Tag Archives: AWS Key Management Service (KMS)

Quantum-resistant signing on AWS, Part 1: Build a software supply chain with ML-DSA

Post Syndicated from Harshvardhan Chunawala original https://aws.amazon.com/blogs/security/quantum-resistant-signing-on-aws-part-1-build-a-software-supply-chain-with-ml-dsa/

Software supply chain attacks have grown in both frequency and sophistication. Recent high-profile compromises of build systems and open source dependencies demonstrate that attackers increasingly target the trust mechanisms that verify software integrity. Those trust mechanisms rely on digital signature algorithms, and today many use traditional algorithms such as Rivest-Shamir-Adleman (RSA) and the Elliptic Curve Digital Signature Algorithm (ECDSA). If a sufficiently powerful quantum computer could forge these signatures, an attacker could potentially inject unauthorized code into signed artifacts, fabricate build attestations, or impersonate legitimate publishers. Using quantum-resistant signatures today defends against threats that might emerge in the future.

Since 2025, the Commercial National Security Algorithm Suite 2.0 (CNSA 2.0), published by the US National Security Agency (NSA), has required US National Security Systems (NSS) to “support and prefer” quantum-resistant signatures for software and firmware, with exclusive use mandated by 2030. The EU Cyber Resilience Act (CRA) takes full effect in December 2027. It requires manufacturers to maintain verifiable software integrity throughout a product’s lifecycle. Organizations that ship software to US federal agencies or sell products in the European market face converging deadlines that demand action now.

Amazon Web Services (AWS) provides the building blocks to construct a quantum-resistant software supply chain today using production-ready, generally available services. In this post, I show you how to combine Module-Lattice-Based Digital Signature Algorithm (ML-DSA) keys in AWS Key Management Service (AWS KMS), ML-DSA certificate hierarchies in AWS Private Certificate Authority, and ML-DSA trust anchors in AWS Identity and Access Management (IAM) Roles Anywhere into an end-to-end signing architecture for binaries, container images, and software bills of materials (SBOMs).

This post is Part 1 of a two-part series on adopting ML-DSA signatures, standardized in NIST FIPS 204 (ML-DSA) signatures, on AWS. As of Oct 2026, this series is the first end-to-end guide from any cloud provider for post-quantum signing across the software supply chain, from establishing an ML-DSA root of trust to enforcing algorithm policy across an organization. This part is for builders and walks through constructing and operating the signing pipeline. Part 2, Enforce your ML-DSA algorithm policy with SCPs and IAM, is for security and governance teams and shows how to turn the algorithm choices made here into preventive and detective controls across an organization.

Understanding the harvest now, forge later threat

After a cryptographically relevant quantum computer (CRQC) exists, the mathematical problems protecting today’s public-key cryptography can be solved efficiently. Attacks that are impractical today because of the computational complexity suddenly become practical using a CRQC. Most discussions of post-quantum cryptography (PQC) focus on the harvest now, decrypt later threat to data confidentiality. The asymmetric keys protecting data in transit can be efficiently derived using a CRQC, exposing the data that was meant to be protected. Digital signatures rely on the same asymmetric mathematical problems that a CRQC would break. This means that software supply chains face a parallel threat that targets integrity rather than confidentiality. An attacker who records signed artifacts today can forge those signatures in the future on a totally different artifact, using a CRQC.

Consider firmware signed with ECDSA P-256 and deployed to a fleet of embedded devices in 2026. These devices verify the firmware signature on every boot for their 15-year operational lifetime and can’t be recalled to re-sign after deployment. If a CRQC becomes operational in 2035, an attacker could produce a valid-looking signature over tampered firmware, and every device in the fleet would accept it as authentic on next restart. For organizations that rely on classical digital signatures as the primary mechanism for verifying software integrity, this weakens a critical link in the verification chain. This is why CNSA 2.0 specifies aggressive timelines for digital signatures: the artifacts you sign today must remain trustworthy for their full operational lifetime.

ML-DSA is designed to resist attacks from both classical and quantum computers. AWS KMS, AWS Private CA, and AWS IAM Roles Anywhere all support ML-DSA, making it possible to address the forge-later threat across your supply chain today without additional tooling.

Architecture overview: Five pillars of a quantum-resistant supply chain

The architecture comprises five trust pillars that together protect your software delivery pipeline:

  1. ML-DSA key management in AWS KMS – All signing keys are generated and protected in FIPS 140-3 Security Level 3 hardware security modules (HSMs). Private keys never leave the HSM boundary.
  2. ML-DSA public key infrastructure (PKI) through AWS Private CA – A certificate hierarchy (root CA, subordinate CA, end-entity certificates) binds ML-DSA public keys to identities, establishing who signed what. CA private keys are generated and stored in hardware-protected HSMs managed by the service and never leave the HSM boundary.
  3. Quantum-resistant workload identity (for external build agents) – For continuous integration and delivery (CI/CD) agents running outside AWS that authenticate through X.509 certificates, IAM Roles Anywhere with ML-DSA certificates ties the signer’s identity back to the same quantum-resistant root of trust.
  4. ML-DSA artifact signing – Build outputs (binaries, container image manifests, packages) are signed using AWS KMS ML-DSA keys. Signatures are stored alongside artifacts in Amazon Simple Storage Service (Amazon S3) or Amazon Elastic Container Registry (Amazon ECR).
  5. ML-DSA SBOM integrity attestation – The SBOM for each release is wrapped in an in-toto Statement that names the artifact it describes by digest, and the Statement is signed with the same ML-DSA code-signing key. This provides quantum-resistant proof that the dependency manifest hasn’t been tampered with and that it belongs to the artifact it accompanies.

These pillars create a chain of trust: AWS Private CA protects the root CA key in its own HSMs, issues certificates that bind identities to AWS KMS code-signing keys, IAM Roles Anywhere uses those certificates to authenticate build agents, and authenticated agents sign every artifact and SBOM they produce.

Figure 1: End-to-end quantum-resistant software supply chain on AWS

Figure 1: End-to-end quantum-resistant software supply chain on AWS

Figure 1 illustrates this architecture in four layers, numbered in the order you build them:

  1. Root of trust (Pillars 1 and 2) – Establish your AWS Private CA hierarchy and create your code-signing key in AWS KMS.
  2. Workload identity (Pillar 3) – Register the CA as an IAM Roles Anywhere trust anchor and issue ML-DSA certificates to build agents, ensuring the signer’s identity chains back to the same quantum-resistant root of trust.
  3. Artifact signing (Pillars 4 and 5) – Sign binaries, container images, and SBOMs using the authenticated build agent.
  4. Verification and enforcement – Validate signatures at deployment and enforce ML-DSA-only policies.

Prerequisites

To follow along, you need:

  • An AWS account with permissions to create resources in AWS KMS, AWS Private CA, IAM Roles Anywhere, and Amazon ECR.
  • AWS Command Line Interface (AWS CLI) v2 configured with appropriate credentials.
  • IAM Roles Anywhere credential helper (aws_signing_helper) v1.8.0 or later, the first release that supports ML-DSA keys and certificates, for workload authentication. Download from the IAM Roles Anywhere documentation.
  • OpenSSL 3.5 or later (required for ML-DSA signature verification and mu computation).
  • ORAS CLI v1.2 or later (for attaching Open Container Initiative (OCI) referrer artifacts to container images). Alternatively, you can use the Notation CLI with a custom plugin or any OCI-compliant client that supports the OCI Referrers API.
  • jq, for constructing and parsing the in-toto Statements used for SBOM attestation and for parsing ORAS output.
  • Amazon Inspector SBOM Generator (Sbomgen), or another tool that produces a CycloneDX JSON SBOM, for the SBOM example. Sbomgen runs only on Linux (x86-64 and ARM64), so run that step on a Linux build agent or container. It uses the registry credentials that oras login stores in the Docker config file, and it also accepts them through --username or the INSPECTOR_SBOMGEN_USERNAME and INSPECTOR_SBOMGEN_PASSWORD environment variables.
  • Java 11 or later and Apache Maven, to run the diy-code-signing-kms-private-ca sample that produces the code-signing CSR in Step 4 of Building the ML-DSA PKI foundation.
  • A container image pushed to Amazon ECR (for the container signing example).

Building the ML-DSA PKI foundation

Start by creating the certificate hierarchy that will anchor your supply chain trust. AWS Private CA generates and stores its own CA signing keys internally in hardware-protected HSMs when you create a certificate authority. Use ML-DSA-87 (NIST security category 5, defined as at least as hard to break as exhaustive key search on AES-256) for the root CA because it protects the longest-lived trust anchor. Use ML-DSA-65 (NIST security category 3) for the subordinate CA to balance security with smaller signature sizes for frequently issued certificates.

The parameter sets used here, ML-DSA-87 and ML-DSA-65, are also the approved set in the example algorithm policy that Part 2 of this series turns into enforceable controls. If your organization has standardized on a different set, substitute it in the commands that follow; the build steps don’t change.

Step 1: Create the root CA in AWS Private CA

When you specify KeyAlgorithm: ML_DSA_87, Private CA generates an ML-DSA-87 key pair internally. You don’t need to create a separate AWS KMS key for the CA.

aws acm-pca create-certificate-authority \
  --certificate-authority-configuration '{
    "KeyAlgorithm": "ML_DSA_87",
    "SigningAlgorithm": "ML_DSA_87",
    "Subject": {
      "CommonName": "PQC Supply Chain Root CA",
      "Organization": "Example Corp",
      "Country": "US"
    }
  }' \
  --certificate-authority-type ROOT

After creation, the root CA is in PENDING_CERTIFICATE state. Activate it by self-signing its certificate. This is where you set the root CA’s validity period (10 years is typical for a root):

# Retrieve the root CA's CSR
aws acm-pca get-certificate-authority-csr \
  --certificate-authority-arn <root-ca-arn> \
  --output text > root-ca.csr

# Self-sign the root CA certificate (valid for 10 years)
ROOT_CERT_ARN=$(aws acm-pca issue-certificate \
  --certificate-authority-arn <root-ca-arn> \
  --csr fileb://root-ca.csr \
  --signing-algorithm ML_DSA_87 \
  --validity Value=3650,Type=DAYS \
  --template-arn arn:aws:acm-pca:::template/RootCACertificate/V1 \
  --query CertificateArn --output text)

# Retrieve and install the self-signed root certificate
aws acm-pca get-certificate \
  --certificate-authority-arn <root-ca-arn> \
  --certificate-arn $ROOT_CERT_ARN \
  --query Certificate --output text > root-ca-cert.pem

aws acm-pca import-certificate-authority-certificate \
  --certificate-authority-arn <root-ca-arn> \
  --certificate fileb://root-ca-cert.pem

Step 2: Create a subordinate CA for code signing

aws acm-pca create-certificate-authority \
  --certificate-authority-configuration '{
    "KeyAlgorithm": "ML_DSA_65",
    "SigningAlgorithm": "ML_DSA_65",
    "Subject": {
      "CommonName": "PQC Code Signing CA",
      "Organization": "Example Corp",
      "Country": "US"
    }
  }' \
  --certificate-authority-type SUBORDINATE

