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Full vulnerability report · 2026
CVE-2026-34478High confidence

Apache Log4j Core: Log injection in Rfc5424Layout due to silent configuration incompatibility

Apache Software Foundation · Apache Log4j Core

6.9MediumCVSS 4.0
Recommended action
Scheduled

Medium technical severity with no CISA KEV confirmation; remediate through the normal risk-based patch cycle unless local exposure raises the priority.

Patch available
R
Operational reassessment

Published severity in operational context

Open reassessment dashboard →
Published severityMediumOperational priority:Medium, unchanged from published severity.unchanged

Evidence used

  • No CISA KEV confirmation is currently recorded.
  • The selected CVSS metric records a network-reachable, unauthenticated path with no user interaction.
  • EPSS is 1.19% for the current model date.

Compensating controls

  • Validate the affected product branch and deploy the verified fixed release.
  • Restrict the affected network interface to trusted sources where business-safe.
  • Monitor vendor guidance and exploitation sources for a material change.

Verification

  1. Confirm that the asset runs Apache Software Foundation Apache Log4j Core and falls inside the recorded affected range.
  2. Verify the installed build against the product-specific fixed version after deployment.
  3. Validate exposure, authentication requirements and compensating controls in the actual environment.
  4. Reopen this reassessment when CVSS, KEV, EPSS, exploit evidence or remediation changes.
Mitigation target: As exposure requiresRemediation target: Within 365 days

This automated reassessment organises public evidence. It does not know asset exposure, business impact or control effectiveness and does not replace CVSS or a human risk decision.

Distribution package intelligence

Release-specific package status

Debian, ubuntu findings are scoped to the named distribution, release and source package. An absent finding does not mean a package is unaffected.

10 package states
Repository candidate not checked

A published vendor fix does not prove that a matching update is enabled and installable on a particular asset. Confirm the local package candidate before scheduling remediation.

Distribution releaseSource packageVendor stateFixed versionEvidence
Debian trixietrixie · sourceapache-log4j1.2Not affectedDebian marks this release not affected (fixed-version marker 0).Not published in this feedDebian Security Tracker ↗Source updated 6 Oct 2026
Debian trixietrixie · sourceapache-log4j2Not affectedDebian marks this release not affected (fixed-version marker 0).Not published in this feedDebian Security Tracker ↗Source updated 6 Oct 2026
Debian bookwormbookworm · sourceapache-log4j1.2Not affectedDebian marks this release not affected (fixed-version marker 0).Not published in this feedDebian Security Tracker ↗Source updated 6 Oct 2026
Debian bookwormbookworm · sourceapache-log4j2Not affectedDebian marks this release not affected (fixed-version marker 0).Not published in this feedDebian Security Tracker ↗Source updated 6 Oct 2026
Debian forkyforky · sourceapache-log4j1.2Not affectedDebian marks this release not affected (fixed-version marker 0).Not published in this feedDebian Security Tracker ↗Source updated 6 Oct 2026
Debian forkyforky · sourceapache-log4j2Not affectedDebian marks this release not affected (fixed-version marker 0).Not published in this feedDebian Security Tracker ↗Source updated 6 Oct 2026
Debian sidsid · sourceapache-log4j1.2Not affectedDebian marks this release not affected (fixed-version marker 0).Not published in this feedDebian Security Tracker ↗Source updated 6 Oct 2026
Debian sidsid · sourceapache-log4j2Not affectedDebian marks this release not affected (fixed-version marker 0).Not published in this feedDebian Security Tracker ↗Source updated 6 Oct 2026
Ubuntu 24.04 LTSnoble · standard archiveapache-log4j1.2Under evaluationCanonical reports that the package might be affected and still needs evaluation or fixing.Not published in this feedCanonical Ubuntu Security ↗Source updated 5 Oct 2026
Ubuntu 24.04 LTSnoble · standard archiveapache-log4j2Under evaluationCanonical reports that the package might be affected and still needs evaluation or fixing.Not published in this feedCanonical Ubuntu Security ↗Source updated 5 Oct 2026
Open-source package ranges4 source-attributed ranges

These OSV and GitHub advisory ranges apply only to the named package and ecosystem. A listed fixed version is not a universal product patch or proof that an update is installed.

