RLSA-2026:26323 (CVE-2026-24734)
Vulnerability from osv_rocky – Published: 2026-06-17 12:03 – Updated: 2026-07-01 12:06 – Source website
VLAI
Summary
Important: tomcat security update
Details
Apache Tomcat is a servlet container for the Java Servlet and JavaServer Pages (JSP) technologies.
Security Fix(es):
- tomcat: Apache Tomcat: Certificate revocation bypass due to improper OCSP response validation (CVE-2026-24734)
For more details about the security issue(s), including the impact, a CVSS score, acknowledgments, and other related information, refer to the CVE page(s) listed in the References section.
Severity
7.4 (High)
References
| URL | Type | |
|---|---|---|
{
"affected": [
{
"package": {
"ecosystem": "Rocky Linux:9",
"name": "tomcat",
"purl": "pkg:rpm/rocky-linux/tomcat?distro=rocky-linux-9-x86-64\u0026epoch=1"
},
"ranges": [
{
"database_specific": {
"yum_repository": "AppStream"
},
"events": [
{
"introduced": "0"
},
{
"fixed": "1:9.0.117-1.el9_8"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"credits": [
{
"name": "Rocky Enterprise Software Foundation"
},
{
"name": "Red Hat"
}
],
"details": "Apache Tomcat is a servlet container for the Java Servlet and JavaServer Pages (JSP) technologies.\n\nSecurity Fix(es):\n\n* tomcat: Apache Tomcat: Certificate revocation bypass due to improper OCSP response validation (CVE-2026-24734)\n\nFor more details about the security issue(s), including the impact, a CVSS score, acknowledgments, and other related information, refer to the CVE page(s) listed in the References section.",
"id": "RLSA-2026:26323",
"modified": "2026-07-01T12:06:45.264611Z",
"published": "2026-06-17T12:03:08.073041Z",
"references": [
{
"type": "ADVISORY",
"url": "https://errata.rockylinux.org/RLSA-2026:26323"
},
{
"type": "REPORT",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2440426"
}
],
"schema_version": "1.7.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N",
"type": "CVSS_V3"
}
],
"summary": "Important: tomcat security update",
"upstream": [
"CVE-2026-24734"
]
}
Loading…
Loading…
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.
Loading…
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.
Loading…
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.
Loading…