After creation, the subordinate CA enters PENDING_CERTIFICATE state with no link to the root. Activate it by signing its certificate signing request (CSR) with the root CA:

# Retrieve the subordinate CA's certificate signing request
aws acm-pca get-certificate-authority-csr \
  --certificate-authority-arn <sub-ca-arn> \
  --output text > sub-ca.csr

# Sign the CSR using the root CA (this establishes the trust hierarchy)
SUB_CERT_ARN=$(aws acm-pca issue-certificate \
  --certificate-authority-arn <root-ca-arn> \
  --csr fileb://sub-ca.csr \
  --signing-algorithm ML_DSA_87 \
  --validity Value=1825,Type=DAYS \
  --template-arn arn:aws:acm-pca:::template/SubordinateCACertificate_PathLen0/V1 \
  --query CertificateArn --output text)

# Retrieve the signed certificate and import it to activate the subordinate CA
aws acm-pca get-certificate \
  --certificate-authority-arn <root-ca-arn> \
  --certificate-arn $SUB_CERT_ARN \
  --query Certificate --output text > sub-ca-cert.pem

aws acm-pca import-certificate-authority-certificate \
  --certificate-authority-arn <sub-ca-arn> \
  --certificate fileb://sub-ca-cert.pem \
  --certificate-chain fileb://root-ca-cert.pem

Step 3: Create the code-signing key in AWS KMS

Your build agents use this key to sign artifacts, so their IAM roles need the kms:Sign permission on it. The end-entity certificate issued by your subordinate CA binds an identity to this key’s public key.

aws kms create-key \
  --key-spec ML_DSA_65 \
  --key-usage SIGN_VERIFY \
  --description "PQC code-signing key for supply chain" \
  --tags TagKey=Purpose,TagValue=CodeSigning

Create an alias for convenient reference in your CI/CD scripts:

aws kms create-alias \
  --alias-name alias/pqc-code-signing \
  --target-key-id <key-id-from-above>

Step 4: Issue the end-entity code signing certificate

To issue a certificate, you need a CSR. Because the ML-DSA private key never leaves the AWS KMS HSM, you can’t generate the CSR locally with OpenSSL. Instead, you construct the CSR’s TBS (to-be-signed) structure containing your subject name and public key, sign it remotely by calling aws kms sign, and assemble the final CSR from those components.

For a working implementation that assembles an ML-DSA CSR around a KMS-managed private key and signs it with AWS KMS, see Post-quantum (ML-DSA) code signing with AWS Private CA and AWS KMS and its diy-code-signing-kms-private-ca sample on GitHub (Java, built with Maven). There is no AWS CLI-only path for this step: the CSR must be constructed and signed in code, and the sample is the reference implementation.

After you have the code-signing.csr file, issue the certificate from your subordinate CA:

# Issue a code-signing certificate valid for one year, signed by the subordinate CA using ML-DSA-65.
# Replace <sub-ca-arn> with the ARN that create-certificate-authority returned for the subordinate CA in Step 2.
CODE_SIGNING_CERT_ARN=$(aws acm-pca issue-certificate \
  --certificate-authority-arn <sub-ca-arn> \
  --csr fileb://code-signing.csr \
  --signing-algorithm ML_DSA_65 \
  --validity Value=365,Type=DAYS \
  --template-arn arn:aws:acm-pca:::template/CodeSigningCertificate/V1 \
  --query CertificateArn --output text)

# Retrieve the issued certificate
aws acm-pca get-certificate \
  --certificate-authority-arn <sub-ca-arn> \
  --certificate-arn $CODE_SIGNING_CERT_ARN \
  --query Certificate --output text > code-signing-cert.pem

This certificate binds the signer identity to the AWS KMS code-signing key material. Note that the certificate validity period (365 days in this example) determines how long verifiers can validate signatures by checking the certificate alone. AWS Private CA lets you choose the validity period of an issued certificate, as long as it ends no later than the issuing CA’s own certificate; in this example the subordinate CA certificate from Step 2 is valid for 1,825 days, so the three-year option below fits inside it. For artifacts that must remain verifiable beyond the certificate’s expiry, consider these approaches:

  • Longer certificate validity – For private PKI, code-signing certificates are commonly issued with multi-year validity (for example, Value=1095,Type=DAYS for 3 years) because you control the issuance policy.
  • Trusted timestamping (RFC 3161) – Countersign each signature with an RFC 3161 timestamp from a Time Stamping Authority (TSA) at signing time. The timestamp proves the signature was created while the certificate was valid, allowing verification indefinitely. AWS doesn’t provide a managed TSA; use a third-party TSA or operate your own.
  • Re-signing – Before a certificate expires, re-sign active artifacts with a newly issued certificate.

Distribute the certificate chain (root CA certificate, subordinate CA certificate, and end-entity certificate) to systems that need to verify your signatures.

Signing artifacts with ML-DSA in your CI/CD pipeline

With the PKI hierarchy in place, integrate ML-DSA signing into your build process. The approach depends on artifact type. ML-DSA-65 signatures are 3,309 bytes (compared to 64 bytes for ECDSA P-256), and the latency of the AWS KMS Sign operation for ML-DSA is comparable to existing asymmetric operations. The larger signature size has negligible impact when stored alongside multi-megabyte container images or packages, but is worth accounting for in size-constrained environments like embedded device images transmitted over low-bandwidth links.

Binary and package signing

Most build outputs, including compiled binaries and packages, are far larger than the 4,096-byte limit that AWS KMS places on the message passed to aws kms sign. Make the EXTERNAL_MU method your pipeline’s default: compute the 64-byte message representative (mu) externally with OpenSSL 3.5, then pass only mu to AWS KMS. This handles an artifact of any size and never needs to change as your artifacts grow. AWS KMS also accepts content directly with --message-type RAW, up to 4,096 bytes. Use RAW only for inputs whose size is fixed by construction, such as the 71-character manifest digest in the container image example that follows. An artifact that fits today is likely to outgrow the limit later, and a pipeline that depends on RAW fails when it does. Both methods produce cryptographically identical signatures. The verifier doesn’t need to know which method was used; standard ML-DSA verification applies in either case.

# Retrieve the public key
aws kms get-public-key --key-id alias/pqc-code-signing \
  --query PublicKey --output text | base64 --decode > pk.der

# Extract raw public key bytes from the DER-encoded SubjectPublicKeyInfo.
# The BIT STRING starts at offset 17 for all ML-DSA key sizes. 
# Expected output: 1,312 bytes (ML-DSA-44), 1,952 bytes (ML-DSA-65), or 2,592 bytes (ML-DSA-87).

openssl asn1parse -inform DER -in pk.der -strparse 17 -noout -out pk_raw.bin

# Compute mu per FIPS 204 Section 6.2
printf '\x00\x00' | cat - artifact.bin > m_prime.bin
openssl dgst -shake256 -xoflen 64 -binary pk_raw.bin > pk_hash.bin
cat pk_hash.bin m_prime.bin | openssl dgst -shake256 -xoflen 64 -binary > mu.bin

# Sign the mu value
aws kms sign \
  --key-id alias/pqc-code-signing \
  --message fileb://mu.bin \
  --message-type EXTERNAL_MU \
  --signing-algorithm ML_DSA_SHAKE_256 \
  --query Signature --output text | base64 --decode > artifact.bin.sig

Store the .sig file alongside the artifact in Amazon S3 or your package repository. Protect the integrity of both the artifact and its signature by enabling S3 Object Lock (WORM protection) or at minimum S3 Versioning with restricted write access. If an attacker can modify or delete either file, verification can’t be trusted. For comprehensive guidance, see Security best practices for Amazon S3.

Container image signing

For container image signing, use the OCI referrer pattern, defined in the OCI Image and Distribution Specifications v1.1. A referrer is an artifact, such as a signature or an SBOM, whose manifest names another image in its subject field. Registries that support the pattern, including Amazon ECR, return these artifacts when a client asks for an image’s referrers. This approach uses AWS KMS ML-DSA keys to generate the signature and stores it as a referrer of the image:

# Repository URI used by ORAS here and in the SBOM steps; replace the account ID and Region
ECR_URI=111122223333.dkr.ecr.us-east-1.amazonaws.com/myapp

# Authenticate ORAS to Amazon ECR
aws ecr get-login-password --region us-east-1 | \
  oras login --username AWS --password-stdin 111122223333.dkr.ecr.us-east-1.amazonaws.com

# Get the image manifest digest
IMAGE_DIGEST=$(aws ecr batch-get-image \
  --repository-name myapp \
  --image-ids imageTag=v1.2.0 \
  --query 'images[0].imageId.imageDigest' --output text)

# Sign the digest. It is a fixed 71 characters, so RAW is safe here (see Binary and package signing).
# AWS CLI v2 expects blob parameters to be base64, so write the digest to a file and pass it with fileb://
echo -n "$IMAGE_DIGEST" > digest.txt
aws kms sign \
  --key-id alias/pqc-code-signing \
  --message fileb://digest.txt \
  --message-type RAW \
  --signing-algorithm ML_DSA_SHAKE_256 \
  --query Signature --output text | base64 --decode > image.mldsa.sig

# Attach signature as OCI referrer using ORAS
oras attach $ECR_URI@$IMAGE_DIGEST \
  --artifact-type "application/vnd.example.mldsa-signature.v1" \
  image.mldsa.sig:application/octet-stream

At deployment time, your admission controller retrieves the referrer artifact and verifies the ML-DSA signature before allowing the image to run. See Verifying a container image signature before deployment later in this post for the full verification workflow and admission control implementation.

SBOM signing

A software bill of materials (SBOM) is a structured inventory of every component, library, and dependency included in a software release. It lists package names, versions, suppliers, and dependency relationships. Organizations use SBOMs to track vulnerabilities, verify license compliance, and respond quickly when a compromised component is disclosed.

Signing the SBOM file on its own proves that the inventory hasn’t been tampered with since it was signed, but not which artifact it describes. If the image signature and the SBOM signature are independent of each other, an attacker who holds a legitimately signed SBOM for a clean image can present it alongside a different signed image and claim that the two correspond. Attaching the SBOM to the image as an OCI referrer doesn’t close this gap by itself, because the subject field of a referrer manifest is set by whoever pushes the referrer; it’s a discovery mechanism, not a cryptographic binding. The binding must be inside the bytes that the signature covers.

To create that binding, wrap the SBOM in an in-toto Statement before signing it. A Statement names the artifacts it describes in its subject field, by digest, and carries the SBOM as its predicate. Because the image manifest digest is part of the signed content, a verifier can confirm that the SBOM in hand was issued for exactly the image it is about to deploy, and a swapped SBOM or a swapped digest fails verification. Embedding the SBOM in the image filesystem is another way to bind the two, because the image digest then covers the SBOM bytes. This post uses the Statement approach because it also works for SBOMs generated by scanning a finished image, for artifacts that have no filesystem such as binaries and firmware, and for images that are already in your registry, and because the SBOM stays readable from the registry without pulling the image.