Ecosystem and packageAffected rangeFirst fixed versionEvidence
Mavenorg.apache.logging.log4j:log4j-coreECOSYSTEM: introduced 2.21.0; fixed 2.25.42.25.4OSV record ↗aggregator derived · 10 Sep 2026
Mavenorg.apache.logging.log4j:log4j-coreECOSYSTEM: introduced 3.0.0-beta1; last affected 3.0.0-beta3Not statedOSV record ↗aggregator derived · 10 Sep 2026
mavenorg.apache.logging.log4j:log4j-core>= 2.21.0, < 2.25.42.25.4GitHub advisory ↗github reviewed aggregator · 14 Apr 2026
mavenorg.apache.logging.log4j:log4j-core>= 3.0.0-beta1, <= 3.0.0-beta3Not statedGitHub advisory ↗github reviewed aggregator · 14 Apr 2026
Direct vendor intelligence

Authoritative vendor CSAF and VEX advisories

Structured product status and remediation from the issuing vendor. Product-state explanations are always visible; large lists can be searched or downloaded.

1 current
CVE-2026-34478 · CSAF 2.0 · revision 3 · finalRed Hat Product Securityorg.apache.logging.log4j/log4j-core: Apache Log4j Core: Log injection via CRLF sequences due to configuration attribute renames
28 known affected

The vendor explicitly identifies these products as affected by this CVE.

  • redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server
  • redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server
  • log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4
  • log4j-core as a component of Red Hat build of Apicurio Registry 2
  • log4j-core as a component of Red Hat build of Apicurio Registry 3
  • log4j-core as a component of Red Hat build of OptaPlanner 8
  • log4j-jcl as a component of Red Hat Enterprise Linux 9
  • log4j-slf4j as a component of Red Hat Enterprise Linux 9
  • log4j.src as a component of Red Hat Enterprise Linux 9
  • bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
  • bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
  • redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3
Summary
A flaw was found in Apache Log4j Core. This vulnerability allows for log injection through the use of Carriage Return Line Feed (CRLF) sequences. This occurs because security-related configuration attributes were silently renamed, impacting users who directly configure Rfc5424Layout with stream-based syslog services. An attacker could exploit this to inject malicious data into log files, potentially obscuring critical security events or manipulating system records.
Remediation
Before applying the update, back up your existing installation, including all applications, configuration files, databases and database settings. The References section of this erratum contains a download link (you must log in to download the update).
Optional official sources

National CERT insights
?CERT means Computer Emergency Response Team; CSIRT is the closely related term Computer Security Incident Response Team.

Choose official national sources for this report. Each advisory shows its original language. Your selection is remembered on this device and included in shared links.

Official European source

ENISA European Vulnerability Database

Official EUVD identifiers, advisory evidence and known-exploited context. Missing fields are not treated as evidence of low risk.

1 current
ENISA EUVD identifier

EUVD-2026-21408

No EUVD known-exploited evidence

ENISA has published the identifier mapping but no EUVD description has been stored yet.

EUVD state
Present in the current official mapping
Known exploitation
Not present in the current ENISA EUVD known-exploited dataset. This is not proof of no exploitation.
ENISA score
Not supplied in the stored EUVD record
Advisory evidence
No linked advisory details stored yet
Recommended actionScheduled

Medium technical severity with no CISA KEV confirmation; remediate through the normal risk-based patch cycle unless local exposure raises the priority.

Patch available
01

What, why and how

Apache Log4j Core's Rfc5424Layout https://logging.apache.org/log4j/2.x/manual/layouts.html#RFC5424Layout , in versions 2.21.0 through 2.25.3, is vulnerable to log injection via CRLF sequences due to undocumented renames of security-relevant configuration attributes. Two distinct issues affect users of stream-based syslog services who configure Rfc5424Layout directly: * The newLineEscape attribute was silently renamed, causing newline escaping to stop working for users of TCP framing (RFC 6587), exposing them to CRLF injection in log output. * The useTlsMessageFormat attribute was silently renamed, causing users of TLS framing (RFC 5425) to be silently downgraded to unframed TCP (RFC 6587), without newline escaping. Users of the SyslogAppender are not affected, as its configuration attributes were not modified. Users are advised to upgrade to Apache Log4j Core 2.25.4, which corrects this issue.

