CVE-2026-97791 (GCVE-0-2026-97791)
Vulnerability from cvelistv5 – Published: 2026-10-09 10:19 – Updated: 2026-10-09 11:08
VLAI
EPSS
VEX
Title
Apache CXF: STSTokenValidator can accept untrusted SAML assertions because it shares validation state between requests
Summary
In Apache CXF, STSTokenValidator checks whether a SAML assertion is signed by a trusted certificate before deciding to send it to the STS. That result was stored in one object shared by all requests, so one request could read another's result. A remote, unauthenticated attacker could send a forged assertion signed with an untrusted certificate while legitimate requests were being processed, and it could be accepted as trusted without ever reaching the STS. Only services that use STSTokenValidator to validate SAML tokens without alwaysValidateToSts set are affected.
Users are recommended to upgrade to versions 4.2.4 or 4.1.9 or 3.6.13, which fix this issue.
Severity
No CVSS data available.
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://lists.apache.org/thread.html/ssdr417qgms9… | vendor-advisory |
| http://www.openwall.com/lists/oss-security/2026/1… |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Apache Software Foundation | Apache CXF |
Affected:
4.2.0 , < 4.2.4
(semver)
Affected: 4.0.0 , < 4.1.9 (semver) Affected: 0 , < 3.6.13 (semver) |
guessed |
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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.
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- 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.
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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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