Generate the SBOM with your preferred tool (such as Amazon Inspector SBOM Generator (Sbomgen) for container images), wrap it in a Statement, and sign the Statement with the same EXTERNAL_MU step you use for binaries:

# Scan the pushed image by digest so the inventory describes exactly the manifest you signed.
# Sbomgen reuses the registry login from the oras login step in the previous section.
inspector-sbomgen container --image $ECR_URI@$IMAGE_DIGEST -o sbom.json

# Wrap the SBOM in an in-toto Statement whose subject is the image manifest digest.
# This puts the digest inside the signed bytes, which binds this SBOM to this image.
jq -n \
  --arg name "$ECR_URI" \
  --arg digest "${IMAGE_DIGEST#sha256:}" \
  --slurpfile sbom sbom.json \
  '{
    "_type": "https://in-toto.io/Statement/v1",
    "subject": [{"name": $name, "digest": {"sha256": $digest}}],
    "predicateType": "https://cyclonedx.org/bom",
    "predicate": $sbom[0]
  }' > sbom.statement.json

# Sign using EXTERNAL_MU (same mu computation as binary signing above,
# with sbom.statement.json as the input)
# ... compute mu from sbom.statement.json ...
aws kms sign \
  --key-id alias/pqc-code-signing \
  --message fileb://mu.bin \
  --message-type EXTERNAL_MU \
  --signing-algorithm ML_DSA_SHAKE_256 \
  --query Signature --output text | base64 --decode > sbom.statement.json.sig

# Attach the Statement and its signature to the image as an OCI referrer so
# verifiers discover them alongside the image signature
oras attach $ECR_URI@$IMAGE_DIGEST \
  --artifact-type "application/vnd.example.mldsa-sbom-attestation.v1" \
  sbom.statement.json:application/vnd.in-toto+json \
  sbom.statement.json.sig:application/octet-stream

Ship the Statement and its .sig file together; the SBOM itself is the Statement’s predicate field, and verifiers extract it after verification. The same pattern binds an SBOM to a binary or package: set the subject digest to the SHA-256 of the file instead of an image manifest digest. The Verifying a binary or SBOM signature section later in this post walks through the full verification workflow, including the subject check that completes the binding.

Quantum-resistant workload identity for build agents

Signing artifacts with ML-DSA keys addresses the integrity of the artifacts themselves. Separately, build agents running outside AWS (on-premises Jenkins, self-hosted GitHub Actions runners, or third-party CI/CD systems) authenticate using X.509 certificates or OIDC tokens typically signed with RSA or ECDSA. These authentication credentials represent a classical cryptographic dependency in the pipeline. IAM Roles Anywhere with ML-DSA certificates replaces that dependency: the credential that the external build agent presents, and the CA that vouches for it, no longer rely on algorithms that are vulnerable to quantum attack. (The TLS connection that carries the request still authenticates the AWS endpoint with a traditional certificate, as public TLS does today; that is a transport concern separate from the signing identity this post is about.) Build agents running on AWS with an attached IAM role don’t have this dependency: their API requests are authenticated with AWS Signature Version 4 (SigV4), which uses a symmetric hash-based message authentication code (HMAC-SHA256). Symmetric schemes like this are already considered quantum-resistant, so no additional action is needed.

Step 1: Register a workload identity CA as a trust anchor

For this walkthrough, reuse the subordinate CA that you created earlier; that avoids the monthly charge for a second CA, and the commands that follow assume it. In production, use a dedicated subordinate CA for workload identity certificates, separate from your code-signing CA. This limits the blast radius if either CA is compromised and has to be revoked, and it lets you apply different issuance policies to the two certificate types.

# Use the ARN that create-certificate-authority returned when you created the
# subordinate CA earlier. If you no longer have it, list your CAs and copy the
# ARN of the SUBORDINATE one.
aws acm-pca list-certificate-authorities \
  --query "CertificateAuthorities[?Type=='SUBORDINATE'].[Arn,Status,CertificateAuthorityConfiguration.Subject.CommonName]" \
  --output table
SUB_CA_ARN=arn:aws:acm-pca:us-east-1:111122223333:certificate-authority/abc-123   # replace with yours

# Register the subordinate CA as an IAM Roles Anywhere trust anchor
aws rolesanywhere create-trust-anchor \
  --name "PQC-CI-CD-Trust-Anchor" \
  --source "sourceType=AWS_ACM_PCA,sourceData={acmPcaArn=$SUB_CA_ARN}" \
  --enabled

Step 2: Create the build agent role and a profile that references it

An IAM Roles Anywhere profile specifies which IAM roles a workload can assume after it authenticates with a certificate from your trust anchor. Create the role first. Its trust policy lets IAM Roles Anywhere assume it only through your trust anchor and only for a certificate whose subject common name identifies the build agent; without those conditions, any certificate that the trust anchor CA issues could assume the role. Its permissions policy grants only what signing requires, on only the code-signing key. Save the trust policy as build-agent-trust.json, replacing the trust anchor ARN with the one that create-trust-anchor returned in Step 1:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {"Service": "rolesanywhere.amazonaws.com"},
      "Action": ["sts:AssumeRole", "sts:TagSession", "sts:SetSourceIdentity"],
      "Condition": {
        "ArnEquals": {
          "aws:SourceArn": "arn:aws:rolesanywhere:us-east-1:111122223333:trust-anchor/ta-id"
        },
        "StringEquals": {
          "aws:PrincipalTag/x509Subject/CN": "pqc-build-agent-01"
        }
      }
    }
  ]
}

Save the permissions policy as build-agent-permissions.json, replacing the resource with your key’s ARN (aws kms describe-key --key-id alias/pqc-code-signing --query KeyMetadata.Arn --output text):

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": ["kms:Sign", "kms:GetPublicKey", "kms:DescribeKey"],
      "Resource": "<code-signing-key-arn>"
    }
  ]
}

Create the role, attach the policy, and then create a profile that references the role:

aws iam create-role \
  --role-name PQCBuildAgentRole \
  --assume-role-policy-document file://build-agent-trust.json

aws iam put-role-policy \
  --role-name PQCBuildAgentRole \
  --policy-name pqc-code-signing \
  --policy-document file://build-agent-permissions.json

aws rolesanywhere create-profile \
  --name "PQC-Build-Agent-Profile" \
  --role-arns "arn:aws:iam::111122223333:role/PQCBuildAgentRole" \
  --enabled

Step 3: Issue the build agent certificate and configure the credential helper

Generate the build agent’s ML-DSA-65 key pair and CSR locally with OpenSSL, have the subordinate CA issue a client authentication certificate for it, and then configure the IAM Roles Anywhere credential helper to present that certificate:

# Generate the build agent's key pair and CSR. The CN must match the
# aws:PrincipalTag/x509Subject/CN condition in the role's trust policy.
openssl genpkey -algorithm ML-DSA-65 -out build-agent-mldsa-key.pem
chmod 400 build-agent-mldsa-key.pem
openssl req -new -key build-agent-mldsa-key.pem \
  -subj "/C=US/O=Example Corp/CN=pqc-build-agent-01" \
  -out build-agent.csr

# Issue a 30-day client authentication certificate from the subordinate CA
# registered as the trust anchor in Step 1.
BUILD_AGENT_CERT_ARN=$(aws acm-pca issue-certificate \
  --certificate-authority-arn $SUB_CA_ARN \
  --csr fileb://build-agent.csr \
  --signing-algorithm ML_DSA_65 \
  --validity Value=30,Type=DAYS \
  --template-arn arn:aws:acm-pca:::template/EndEntityClientAuthCertificate/V1 \
  --query CertificateArn --output text)

aws acm-pca get-certificate \
  --certificate-authority-arn $SUB_CA_ARN \
  --certificate-arn $BUILD_AGENT_CERT_ARN \
  --query Certificate --output text > build-agent-mldsa.pem

# In production, store the private key in a TPM or HSM rather than as a plaintext file.
aws_signing_helper credential-process \
  --certificate build-agent-mldsa.pem \
  --private-key build-agent-mldsa-key.pem \
  --trust-anchor-arn arn:aws:rolesanywhere:us-east-1:111122223333:trust-anchor/ta-id \
  --profile-arn arn:aws:rolesanywhere:us-east-1:111122223333:profile/profile-id \
  --role-arn arn:aws:iam::111122223333:role/PQCBuildAgentRole

The helper produces short-lived AWS Security Token Service (AWS STS) credentials scoped to the build role, replacing long-lived AWS access keys. In production, protect the ML-DSA private key with hardware-backed storage such as a Trusted Platform Module (TPM), an HSM, or an encrypted credential store with restricted file permissions. The plaintext file path shown here is for demonstration purposes. The private key authorizes access to your code-signing infrastructure and should be treated with the same protection level as any signing key. On Linux build agents, at minimum restrict the file to chmod 400 owned by the service account and consider using a PKCS#11 provider to avoid storing the raw key on disk entirely.

Verification and policy enforcement

A signing architecture is only as strong as its verification. Producing signatures is half the story. The other half is giving the systems and people that deploy your artifacts, such as deployment pipelines, Kubernetes admission controllers, and engineers installing a package, a concrete way to verify those signatures and make trust decisions before an artifact is deployed or run.

Distributing your trust chain

Before any verifier can check a signature, it needs to trust the CA that issued the code-signing certificate. This trust is established through a trust store: a local collection of root CA certificates that a system treats as authoritative. Trust stores exist in operating systems (such as /etc/pki/ca-trust/ on Linux, Keychain on macOS), language run-times (Java cacerts), container base images, and custom application configurations.

For private PKI hierarchies like the one in this post, your root CA certificate isn’t in any default public trust store. You must explicitly add it to the trust stores of every system that will verify your signatures. Common approaches include:

  • Baking the root CA certificate into your container base images during the build process
  • Distributing it through configuration management (AWS Systems Manager Parameter Store, AWS Secrets Manager, or your existing configuration tooling)
  • Publishing it to an internal S3 bucket with versioning and access logging
  • Storing it as an OCI artifact in Amazon ECR alongside the images it protects

Treat trust store management with the same rigor as credential management. If an attacker can inject a rogue root certificate into your trust stores, they can make forged signatures appear valid. Restrict write access to trust stores and audit changes through AWS CloudTrail or your system-level audit logs.

