLKEM768"
    }
}

If the keyExchange field shows X25519MLKEM768, then hybrid post-quantum key exchange in TLS is active. If it shows a traditional algorithm such as X25519, the client is not advertising ML-KEM support, and you should check the client version and configuration.

Troubleshooting

If your Secrets Manager API calls aren’t negotiating X25519MLKEM768 after updating your clients, check your SDK version, OpenSSL version (Python), and firewall or proxy configuration as shown in the Client Hybrid Post-Quantum Key Exchange Requirements section near the beginning of this post.

What’s next

This launch is one step in a broader migration. AWS is continuing to roll out ML-KEM support across AWS service HTTPS endpoints as part of Workstream 2 of the AWS PQC Migration Plan, with a target of full coverage across public AWS endpoints.

Support for CRYSTALS-Kyber, the pre-standardization predecessor to ML-KEM, is phasing out across AWS endpoints in 2026. Customers on older SDK versions that advertise only CRYSTALS-Kyber support will fall back gracefully to traditional TLS rather than negotiate the deprecated algorithm. To avoid this fallback, upgrade to the SDK versions listed in this post.

The journey of PQC migration extends beyond confidentiality of data in transit. To stay informed about the latest developments in the AWS PQC journey and your side of shared responsibility, follow the AWS Post-Quantum Cryptography page.

Conclusion

AWS Secrets Manager now enables hybrid post-quantum key exchange using ML-KEM by default to help protect your secrets and support your compliance efforts. This update requires no code changes or configuration updates for customers using the latest client versions.

This post covered how AWS Secrets Manager uses hybrid post-quantum cryptography to secure TLS connections, which clients support this capability, and how to verify that your connections are protected against harvest now, decrypt later attacks.

To benefit from this announcement today:

  • Upgrade your Secrets Manager client (Agent, Lambda extension, or CSI Driver) to the latest available versions to enable hybrid post-quantum key exchange using ML-KEM
  • If your workload uses the AWS SDK instead of a caching client, upgrade your AWS SDK and underlying dependencies to the minimum versions listed in this post
  • Verify hybrid post-quantum key exchange in TLS is active by checking the keyExchange field in CloudTrail tlsDetails for your Secrets Manager API calls
  • Test end-to-end hybrid post-quantum key exchange TLS connectivity in your environment, including network paths that traverse corporate firewalls or proxies

AWS will continue rolling out post-quantum cryptography support. For information about the broader migration effort, see the AWS PQC Migration Plan. Keep an updated cryptographic inventory of your broader environment to identify other uses of traditional public-key cryptography that will require migration. The CISA Quantum-Readiness guidance and the AWS PQC Migration Plan are good starting points.

Additional resources

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P. Stéphanie Mbappe

P. Stéphanie Mbappe

Stéphanie is a Security Consultant with Amazon Web Services. She delights in assisting her customers at any step of their security journey. Stéphanie enjoys learning, designing new solutions, and sharing her knowledge with others.

Tobias Nickl

Tobias Nickl

Tobias is a Security Consultant at Amazon Web Services, specializing in security architecture and cloud transformation. He partners with AWS customers to design and implement security architectures that address both current and emerging threats. Through his work, he helps organizations build security strategies that evolve with their cloud maturity.

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