Skip to content

sigstore-java has a vulnerability with bundle verification

Low severity GitHub Reviewed Published Dec 5, 2024 in sigstore/sigstore-java • Updated Dec 6, 2024

Package

maven dev.sigstore:sigstore-java (Maven)

Affected versions

< 1.2.0

Patched versions

1.2.0

Description

Summary

sigstore-java has insufficient verification for a situation where a bundle provides a invalid signature for a checkpoint.

Impact

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

Currently checkpoints are only used to ensure the root hash of an inclusion proof was provided by the log in question. Failing to validate that means a bundle may provide an inclusion proof that doesn't actually correspond to the log in question. This may eventually lead a monitor/witness being unable to detect when a compromised logs are providing different views of themselves to different clients.

There are other mechanisms right now that mitigate this, such as the signed entry timestamp. Sigstore-java currently requires a valid signed entry timestamp. By correctly verifying the signed entry timestamp we can make certain assertions about the log signing the log entry (like the log was aware of the artifact signing event and signed it). Therefore the impact on clients that are not monitors/witnesses is very low.

All cryptographic materials and identity information in the bundle must still be verified for the verification to pass. A valid signed entry timestamp is still required for verification 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 v1.1.0

git clone --branch v1.1.0 [email protected]:sigstore/sigstore-java
cd sigstore-java
./gradlew :sigstore-cli:build
tar -xf sigstore-cli/build/distributions/sigstore-cli-1.1.0-SNAPSHOT.tar --strip-components 1

Create some random blob and sign it

dd bs=1 count=50 </dev/urandom > blob
./bin/sigstore-cli sign --bundle=blob.sigstore.json blob

Modify the checkpoint signature on the bundle, this is the last base64 section in the checkpoint, the following diff just swaps changes the last 3 base64 characters to aaa.

"checkpoint": {
+    "envelope": "rekor.sigstore.dev - 1193050959916656506\n29874050\nhnEOPEa6SDzqJDydU+J96TQyfYfqEpsGg0aVbmfjWDw\u003d\n\n— rekor.sigstore.dev wNI9ajBFAiEA4M7t/9b42FzeArRhC6oRvs7UvKwklaFLYfDDGTi2R4kCIBNc2d0VCyUbs3hd+bI7+0RHhvLOdAqYg7j/3xPe2ZPb\n"
-    "envelope": "rekor.sigstore.dev - 1193050959916656506\n29874050\nhnEOPEa6SDzqJDydU+J96TQyfYfqEpsGg0aVbmfjWDw\u003d\n\n— rekor.sigstore.dev wNI9ajBFAiEA4M7t/9b42FzeArRhC6oRvs7UvKwklaFLYfDDGTi2R4kCIBNc2d0VCyUbs3hd+bI7+0RHhvLOdAqYg7j/3xPe2aaa\n"
}
./bin/sigstore-cli verify --bundle=blob.sigstore.json blob
# no errors???!

Patches

Patched in v1.2.0 release (patch: sigstore/sigstore-java@23fb488)
Conformance tests added sigstore/sigstore-conformance#139

Workarounds

Verifiers may chose to verify the checkpoint manually after running KeylessVerifier.verify()

var bundle = Bundle.from(bundleFile, StandardCharsets.UTF_8);
var entry = bundle.getEntries().get(0);
var checkpoint = entry.getVerification().getInclusionProof().parsedCheckpoint();
var signedData = Splitter.on("\n\n").splitToList(entry.getVerification().getInclusionProof().getCheckpoint()).get(0) + "\n";

var tufClient = SigstoreTufClient.builder().usePublicGoodInstance().build();
tufClient.update();
var trustedRoot = tufClient.getSigstoreTrustedRoot();
var tlog =  TransparencyLog.find(trustedRoot.getTLogs(), Hex.decode(entry.getLogID()), entry.getIntegratedTimeInstant());

if (!Verifiers.newVerifier(tlog.get().getPublicKey().toJavaPublicKey()).verify(signedData.getBytes(StandardCharsets.UTF_8), checkpoint.getSignatures().get(0).getSignature())) {
  throw new Exception("Checkpoint signature was invalid");
}

References

@loosebazooka loosebazooka published to sigstore/sigstore-java Dec 5, 2024
Published by the National Vulnerability Database Dec 5, 2024
Published to the GitHub Advisory Database Dec 5, 2024
Reviewed Dec 5, 2024
Last updated Dec 6, 2024

Severity

Low

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 Present
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity Low
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:P/PR:N/UI:N/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N

EPSS score

0.045%
(18th percentile)

Weaknesses

CVE ID

CVE-2024-54140

GHSA ID

GHSA-jp26-88mw-89qr

Source code

Credits

Loading Checking history
See something to contribute? Suggest improvements for this vulnerability.