Exporting your certificate chain requires exporting the root CA, and then any subordinate CAs that issue certificates that will be involved in verifying signatures:

# Export the root CA certificate
aws acm-pca get-certificate-authority-certificate \
  --certificate-authority-arn <root-ca-arn> \
  --query Certificate --output text > root-ca.pem

# Export the subordinate CA certificate. Select only the Certificate field: for a
# subordinate CA this call also returns CertificateChain, and --output text would
# print both on one tab-separated line, producing a file that OpenSSL can't parse.
aws acm-pca get-certificate-authority-certificate \
  --certificate-authority-arn <sub-ca-arn> \
  --query Certificate --output text > sub-ca.pem
  
# Bundle the full chain for verifiers
cat root-ca.pem sub-ca.pem > trust-chain.pem

Verifiers use this chain to confirm that the code-signing public key was issued by a CA they trust.

The CAs in this post are created without a revocation configuration, and the verification commands that follow don’t check revocation status, which keeps the walkthrough short. In production, configure a certificate revocation list (CRL) or an Online Certificate Status Protocol (OCSP) responder on the subordinate CA (see Plan your AWS Private CA certificate revocation method in the AWS Private CA User Guide; both work with ML-DSA CAs). If you use a CRL, distribute it alongside the trust chain and add -crl_check -CRLfile <crl-file> to the openssl verify command below, where <crl-file> is the CRL that AWS Private CA publishes to your S3 bucket, so that a revoked code-signing certificate fails verification.

Verifying a binary or SBOM signature

Verify the code-signing certificate against the trust chain, confirm that it is a code-signing certificate issued to the signer you expect, extract its public key, and then verify the signature with OpenSSL 3.5. The second check matters: a chain check alone accepts every certificate that the CA hierarchy has issued, including the build agent client certificates from the previous section, so pin the expected subject in your verifier configuration:

# Step 1: Verify that the code-signing certificate chains to the trusted root CA and carries the
# Code Signing extended key usage. -purpose codesign (OpenSSL 3.2 and later) rejects a certificate
# that chains correctly but was issued for another purpose, such as a build agent's client
# authentication certificate from the same subordinate CA.
# trust-chain.pem contains the root CA and subordinate CA certificates distributed in the previous section.
openssl verify -CAfile trust-chain.pem -purpose codesign code-signing-cert.pem
# Confirm that the certificate was issued to the signer you expect. Replace <signer-cn> with the
# common name in your code-signing certificate's subject.
openssl x509 -in code-signing-cert.pem -noout -subject -nameopt RFC2253 | grep -q "CN=<signer-cn>" || { echo "Unexpected signer"; exit 1; }

# Step 2: Extract the public key from the verified certificate.
openssl x509 -in code-signing-cert.pem -pubkey -noout > signing-key.pem

# Step 3: Verify the artifact signature using the trusted public key.
openssl pkeyutl -verify \
  -pubin -inkey signing-key.pem \
  -in artifact.bin \
  -sigfile artifact.bin.sig \
  -rawin

A successful verification prints Signature Verified Successfully and returns an exit status of 0. A failed verification prints Signature Verification Failure and returns a nonzero exit status. In shell scripts, check the exit status of each command, or run the block with set -e, so that a failed certificate chain check stops the script before signature verification and a failed signature check blocks downstream actions.

For an SBOM, run the same three steps with sbom.statement.json as the -in file and sbom.statement.json.sig as the -sigfile, then add a fourth: confirm that the subject digest inside the verified Statement is the digest of the artifact you are about to deploy. Signature verification proves the Statement is authentic; the subject check proves it describes this artifact and not another one. The digest you compare against must come from the artifact itself, resolved from the registry for an image or computed from the file for a binary, never from the Statement. For an image, this is the same digest you verify the image signature against, so the two checks together establish that this SBOM describes this signed image.

# Step 4 (SBOM only): the signed Statement must name the image being deployed.
# Resolve the digest from Amazon ECR, not from the Statement.
IMAGE_DIGEST=$(aws ecr batch-get-image \
  --repository-name myapp \
  --image-ids imageTag=v1.2.0 \
  --query 'images[0].imageId.imageDigest' --output text)
SUBJECT_DIGEST=$(jq -r '.subject[0].digest.sha256' sbom.statement.json)
[ "sha256:$SUBJECT_DIGEST" = "$IMAGE_DIGEST" ] || { echo "SBOM does not describe this image"; exit 1; }

# Only now extract the SBOM for downstream tooling
jq '.predicate' sbom.statement.json > sbom.json

For a binary, compare the subject digest to the output of sha256sum artifact.bin instead. Reject the SBOM if either the signature or the subject check fails.

Verifying a container image signature before deployment

Pull the ML-DSA signature from the OCI referrer artifact in Amazon ECR, then verify it against the image manifest digest:

# Pull the signature referrer. ORAS 1.2 lists referrers under "manifests";
# ORAS 1.3 and later list them under "referrers". The jq filter accepts either.
oras discover $ECR_URI@$IMAGE_DIGEST \
  --artifact-type "application/vnd.example.mldsa-signature.v1" --format json | \
  jq -r '(.referrers // .manifests)[0].digest' | \
  xargs -I{} oras pull $ECR_URI@{} -o /tmp/sig/

# Re-derive the image digest and verify
echo -n "$IMAGE_DIGEST" > /tmp/digest.txt
openssl pkeyutl -verify \
  -pubin -inkey signing-key.pem \
  -in /tmp/digest.txt \
  -sigfile /tmp/sig/image.mldsa.sig \
  -rawin

# Exit code 0 = image is authentic; non-zero = reject deployment

The same oras discover command with --artifact-type "application/vnd.example.mldsa-sbom-attestation.v1" retrieves the SBOM attestation and its signature; verify them as described in the previous section, including the subject check. The jq filter shown takes the first referrer of the requested type. Don’t rely on the order in which a registry lists referrers, and expect more than one after an image has been re-signed: a production verifier should check every referrer of that type and accept the image if at least one signature verifies against a certificate that chains to your trust store. Taking only the first can reject a correctly signed image, but it can never accept an unsigned one.

To enforce these checks at deployment time, run them in a Kubernetes admission controller, a component that the API server calls before it accepts a pod and that can reject the request. You can write one as a validating admission webhook (see Dynamic Admission Control in the Kubernetes documentation), or use Open Policy Agent (OPA) Gatekeeper, an admission webhook that enforces policies evaluated by the OPA policy engine, and package the verification steps as a Gatekeeper external data provider that a constraint calls. For a worked example of gating Amazon EKS deployments on image signatures, see Announcing Container Image Signing with AWS Signer and Amazon EKS, which verifies AWS Signer signatures at admission with Kyverno and discusses the Gatekeeper and custom webhook alternatives. The ML-DSA signature referrer in this post is a custom artifact type that those tools don’t verify out of the box, so the verification steps in this section run in code you supply. In either design, the controller runs before any pod is scheduled, rejecting images that lack a valid ML-DSA signature referrer in Amazon ECR or whose SBOM attestation doesn’t name the image being deployed.

Preventive and detective controls

Signature verification stops the use of an untrusted artifact at deployment. Organization-level controls apply earlier and more broadly: preventive controls stop teams from creating new traditional signing keys, and detective controls record every signing operation so you can audit which principal signed each artifact and when.

Preventive guardrails. Use an AWS Organizations Service control policy (SCP) to block creation of traditional signing keys in security-critical accounts, forcing all new signing workloads to use ML-DSA:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "RequirePQCSigningKeys",
      "Effect": "Deny",
      "Action": "kms:CreateKey",
      "Resource": "*",
      "Condition": {
        "StringNotLike": {
          "kms:KeySpec": "ML_DSA_*"
        },
        "StringEquals": {
          "kms:KeyUsage": "SIGN_VERIFY"
        }
      }
    }
  ]
}

This SCP prevents teams from creating new RSA or ECDSA signing keys, enforcing quantum-resistant signatures as the only option for new workloads. Note that this SCP constrains the algorithm family, not the parameter set: it would still permit an ML-DSA-44 key, which this architecture doesn’t use. Part 2 of this series picks up at exactly this point. It shows how to express a complete algorithm policy (in its example, approve ML-DSA-65 and ML-DSA-87 and exclude ML-DSA-44) as layered controls using the kms:KeySpec condition key in SCPs, IAM permission boundaries, and AWS KMS key policies; how to restrict the use of keys that already exist; and how to govern surfaces such as AWS Private CA that have no algorithm condition key. This SCP and the parameter-set SCP in Part 2 work together: attach both, and every new signing key must use an approved parameter set.

Audit trail. AWS CloudTrail logs every kms:Sign and kms:Verify API call, providing an immutable record of when each artifact was signed and by which principal. Use an organization trail and query its logs with Amazon Athena to analyze signing activity across accounts and correlate it with your deployment events.

Regulatory timeline and recommended actions

The following table maps regulatory milestones to specific actions you can take today using the architecture described in this post. This information is provided for general awareness only and does not constitute legal or compliance advice. Consult your legal and compliance teams to determine your organization’s specific obligations. For a broader overview of global PQC regulatory timelines, see Migrating to Post-Quantum Cryptography.

Regulation Deadline Regulatory language Action on AWS
CNSA 2.0: Support and prefer 2025 (in effect) CNSA 2.0 timeline (Sep 2022, FAQ v2.1 Dec 2024): Software and firmware signing must “support and prefer” CNSA 2.0 algorithms by 2025 Create ML-DSA keys in AWS KMS, begin signing artifacts with ML-DSA alongside existing traditional signatures
CNSA 2.0: New system acquisitions January 2027 CNSA 2.0 FAQ v2.1 (Dec 2024): “All new NSS acquisitions must be CNSA 2.0 compliant at deployment, effective 1 January 2027” Full ML-DSA PKI operational, IAM Roles Anywhere trust anchors using ML-DSA, all new builds carry ML-DSA signatures
EU Cyber Resilience Act 11 December 2027 Regulation (EU) 2024/2847, Annex I, Part I(2)(f): Products must “protect the integrity of stored, transmitted or otherwise processed data, personal or other, commands, programs and configuration against any manipulation or modification not authorised by the user, and report on corruptions”; Part II(7): Manufacturers must “provide for mechanisms to securely distribute updates” ML-DSA code signing for all software updates shipped to EU markets, signed SBOMs accompany every release
CNSA 2.0: Exclusive use 2030 CNSA 2.0 timeline: Software and firmware signing must “exclusively use” CNSA 2.0 algorithms by 2030 Remove traditional signing keys from supply chain, SCP enforcement of ML-DSA-only key creation
PCI DSS 4.0 Req 12.3.3 Mandatory since March 2025 PCI DSS v4.0.1, Requirement 12.3.3: “Cryptographic cipher suites and protocols in use are documented and reviewed at least once every 12 months”, including an up-to-date inventory of the cipher suites and protocols in use Document cryptographic inventory in AWS KMS, tag ML-DSA versus traditional keys, maintain migration progress tracking

Note for NSS customers and other CNSA 2.0 adopters: CNSA 2.0 is the quantum-resistant algorithm suite that the NSA requires for NSS, the federal systems that carry classified information or support intelligence, cryptologic, military command and control, and weapons functions. When ML-DSA is used for any signature purpose, including software and firmware signing, CNSA 2.0 permits only the ML-DSA-87 parameter set. (For software and firmware signing it also approves the stateful hash-based schemes LMS and XMSS, which this post doesn’t cover.) The ML-DSA-65 parameter set used in this post’s code-signing examples is appropriate for commercial workloads but isn’t permitted on NSS. CNSA 2.0 is binding only for NSS, but it’s followed voluntarily well beyond that boundary: by suppliers to the US defense and intelligence market, in the United States and allied countries, whose products must meet NSS requirements, and by commercial organizations in and outside the United States that adopt it as a conservative baseline because it specifies the highest NIST security category and removes the need to revisit parameter choices later. If your systems fall under CNSA 2.0 scope, or you’ve chosen to align with it, substitute ML-DSA-87 for all signing keys and certificates. Part 2 of this series shows how to make that substitution enforceable: the same kms:KeySpec controls that exclude ML-DSA-44 in its example can be pointed at ML_DSA_87 as the only approved key spec.

