CVE-2026-71885 (GCVE-0-2026-71885)
Vulnerability from cvelistv5 – Published: 2026-10-03 08:51 – Updated: 2026-10-03 08:51
VLAI
EPSS
VEX
Title
MLS X.509 credential not bound to the LeafNode signature key
Summary
In Bouncy Castle for Java before 1.86, the Messaging Layer Security (MLS, RFC 9420) implementation did not bind an X.509 credential to a LeafNode's signature_key. LeafNode.verify() checked a leaf's signature against the signature_key carried in the leaf itself, while the credential's X.509 certificate chain was stored but never parsed or validated, so the end-entity certificate's public key was never required to match signature_key as RFC 9420 sec. 5.3 requires. A party could therefore present another party's certificate as its credential while signing the leaf, and the enclosing KeyPackage, with an unrelated key, and be accepted under that other party's identity through KeyPackage.verify() and the Group leaf-validation path. In a deployment that admits external commits without an independent credential-admission check, an unauthenticated attacker could be admitted under a victim's X.509 identity, evict the victim (resynchronization compares whole credentials rather than signing keys), derive the current epoch, decrypt subsequent group messages, and send messages accepted as the victim. TreeKEM.LeafNode now requires the end-entity certificate's subject public key, in the cipher suite's signature encoding, to equal signature_key for an X.509 credential and rejects the leaf otherwise, including an empty chain or a certificate whose key type does not match the cipher suite; certificate-chain and identity validation to a trust anchor remain the application's responsibility per RFC 9420 sec. 5.3.1. Deployments using only basic credentials are unaffected.
Severity
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/bcgit/bc-java/wiki/CVE%E2%80%9… | vendor-advisory |
| https://github.com/bcgit/bc-java/commit/77632a57e… | patch |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Legion of the Bouncy Castle Inc. | BC-JAVA |
Affected:
0 , < 1.86
(maven)
|
guessed |
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}
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"value": "\u003cp\u003eIn Bouncy Castle for Java before 1.86, the Messaging Layer Security (MLS, RFC 9420) implementation did not bind an X.509 credential to a LeafNode\u0027s signature_key. LeafNode.verify() checked a leaf\u0027s signature against the signature_key carried in the leaf itself, while the credential\u0027s X.509 certificate chain was stored but never parsed or validated, so the end-entity certificate\u0027s public key was never required to match signature_key as RFC 9420 sec. 5.3 requires. A party could therefore present another party\u0027s certificate as its credential while signing the leaf, and the enclosing KeyPackage, with an unrelated key, and be accepted under that other party\u0027s identity through KeyPackage.verify() and the Group leaf-validation path. In a deployment that admits external commits without an independent credential-admission check, an unauthenticated attacker could be admitted under a victim\u0027s X.509 identity, evict the victim (resynchronization compares whole credentials rather than signing keys), derive the current epoch, decrypt subsequent group messages, and send messages accepted as the victim. TreeKEM.LeafNode now requires the end-entity certificate\u0027s subject public key, in the cipher suite\u0027s signature encoding, to equal signature_key for an X.509 credential and rejects the leaf otherwise, including an empty chain or a certificate whose key type does not match the cipher suite; certificate-chain and identity validation to a trust anchor remain the application\u0027s responsibility per RFC 9420 sec. 5.3.1. Deployments using only basic credentials are unaffected.\u003c/p\u003e"
}
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"providerMetadata": {
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},
"title": "MLS X.509 credential not bound to the LeafNode signature key",
"x_generator": {
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}
}
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"datePublished": "2026-10-03T08:51:53.292Z",
"dateReserved": "2026-08-08T00:06:06.982Z",
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"state": "PUBLISHED"
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"percentile": "0.07555"
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"nvd": {
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"affected": [
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],
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}
],
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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