For organizations serving both US government and EU commercial markets, the January 2027 and December 2027 deadlines converge into a single migration window. Starting now provides margin for testing, key rotation planning, and certificate chain validation.

Clean up

You created a number of cryptographic resources in the prior steps and examples. AWS Private CA charges a monthly fee per CA and AWS KMS charges per key per month. To avoid ongoing charges, delete them if you aren’t actively using them. Start by listing what exists, so that you catch every resource you created, including duplicates from repeated runs. These commands list one Region; if you worked in more than one, repeat them with --region for each.

# List every private CA with its type, status, key algorithm, and subject.
# A CA you already deleted shows DELETED until its restoration window ends.
aws acm-pca list-certificate-authorities \
  --query 'CertificateAuthorities[].[Arn,Type,Status,CertificateAuthorityConfiguration.KeyAlgorithm,CertificateAuthorityConfiguration.Subject.CommonName]' \
  --output table

# List every ML-DSA key in AWS KMS with its state and creation date.
# A key already scheduled for deletion shows PendingDeletion.
for KEY_ID in $(aws kms list-keys --query 'Keys[].KeyId' --output text); do
  aws kms describe-key --key-id "$KEY_ID" \
    --query 'KeyMetadata.[KeyId,KeySpec,KeyState,CreationDate]' --output text
done | grep ML_DSA

# Show which alias points at which key. A key that no alias points at
# is usually a leftover from an earlier run.
aws kms list-aliases --query 'Aliases[].[AliasName,TargetKeyId]' --output text | grep -v '^alias/aws/'

AWS Private CA has no command that lists the certificates a CA has issued. If you need serial numbers for the revocation step that follows, generate an audit report with aws acm-pca create-certificate-authority-audit-report, which writes a list of every certificate the CA has issued or revoked to an S3 bucket that grants the service write access.

Delete each resource that you don’t need, including any extra copies that the listing revealed, then run the listing again to confirm that nothing is left:

# Revoke any issued end-entity certificates while the subordinate CA is still active
aws acm-pca revoke-certificate \
  --certificate-authority-arn <sub-ca-arn> \
  --certificate-serial <serial-number> \
  --revocation-reason CESSATION_OF_OPERATION

# Delete the IAM Roles Anywhere resources that reference the CA
aws rolesanywhere delete-profile --profile-id <profile-id>
aws rolesanywhere delete-trust-anchor --trust-anchor-id <trust-anchor-id>

# Delete the build agent role that the profile referenced, and the local copy of its private key
aws iam delete-role-policy --role-name PQCBuildAgentRole --policy-name pqc-code-signing
aws iam delete-role --role-name PQCBuildAgentRole
rm -f build-agent-mldsa-key.pem

# Delete the AWS KMS code-signing key (schedule 7-day waiting period).
# ScheduleKeyDeletion doesn't accept an alias, so resolve the key ID first.
KEY_ID=$(aws kms describe-key --key-id alias/pqc-code-signing \
  --query KeyMetadata.KeyId --output text)
aws kms schedule-key-deletion --key-id $KEY_ID --pending-window-in-days 7

# Remove the alias. It survives key deletion and would otherwise show up in the
# listing above on your next run.
aws kms delete-alias --alias-name alias/pqc-code-signing

# Disable and delete the subordinate CA
aws acm-pca update-certificate-authority \
  --certificate-authority-arn <sub-ca-arn> --status DISABLED
aws acm-pca delete-certificate-authority \
  --certificate-authority-arn <sub-ca-arn> --permanent-deletion-time-in-days 7

# Disable and delete the root CA
aws acm-pca update-certificate-authority \
  --certificate-authority-arn <root-ca-arn> --status DISABLED
aws acm-pca delete-certificate-authority \
  --certificate-authority-arn <root-ca-arn> --permanent-deletion-time-in-days 7

If you are adapting this for long-term use, plan for log retention. CloudTrail Event History keeps only the last 90 days of management events and is not a substitute for a trail. For the audit trail described earlier, create a trail that delivers to an S3 bucket with the lifecycle policy and access controls your retention requirements call for.

Conclusion

In this post, I showed you how to build a quantum-resistant software supply chain on AWS by combining ML-DSA signing in AWS KMS, ML-DSA certificate hierarchies in AWS Private CA, and ML-DSA workload authentication through IAM Roles Anywhere. The architecture covers the full pipeline; from authenticated build agents through signed binaries, container images, and SBOMs, to verification and policy enforcement at deployment.

Every ML-DSA capability used in this post is generally available. AWS Private CA and IAM Roles Anywhere support ML-DSA in all commercial AWS Regions, the AWS GovCloud (US) Regions, and the China Regions, and AWS KMS supports ML-DSA in commercial AWS Regions. You don’t need to wait for a standards body or third-party tool to finalize PQC support. The primitives are ready.

To get started, create your first ML-DSA key in AWS KMS and sign a test artifact. From there, extend to your PKI hierarchy, integrate IAM Roles Anywhere for your build agents, and add ML-DSA signatures to your container and SBOM workflows.

Building the pipeline is half the work. The other half is making sure the algorithm choices you made stay in force as accounts, teams, and standards change. That’s the subject of Part 2 of this series, Enforce your ML-DSA algorithm policy with SCPs and IAM, written for the security and governance teams who own that problem.

For more information, see:

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


Harshvardhan Chunawala

Harshvardhan Chunawala

Harshvardhan is a Solutions Architect and Security SME at AWS, where he leads cross-team efforts with Amazon Leo, Amazon Security, and AWS Agentic AI. A Golden Jacket awardee with over a decade in cloud security, he’s an advisory board member, Visiting Faculty, and researcher at Carnegie Mellon University. He advises C-suite executives, enterprise leaders, and startup founders worldwide on building secure, scalable cloud platforms.

Security posture improvement in the AI era

Post Syndicated from Celeste Bishop original https://aws.amazon.com/blogs/security/security-posture-improvement-in-the-ai-era/

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.

AWS KMS CloudWatch metrics help you better track and understand how your KMS keys are being used

Post Syndicated from Norman Li original https://aws.amazon.com/blogs/security/aws-kms-cloudwatch-metrics-help-you-better-track-and-understand-how-your-kms-keys-are-being-used/

AWS Key Management Service (AWS KMS) is pleased to launch key-level filtering for AWS KMS API usage in Amazon CloudWatch metrics, providing enhanced visibility to help customers improve their operational efficiency and aid in security and compliance risk management.

AWS KMS currently publishes account-level AWS KMS API usage metrics to Amazon CloudWatch, enabling you to monitor and manage your API usage. However, if you’re using numerous KMS keys, pinpointing the ones with the highest request rate quota usage or significant API costs becomes challenging. For example, if you have more than 10 active KMS keys in your account, prior to this launch you would have needed to build a custom CloudTrail and Amazon Athena based solution to locate which specific keys are driving the majority of API usage and costs. With the new CloudWatch metrics, which are available under the AWS/KMS namespace in CloudWatch, you can track, understand, and set alerts on detailed API usage at the individual KMS key level without building a costly customized solution.

This blog post explores several use cases to help you better take advantage of these newly introduced CloudWatch metrics to manage your AWS KMS API usage and costs. The use cases cover viewing and understanding your API usage at the key level, and creating CloudWatch alerts to detect unintentional runaway usage.

Overview of new CloudWatch metrics for KMS keys

With CloudWatch metrics for KMS keys, you can now do the following:

  1. View the API usage for a specific KMS key, filtered by individual API operations (for example, Encrypt, Decrypt, or GenerateDataKey).
  2. See the aggregated usage across cryptographic operations for a given KMS key.
  3. Set up an alarm if a specific KMS key exceeds a specified threshold on a single API operation, or a set of API operations.

This streamlined approach allows you to quickly monitor, understand, and troubleshoot the API usage patterns of your KMS keys, without the overhead of the previous multi-step process. Let’s detail how these key-level API usage metrics can be used in two real-world examples.

Example 1: How to locate the KMS keys that consume the most API usage quota or contribute the most API charges

When you surpass your AWS KMS API request rate quotas, you can view your AWS KMS API utilization within the Service Quotas console. However, you might still find it cumbersome to identify the KMS keys that consume the largest amount of your request quota. When you receive the AWS KMS API charges that exceed your expectation, you can check the detailed billing usage in each AWS Region in Cost Explorer, but you cannot easily locate the KMS keys with the most API charges. This process becomes even more challenging when you manage a large number of KMS keys.

With the key-level API usage CloudWatch metrics, you can use the advanced metric query option to query CloudWatch Metrics Insights data with a user-friendly dialect of SQL to locate the KMS keys that consume the largest portion of the API usage quota or contribute the most API charges.

Walkthrough

To use Amazon CloudWatch Metrics Insights to identify the top 20 KMS keys that have the most cryptographic API usage up to the last 3 hours, complete the following steps:

  1. Open the CloudWatch console.
  2. In the navigation pane, choose Metrics, and then choose All metrics.
  3. Choose the Multi source query tab.
  4. For the data source, choose CloudWatch Metrics Insights.
  5. You can enter the following example query in Editor view:

    Note: In Builder view, the metric namespace, metric name, filter by, group by, order by, and limit options are shown. In Editor view, the same options as in Builder view are shown in query format.

    	SELECT SUM(SuccessfulRequest)
    	FROM SCHEMA("AWS/KMS", KeyArn, Operation)
    	GROUP BY KeyArn
    	ORDER BY MAX () DESC
    	LIMIT 20

  6. Choose Run in the Editor view or Graph query in the Builder view.

Example 2: How to set a new detailed alarm on unintentional runaway AWS KMS API usage

Running big data processing workflows that read Amazon Simple Storage Service (Amazon S3) files encrypted by KMS keys is a common scenario for analytics, business reporting, or machine learning projects. Typically, these workflows read a limited number of files from S3 on each invocation. However, misconfigured workflows could unintentionally read a large number of S3 files, which could result in exceeding your AWS KMS API request rate quotas or incurring undesirable charges due to spiky AWS KMS API usage. Historically, to address this issue, you would have had to build a customized alarm system by following these steps: 1) send AWS CloudTrail events generated by AWS KMS to Amazon CloudWatch Logs; 2) write queries in Amazon CloudWatch Logs Insights to track your API request usage; and 3) enable anomaly detection on the corresponding CloudWatch Log Insights math expression.

Now, with key-level API usage CloudWatch metrics, you can directly enable anomaly detection on these metrics to set up alarms for anomalous AWS KMS API usage patterns. This provides a more streamlined and efficient way to monitor and detect potential runaway workflows. By using these CloudWatch metrics and anomaly detection capabilities, you can proactively identify and address unintended increases in AWS KMS API usage, helping to avoid unexpected charges or service disruptions in your analytics, reporting, or machine learning pipelines.

Walkthrough

Consider a scenario where you have an analytics workflow that runs frequently, which uses the Decrypt AWS KMS API operation on a KMS key to decrypt and read data from S3. You would like to enable anomaly detection on the KMS key to trigger an alarm when the Decrypt call volume to the specific KMS key sees a discernible trend or pattern. To do so, complete the following steps:

  1. Open the CloudWatch console.
  2. In the navigation pane, choose Metrics, and then choose All metrics.
  3. Choose KMS, and then choose KeyArn, Operation.
  4. In the search bar, enter the Amazon Resource Name (ARN) of the key, and then choose Search. Select the CloudWatch metric you would like to enable anomaly detection for.
  5. Navigate to Graphed metrics, and using the Statistic and Period drop-down lists, choose the statistic and period that you would like to monitor. Then you can enable anomaly detection by selecting the Pulse icon.

    Figure 1: How to enable anomaly detection on a SuccessfulRequest metric

    Figure 1: How to enable anomaly detection on a SuccessfulRequest metric

  6. You can adjust the anomaly detection by setting the sensitivity to adjust the bandwidth, if needed.

    Figure 2: Anomaly detection is enabled on the SuccessfulRequest metric. The gray band illustrates the expected range of values and the anomaly is in red

    Figure 2: Anomaly detection is enabled on the SuccessfulRequest metric. The gray band illustrates the expected range of values and the anomaly is in red

Conclusion

This blog post highlighted the newly introduced key-level filtering capability for the AWS KMS API usage in CloudWatch. We showed two real-world use cases to demonstrate how you can use the new CloudWatch metrics. These use cases include improving operational visibility, setting up proactive alarms on anomalies in KMS API usage patterns, and potentially tracking detailed key usage for compliance purposes.

If you have feedback about this blog post, submit comments in the Comments section below. If you have questions about this blog post, start a new thread in the AWS Key Management Service re:Post.
 

Norman Li
Norman Li

Norman is a Software Development Manager for AWS KMS. In this role, Norman leads the development of visibility features, as well as internal scalability initiatives. Outside of work, Norman likes to spend time in the beautiful Pacific Northwest mountains.
Haiyu Zhen
Haiyu Zhen

Haiyu is a Senior Software Development Engineer for AWS KMS. She specializes in building secure, large-scale distributed systems and is passionate about enhancing cloud-native application security without compromising performance.

The curious case of faster AWS KMS symmetric key rotation

Post Syndicated from Jeremy Stieglitz original https://aws.amazon.com/blogs/security/the-curious-case-of-faster-aws-kms-symmetric-key-rotation/

Today, AWS Key Management Service (AWS KMS) is introducing faster options for automatic symmetric key rotation. We’re also introducing rotate on-demand, rotation visibility improvements, and a new limit on the price of all symmetric keys that have had two or more rotations (including existing keys). In this post, I discuss all those capabilities and changes. I also present a broader overview of how symmetric cryptographic key rotation came to be, and cover our recommendations on when you might need rotation and how often to rotate your keys. If you’ve ever been curious about AWS KMS automatic key rotation—why it exists, when to enable it, and when to use it on-demand—read on.

How we got here

There are longstanding reasons for cryptographic key rotation. If you were Caesar in Roman times and you needed to send messages with sensitive information to your regional commanders, you might use keys and ciphers to encrypt and protect your communications. There are well-documented examples of using cryptography to protect communications during this time, so much so that the standard substitution cipher, where you swap each letter for a different letter that is a set number of letters away in the alphabet, is referred to as Caesar’s cipher. The cipher is the substitution mechanism, and the key is the number of letters away from the intended letter you go to find the substituted letter for the ciphertext.

The challenge for Caesar in relying on this kind of symmetric key cipher is that both sides (Caesar and his field generals) needed to share keys and keep those keys safe from prying eyes. What happens to Caesar’s secret invasion plans if the key used to encipher his attack plan was secretly intercepted in transmission down the Appian Way? Caesar had no way to know. But if he rotated keys, he could limit the scope of which messages could be read, thus limiting his risk. Messages sent under a key created in the year 52 BCE wouldn’t automatically work for messages sent the following year, provided that Caesar rotated his keys yearly and the newer keys weren’t accessible to the adversary. Key rotation can reduce the scope of data exposure (what a threat actor can see) when some but not all keys are compromised. Of course, every time the key changed, Caesar had to send messengers to his field generals to communicate the new key. Those messengers had to ensure that no enemies intercepted the new keys without their knowledge – a daunting task.

Illustration of Roman solider on horseback riding through countryside on cobblestone trail.

Figure 1: The state of the art for secure key rotation and key distribution in 52 BC.

Fast forward to the 1970s–2000s

In modern times, cryptographic algorithms designed for digital computer systems mean that keys no longer travel down the Appian Way. Instead, they move around digital systems, are stored in unprotected memory, and sometimes are printed for convenience. The risk of key leakage still exists, therefore there is a need for key rotation. During this period, more significant security protections were developed that use both software and hardware technology to protect digital cryptographic keys and reduce the need for rotation. The highest-level protections offered by these techniques can limit keys to specific devices where they can never leave as plaintext. In fact, the US National Institute of Standards and Technologies (NIST) has published a specific security standard, FIPS 140, that addresses the security requirements for these cryptographic modules.

Modern cryptography also has the risk of cryptographic key wear-out

Besides addressing risks from key leakage, key rotation has a second important benefit that becomes more pronounced in the digital era of modern cryptography—cryptographic key wear-out. A key can become weaker, or “wear out,” over time just by being used too many times. If you encrypt enough data under one symmetric key, and if a threat actor acquires enough of the resulting ciphertext, they can perform analysis against your ciphertext that will leak information about the key. Current cryptographic recommendations to protect against key wear-out can vary depending on how you’re encrypting data, the cipher used, and the size of your key. However, even a well-designed AES-GCM implementation with robust initialization vectors (IVs) and large key size (256 bits) should be limited to encrypting no more than 4.3 billion messages (232), where each message is limited to about 64 GiB under a single key.

Figure 2: Used enough times, keys can wear out.

Figure 2: Used enough times, keys can wear out.

During the early 2000s, to help federal agencies and commercial enterprises navigate key rotation best practices, NIST formalized several of the best practices for cryptographic key rotation in the NIST SP 800-57 Recommendation for Key Management standard. It’s an excellent read overall and I encourage you to examine Section 5.3 in particular, which outlines ways to determine the appropriate length of time (the cryptoperiod) that a specific key should be relied on for the protection of data in various environments. According to the guidelines, the following are some of the benefits of setting cryptoperiods (and rotating keys within these periods):

5.3 Cryptoperiods

A cryptoperiod is the time span during which a specific key is authorized for use by legitimate entities or the keys for a given system will remain in effect. A suitably defined cryptoperiod:

  1. Limits the amount of information that is available for cryptanalysis to reveal the key (e.g. the number of plaintext and ciphertext pairs encrypted with the key);
  2. Limits the amount of exposure if a single key is compromised;
  3. Limits the use of a particular algorithm (e.g., to its estimated effective lifetime);
  4. Limits the time available for attempts to penetrate physical, procedural, and logical access mechanisms that protect a key from unauthorized disclosure;
  5. Limits the period within which information may be compromised by inadvertent disclosure of a cryptographic key to unauthorized entities; and
  6. Limits the time available for computationally intensive cryptanalysis.

Sometimes, cryptoperiods are defined by an arbitrary time period or maximum amount of data protected by the key. However, trade-offs associated with the determination of cryptoperiods involve the risk and consequences of exposure, which should be carefully considered when selecting the cryptoperiod (see Section 5.6.4).

(Source: NIST SP 800-57 Recommendation for Key Management, page 34).

One of the challenges in applying this guidance to your own use of cryptographic keys is that you need to understand the likelihood of each risk occurring in your key management system. This can be even harder to evaluate when you’re using a managed service to protect and use your keys.

Fast forward to the 2010s: Envisioning a key management system where you might not need automatic key rotation

When we set out to build a managed service in AWS in 2014 for cryptographic key management and help customers protect their AWS encryption workloads, we were mindful that our keys needed to be as hardened, resilient, and protected against external and internal threat actors as possible. We were also mindful that our keys needed to have long-term viability and use built-in protections to prevent key wear-out. These two design constructs—that our keys are strongly protected to minimize the risk of leakage and that our keys are safe from wear out—are the primary reasons we recommend you limit key rotation or consider disabling rotation if you don’t have compliance requirements to do so. Scheduled key rotation in AWS KMS offers limited security benefits to your workloads.

Specific to key leakage, AWS KMS keys in their unencrypted, plaintext form cannot be accessed by anyone, even AWS operators. Unlike Caesar’s keys, or even cryptographic keys in modern software applications, keys generated by AWS KMS never exist in plaintext outside of the NIST FIPS 140-2 Security Level 3 fleet of hardware security modules (HSMs) in which they are used. See the related post AWS KMS is now FIPS 140-2 Security Level 3. What does this mean for you? for more information about how AWS KMS HSMs help you prevent unauthorized use of your keys. Unlike many commercial HSM solutions, AWS KMS doesn’t even allow keys to be exported from the service in encrypted form. Why? Because an external actor with the proper decryption key could then expose the KMS key in plaintext outside the service.

This hardened protection of your key material is salient to the principal security reason customers want key rotation. Customers typically envision rotation as a way to mitigate a key leaking outside the system in which it was intended to be used. However, since KMS keys can be used only in our HSMs and cannot be exported, the possibility of key exposure becomes harder to envision. This means that rotating a key as protection against key exposure is of limited security value. The HSMs are still the boundary that protects your keys from unauthorized access, no matter how many times the keys are rotated.

If we decide the risk of plaintext keys leaking from AWS KMS is sufficiently low, don’t we still need to be concerned with key wear-out? AWS KMS mitigates the risk of key wear-out by using a key derivation function (KDF) that generates a unique, derived AES 256-bit key for each individual request to encrypt or decrypt under a 256-bit symmetric KMS key. Those derived encryption keys are different every time, even if you make an identical call for encrypt with the same message data under the same KMS key. The cryptographic details for our key derivation method are provided in the AWS KMS Cryptographic Details documentation, and KDF operations use the KDF in counter mode, using HMAC with SHA256. These KDF operations make cryptographic wear-out substantially different for KMS keys than for keys you would call and use directly for encrypt operations. A detailed analysis of KMS key protections for cryptographic wear-out is provided in the Key Management at the Cloud Scale whitepaper, but the important take-away is that a single KMS key can be used for more than a quadrillion (250) encryption requests without wear-out risk.

In fact, within the NIST 800-57 guidelines is consideration that when the KMS key (key-wrapping key in NIST language) is used with unique data keys, KMS keys can have longer cryptoperiods:

“In the case of these very short-term key-wrapping keys, an appropriate cryptoperiod (i.e., which includes both the originator and recipient-usage periods) is a single communication session. It is assumed that the wrapped keys will not be retained in their wrapped form, so the originator-usage period and recipient-usage period of a key-wrapping key is the same. In other cases, a key-wrapping key may be retained so that the files or messages encrypted by the wrapped keys may be recovered later. In such cases, the recipient-usage period may be significantly longer than the originator-usage period of the key-wrapping key, and cryptoperiods lasting for years may be employed.”

Source: NIST 800-57 Recommendations for Key Management, section 5.3.6.7.

So why did we build key rotation in AWS KMS in the first place?

Although we advise that key rotation for KMS keys is generally not necessary to improve the security of your keys, you must consider that guidance in the context of your own unique circumstances. You might be required by internal auditors, external compliance assessors, or even your own customers to provide evidence of regular rotation of all keys. A short list of regulatory and standards groups that recommend key rotation includes the aforementioned NIST 800-57, Center for Internet Security (CIS) benchmarks, ISO 27001, System and Organization Controls (SOC) 2, the Payment Card Industry Data Security Standard (PCI DSS), COBIT 5, HIPAA, and the Federal Financial Institutions Examination Council (FFIEC) Handbook, just to name a few.

Customers in regulated industries must consider the entirety of all the cryptographic systems used across their organizations. Taking inventory of which systems incorporate HSM protections, which systems do or don’t provide additional security against cryptographic wear-out, or which programs implement encryption in a robust and reliable way can be difficult for any organization. If a customer doesn’t have sufficient cryptographic expertise in the design and operation of each system, it becomes a safer choice to mandate a uniform scheduled key rotation.

That is why we offer an automatic, convenient method to rotate symmetric KMS keys. Rotation allows customers to demonstrate this key management best practice to their stakeholders instead of having to explain why they chose not to.

Figure 3 details how KMS appends new key material within an existing KMS key during each key rotation.

Figure 3: KMS key rotation process

Figure 3: KMS key rotation process

We designed the rotation of symmetric KMS keys to have low operational impact to both key administrators and builders using those keys. As shown in Figure 3, a keyID configured to rotate will append new key material on each rotation while still retaining and keeping the existing key material of previous versions. This append method achieves rotation without having to decrypt and re-encrypt existing data that used a previous version of a key. New encryption requests under a given keyID will use the latest key version, while decrypt requests under that keyID will use the appropriate version. Callers don’t have to name the version of the key they want to use for encrypt/decrypt, AWS KMS manages this transparently.

Some customers assume that a key rotation event should forcibly re-encrypt any data that was ever encrypted under the previous key version. This is not necessary when AWS KMS automatically rotates to use a new key version for encrypt operations. The previous versions of keys required for decrypt operations are still safe within the service.

We’ve offered the ability to automatically schedule an annual key rotation event for many years now. Lately, we’ve heard from some of our customers that they need to rotate keys more frequently than the fixed period of one year. We will address our newly launched capabilities to help meet these needs in the final section of this blog post.

More options for key rotation in AWS KMS (with a price reduction)

After learning how we think about key rotation in AWS KMS, let’s get to the new options we’ve launched in this space:

  • Configurable rotation periods: Previously, when using automatic key rotation, your only option was a fixed annual rotation period. You can now set a rotation period from 90 days to 2,560 days (just over seven years). You can adjust this period at any point to reset the time in the future when rotation will take effect. Existing keys set for rotation will continue to rotate every year.
  • On-demand rotation for KMS keys: In addition to more flexible automatic key rotation, you can now invoke on-demand rotation through the AWS Management Console for AWS KMS, the AWS Command Line Interface (AWS CLI), or the AWS KMS API using the new RotateKeyOnDemand API. You might occasionally need to use on-demand rotation to test workloads, or to verify and prove key rotation events to internal or external stakeholders. Invoking an on-demand rotation won’t affect the timeline of any upcoming rotation scheduled for this key.

    Note: We’ve set a default quota of 10 on-demand rotations for a KMS key. Although the need for on-demand key rotation should be infrequent, you can ask to have this quota raised. If you have a repeated need for testing or validating instant key rotation, consider deleting the test keys and repeating this operation for RotateKeyOnDemand on new keys.

  • Improved visibility: You can now use the AWS KMS console or the new ListKeyRotations API to view previous key rotation events. One of the challenges in the past is that it’s been hard to validate that your KMS keys have rotated. Now, every previous rotation for a KMS key that has had a scheduled or on-demand rotation is listed in the console and available via API.
     
    Figure 4: Key rotation history showing date and type of rotation

    Figure 4: Key rotation history showing date and type of rotation

  • Price cap for keys with more than two rotations: We’re also introducing a price cap for automatic key rotation. Previously, each annual rotation of a KMS key added $1 per month to the price of the key. Now, for KMS keys that you rotate automatically or on-demand, the first and second rotation of the key adds $1 per month in cost (prorated hourly), but this price increase is capped at the second rotation. Rotations after your second rotation aren’t billed. Existing customers that have keys with three or more annual rotations will see a price reduction for those keys to $3 per month (prorated) per key starting in the month of May, 2024.

Summary

In this post, I highlighted the more flexible options that are now available for key rotation in AWS KMS and took a broader look into why key rotation exists. We know that many customers have compliance needs to demonstrate key rotation everywhere, and increasingly, to demonstrate faster or immediate key rotation. With the new reduced pricing and more convenient ways to verify key rotation events, we hope these new capabilities make your job easier.

Flexible key rotation capabilities are now available in all AWS Regions, including the AWS GovCloud (US) Regions. To learn more about this new capability, see the Rotating AWS KMS keys topic in the AWS KMS Developer Guide.

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

Author

Jeremy Stieglitz

Jeremy is the Principal Product Manager for AWS KMS, where he drives global product strategy and roadmap. Jeremy has more than 25 years of experience defining security products and platforms across large companies (RSA, Entrust, Cisco, and Imperva) and start-up environments (Dataguise, Voltage, and Centrify). Jeremy is the author or co-author of 23 patents in network security, user authentication, and network automation and control.

How to migrate asymmetric keys from CloudHSM to AWS KMS

Post Syndicated from Mani Manasa Mylavarapu original https://aws.amazon.com/blogs/security/how-to-migrate-asymmetric-keys-from-cloudhsm-to-aws-kms/

In June 2023, Amazon Web Services (AWS) introduced a new capability to AWS Key Management Service (AWS KMS): you can now import asymmetric key materials such as RSA or elliptic-curve cryptography (ECC) private keys for your signing workflow into AWS KMS. This means that you can move your asymmetric keys that are managed outside of AWS KMS—such as a hybrid (on-premises) environment, multi-cloud environment, and even AWS CloudHSM—and make them available through AWS KMS. Combined with the announcement on AWS KMS HSMs achieving FIPS 140-2 Security Level 3, you can make sure that your keys are secured and used in a manner that aligns to the cryptographic standards laid out by the U.S. National Institute of Standards and Technology (NIST).

In this post, we will show you how to migrate your asymmetric keys from CloudHSM to AWS KMS. This can help you simplify your key management strategy and take advantage of the robust authorization control of AWS KMS key policies.

Benefits of importing key materials into AWS KMS

In general, we recommend that you use a native KMS key because it provides the best security, durability, and availability compared to other key store options. AWS KMS FIPS-validated hardware security modules (HSMs) generate the key materials for KMS keys, and these key materials never leave the HSMs unencrypted. Operations that require use of your KMS key (for example, decryption of a data key or digital signature signing) must occur within the HSM.

However, depending on your organization’s requirements, you might need to bring your own key (BYOK) from outside. Importing your own key gives you direct control over the generation, lifecycle management, and durability of your keys. In addition, you have full control over the availability of your imported keys because you can set an expiration period or delete and reimport the keys at any time. You have greater control over the durability of your imported keys because you can maintain the original version of the keys elsewhere. If you need to generate and store copies of keys outside of AWS, these additional controls can help you meet your compliance requirements.

Solution overview

At a high level, our solution involves downloading the wrapping key from AWS KMS, using the CloudHSM Command Line Interface (CLI) to import a wrapping key to CloudHSM, wrapping the private key by using the wrapping key in CloudHSM, and uploading the wrapped private key to AWS KMS by using an import token. You can perform the same procedures by using other supported libraries, such as the PKCS #11 library or a JCE provider.

Figure 1: Overall architecture of the solution

Figure 1: Overall architecture of the solution

As shown in Figure 1, the solution involves the following steps:

  1. Create a KMS key without key material in AWS KMS
  2. Download the wrapping public key and import token from AWS KMS
  3. Import the wrapping key provided by AWS KMS into CloudHSM
  4. Wrap the private key inside CloudHSM with the imported wrapping public key from AWS KMS
  5. Import the wrapped private key to AWS KMS

For the walkthrough in this post, you will import into AWS KMS an ECC 256-bit private key (NIST P-256) that’s used for signing purpose from a CloudHSM cluster. When you import an asymmetric key into AWS KMS, you only need to import a private key. You don’t need to import a public key because AWS KMS can generate and retrieve a public key from the private key after the private key is imported.

Prerequisites

To follow along with this walkthrough, make sure that you have the following prerequisites in place:

  1. An active CloudHSM cluster with at least one active HSM and a valid crypto user credential.
  2. An Amazon Elastic Compute Cloud (Amazon EC2) instance with the CloudHSM Client SDK 5 installed and configured to connect to the CloudHSM cluster. For instructions on how to configure and connect the client instance, see Getting started with AWS CloudHSM.
  3. OpenSSL installed on your EC2 instance (we recommend version 3.0.0 or newer).

Step 1: Create a KMS key without key material in AWS KMS

The first step is to create a new KMS key. You can do this through the AWS KMS console or the AWS CLI, or by running the CreateKey API operation.

When you create your key, keep the following guidance in mind:

  • Set the key material origin to External so that no key material is created for this new key.
  • According to NIST SP 800-57 guidance and cryptography best practice, in general, you should use a single key for only one purpose (for example, if you use an RSA key for encryption, you shouldn’t also use that key for signing). Select the key usage that best suits your use case.
  • Make sure that the key spec match the algorithm specification of the key that you are trying to import from CloudHSM.
  • If you want to use the key in multiple AWS Regions (for example, to avoid the need for a cross-Region call to access the key), consider using a multi-Region key.

To create a KMS key using the AWS CLI

  • Run the following command:
    aws kms create-key --origin EXTERNAL --key-spec ECC_NIST_P256 --key-usage SIGN_VERIFY

Step 2: Download the wrapping public key and import token from AWS KMS

After you create the key, download the wrapping key and import token.

The wrapping key spec and the wrapping algorithm that you select depend on the key that you’re trying to import. AWS KMS supports several standard RSA wrapping algorithms and a two-step hybrid wrapping algorithm. CloudHSM supports both wrapping algorithms as well.

In general, an RSA wrapping algorithm (RSAES_OAEP_SHA_*) with a key spec of RSA_4096 should be sufficient for wrapping ECC private keys because it can wrap the key material completely. However, when importing RSA private keys, you will need to use the two-step hybrid wrapping algorithm (RSA_AES_KEY_WRAP_SHA_*) due to their large key size. The overall process is the same as what’s shown here, but the two-step hybrid wrapping algorithm requires that you encrypt your key material with an Advanced Encryption Standard (AES) symmetric key that you generate, and then encrypt the AES symmetric key with the RSA public wrapping key. Additionally, when you select the wrapping algorithm, you also have a choice between the SHA-1 or SHA-256 hashing algorithm. We recommend that you use the SHA-256 hashing algorithm whenever possible.

Note that each wrapping public key and import token set is valid for 24 hours. If you don’t use the set to import key material within 24 hours of downloading it, you must download a new set.

To download the wrapping public key and import token from AWS KMS

  1. Run the following command. Make sure to replace <KMS KeyID> with the key ID of the KMS key that you created in the previous step. The key ID is the last part of the key ARN after :key/ (for example, arn:aws:kms:us-east-1:<AWS Account ID>:key/<Key ID>). “ImportToken.b64” represents the wrapping token, and “WrappingPublicKey.b64” represents the import token.
    aws kms get-parameters-for-import \
    --key-id <KMS KeyID> \
    --wrapping-algorithm RSAES_OAEP_SHA_256 \
    --wrapping-key-spec RSA_4096 \
    --query "[ImportToken, PublicKey]" \
    --output text \
    | awk '{print $1 > "ImportToken.b64"; print $2 > "WrappingPublicKey.b64"}'

  2. Decode the base64 encoding.
    openssl enc -d -base64 -A -in WrappingPublicKey.b64 -out WrappingPublicKey.bin

To convert the wrapping public key from DER to PEM format

  • The key import pem command in CloudHSM CLI requires that the public key is in PEM format. AWS KMS outputs public keys in the DER format, so you must convert the wrapping public key to PEM format. To convert the public key to PEM format, run the following command:
    openssl rsa -pubin -in WrappingPublicKey.bin -inform DER -outform PEM -out WrappingPublicKey.pem

Step 3: Import the wrapping key provided by AWS KMS into CloudHSM

Now that you have created the KMS key and made the necessary preparations to import it, switch to CloudHSM to import the key.

To import the wrapping key

  1. Log in to your EC2 instance that has the CloudHSM CLI installed and run the following command to use it in an interactive mode:
    /opt/cloudhsm/bin/cloudhsm-cli interactive

  2. Log in with your crypto user credential. Make sure to replace <YourUserName> with your own information and supply your password when prompted.
    login --username <YourUserName> --role crypto-user

  3. Import the wrapping key and set the attribute allowing this key to be used for wrapping other keys.
    key import pem --path ./WrappingPublicKey.pem --label <kms-wrapping-key> --key-type-class rsa-public --attributes wrap=true

    You should see an output similar to the following:

    {
      "error_code": 0,
      "data": {
        "key": {
          "key-reference": "0x00000000002800c2",
          "key-info": {
            "key-owners": [
              {
                "username": "<YourUserName>",
                "key-coverage": "full"
              }
            ],
            "shared-users": [],
            "cluster-coverage": "full"
          },
          "attributes": {
            "key-type": "rsa",
            "label": "<kms-wrapping-key>",
            "id": "0x",
            "check-value": "0x5efd07",
            "class": "public-key",
            "encrypt": false,
            "decrypt": false,
            "token": true,
            "always-sensitive": false,
            "derive": false,
            "destroyable": true,
            "extractable": true,
            "local": false,
            "modifiable": true,
            "never-extractable": false,
            "private": true,
            "sensitive": false,
            "sign": false,
            "trusted": false,
            "unwrap": false,
            "verify": false,
            "wrap": true,
            "wrap-with-trusted": false,
            "key-length-bytes": 1024,
            "public-exponent": "0x010001",
            "modulus": "0xd7683010 … b6fc9df07",
            "modulus-size-bits": 4096
          }
        },
        "message": "Successfully imported key"
      }
    }

  4. From the output, note the value for the key label (<kms-wrapping-key> in this example) because you will need it for the next step.

Step 4: Wrap the private key inside CloudHSM with the imported wrapping public key from AWS KMS

Now that you have imported the wrapping key into CloudHSM, you can wrap the private key that you want to import to AWS KMS by using the wrapping key.

Important: Only the owner of a key—the crypto user who created the key—can wrap the key. In addition, the key that you want to wrap must have the extractable attribute set to true.

To wrap the private key

  1. Use the key wrap command in the CloudHSM CLI to wrap the private key that’s stored in CloudHSM. Make sure to replace the following placeholder values with your own information:
    • rsa-oaep specifies the wrapping algorithm.
    • --payload-filter is used to define the key that you want to wrap out of the HSM. You can use the key reference (for example, key-reference=0x00000000002800c2) or reference key attributes, such as the key label. In our example, we used the key label ec-priv-import-to-kms.
    • --wrapping-filter is used to define the key that you will use to wrap out the payload key. This should be the wrapping key that you imported previously from AWS KMS, which was labeled kms-wrapping-key in Step 3.3.
    • --hash-function defines the hash function used as part of the OAEP encryption. This should match the wrapping algorithm that you specified when you got the import parameters from AWS KMS. In our example, it should be SHA-256 because we selected RSAES_OAEP_SHA_256 as the wrapping algorithm previously.
    • --mgf defines the mask generation function used as part of the OAEP encryption. The mask hash function must match the signing mechanism hash function, which is SHA-256 in this example.
    • --path defines the path to the binary file where the wrapped key data will be saved. In this example, we name the file EncryptedECC_P256KeyMaterial.bin but you can specify a different name.
    key wrap rsa-oaep --payload-filter attr.label=ec-priv-import-to-kms --wrapping-filter attr.label=kms-wrapping-key --hash-function sha256 --mgf mgf1-sha256 --path EncryptedECC_P256KeyMaterial.bin

(Optional) To export the public key

  • You can also use the CloudHSM CLI to export the public key of your private key. You will use this key for testing later. Make sure to replace the placeholder values <ec-priv-import-to-kms> and <KeyName.pem> with your own information.
    key generate-file --encoding pem --path <KeyName.pem> --filter attr.label=<ec-priv-import-to-kms>

Step 5: Import the wrapped private key to AWS KMS

Now that you’ve wrapped the private key from CloudHSM, you can import it into AWS KMS.

Note that you have the option to set an expiration time for your imported key. After the expiration time passes, AWS KMS deletes your imported key automatically.

To import the wrapped private key to AWS KMS

  1. If you have been using the CLI or API, the import token is base64 encoded. You must decode the token from base64 to binary format before it can be used. You can use OpenSSL to do this.
    openssl enc -d -base64 -A -in ImportToken.b64 -out ImportToken.bin

  2. Run the following command to import the wrapped private key. Make sure to replace <KMS KeyID> with the key ID of the KMS key that you created in Step 1.
    aws kms import-key-material --key-id <KMS KeyID> \
    --encrypted-key-material fileb://EncryptedECC_P256KeyMaterial.bin \
    --import-token fileb://ImportToken.bin \
    --expiration-model KEY_MATERIAL_DOES_NOT_EXPIRE

Test whether your private key was imported successfully

The nature of asymmetric cryptography means that a digital signature produced by your private key should produce the same signature on the same message, regardless of the tool that you used to perform the signing operation. To verify that your imported private key functions the same in both CloudHSM and AWS KMS, you can perform a signing operation and compare the signature on CloudHSM and AWS KMS to make sure that they are the same.

Another way to check that your imported private key functions are the same in AWS KMS is to perform a signing operation and then verify the signature by using the corresponding public key that you exported from CloudHSM in Step 4. We will show you how to use this method to check that your private key was imported successfully.

To test that your private key was imported

  1. Create a simple message in a text file and encode it in base64.
    echo -n 'Testing My Imported Key!' | openssl base64 -out msg_base64.txt

  2. Perform the signing operation by using AWS KMS. Make sure to replace <YourImported KMS KeyID> with your own information.
    aws kms sign --key-id <YourImported KMS KeyID> --message fileb://msg_base64.txt --message-type RAW --signing-algorithm ECDSA_SHA_256

    The following shows the output of the signing operation.

    {
    "KeyId": "arn:aws:kms:us-east-1:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab",
    "Signature": "EXAMPLEXsP11QVTkrSsab2CygcgtodDbSpd+j558B4qINpKIxwIhAMkKwd65mA3roo76ItuHiRsbwO9F0XMyuyKCKEXAMPLE",
    "SigningAlgorithm": "ECDSA_SHA_256"
    }

  3. Save the signature in a separate file called signature.sig and decode it from base64 to binary.
    openssl enc -d -base64 -in signature.sig -out signature.bin

  4. Verify the signature by using the public key that you exported from CloudHSM in Step 4.
    openssl dgst -sha256 -verify <KeyName.pem> -signature signature.bin msg_base64.txt

    If successful, you should see a message that says Verified OK.

Conclusion

In this post, you learned how to import an asymmetric key into AWS KMS from CloudHSM by using the CloudHSM CLI.

Although this post focused on migrating keys from CloudHSM, you can also follow the general directions to import your asymmetric key from elsewhere. When you import a private key, make sure that the imported key matches the key spec and the wrapping algorithm that you choose in AWS KMS.

 
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Mani Manasa Mylavarapu

Mani Manasa Mylavarapu

Manasa is a Software Development Manager at AWS KMS. Manasa leads the development of custom key store features for both the CloudHSM Key Store and External Key Store. Beyond her professional role, Manasa enjoys playing board games and exploring the scenic hikes of Seattle.

Author

Kevin Lee

Kevin is a Senior Product Manager at AWS KMS. Kevin’s work interests include client-side encryption and key management strategy within a multi-tenant environment. Outside of work, Kevin enjoys occasional camping and snowboarding in the Pacific Northwest and playing video games.

Patrick Palmer

Patrick Palmer

Patrick is a Principal Security Specialist Solutions Architect. He helps customers around the world use AWS services in a secure manner, and specializes in cryptography. When not working, he enjoys spending time with his growing family and playing video games.