What

Apache Log4j Core's Rfc5424Layout https://logging.apache.org/log4j/2.x/manual/layouts.html#RFC5424Layout , in versions 2.21.0 through 2.25.3, is vulnerable to log injection via CRLF sequences due to undocumented renames of security-relevant configuration attributes. Two distinct issues affect users of stream-based syslog services who configure Rfc5424Layout directly: * The newLineEscape attribute was silently renamed, causing newline escaping to stop working for users of TCP framing (RFC 6587), exposing them to CRLF injection in log output. * The useTlsMessageFormat attribute was silently renamed, causing users of TLS framing (RFC 5425) to be silently downgraded to unframed TCP (RFC 6587), without newline escaping. Users of the SyslogAppender are not affected, as its configuration attributes were not modified. Users are advised to upgrade to Apache Log4j Core 2.25.4, which corrects this issue.

Why

The code does not function according to its published specifications, potentially leading to incorrect usage.

How

An attacker operating through a network path may attempt exploitation without authentication or user interaction. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.

What

Apache Log4j Core's Rfc5424Layout https://logging.apache.org/log4j/2.x/manual/layouts.html#RFC5424Layout , in versions 2.21.0 through 2.25.3, is vulnerable to log injection via CRLF sequences due to undocumented renames of security-relevant configuration attributes. Two distinct issues affect users of stream-based syslog services who configure Rfc5424Layout directly: * The newLineEscape attribute was silently renamed, causing newline escaping to stop working for users of TCP framing (RFC 6587), exposing them to CRLF injection in log output. * The useTlsMessageFormat attribute was silently renamed, causing users of TLS framing (RFC 5425) to be silently downgraded to unframed TCP (RFC 6587), without newline escaping. Users of the SyslogAppender are not affected, as its configuration attributes were not modified. Users are advised to upgrade to Apache Log4j Core 2.25.4, which corrects this issue.

Why

The code does not function according to its published specifications, potentially leading to incorrect usage.

How

An attacker operating through a network path may attempt exploitation without authentication or user interaction. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.

02

Exploit reality and attack path

CVSS severity, EPSS forecast probability, public exploit material and CISA-confirmed exploitation are separate signals.

Observed exploitation
?Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.
No confirmed evidence

No CISA KEV match was present at the last successful refresh. This means no confirmation from that source, not proof of no exploitation.

Public PoC / exploit material
?Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.
None recorded

No exploit-tagged reference or CISA SSVC proof-of-concept state is currently recorded. Research may still exist outside the structured feeds.

Likely attack path
a network path → Incorrect Provision of Specified Functionality → cause the confidentiality, integrity or availability impact described by the vendor
Attack surface
Network
Privileges required
None: unauthenticated exploitation is possible
User interaction
None
Attack complexity
Low: no specialised conditions are recorded
Security boundary
Not a CVSS 4.0 base metric
Weakness
?CWE means Common Weakness Enumeration: a standard category for the underlying weakness.
CWE-684 ↗

CWE-684: Incorrect Provision of Specified Functionality. The code does not function according to its published specifications, potentially leading to incorrect usage.

CVSS vector
?CVSS means Common Vulnerability Scoring System. The vector records the metric values used to calculate technical severity.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:N/SC:N/SI:L/SA:N

Common Vulnerability Scoring System 4.0: the compact vector below is decoded into plain language.

AVNetworkAttack vector: The vulnerable component can be reached over a network.ACLowAttack complexity: No specialised conditions are required beyond attacker-controlled input.ATNoneAttack requirements: No additional deployment or execution condition is required.PRNonePrivileges required: The attacker does not need an account or existing privileges.UINoneUser interaction: No action by another user is required.VCNoneVulnerable-system confidentiality: No direct loss is represented by this metric.VINoneVulnerable-system integrity: No direct loss is represented by this metric.VANoneVulnerable-system availability: No direct loss is represented by this metric.SCNoneSubsequent-system confidentiality: No direct loss is represented by this metric.SILowSubsequent-system integrity: A successful attack can cause a limited loss.SANoneSubsequent-system availability: No direct loss is represented by this metric.
Post-exploitation / living off the land
No specific living-off-the-land technique is confirmed in the structured sources. Monitor normal administration tools for activity inconsistent with the affected service's baseline.
NetworkUnauthenticatedCWE-684
A

Official authority intelligence

Only matched European and national findings are included. Language selectors and unavailable sources are omitted.

BSI · German · WID-SEC-2026-2451Oracle Siebel CRM: Mehrere Schwachstellen

Ein entfernter, anonymer oder authentisierter Angreifer kann mehrere Schwachstellen in Oracle Siebel CRM ausnutzen, um die Vertraulichkeit, Integrität und Verfügbarkeit zu gefährden.

Official advisory ↗
BSI · German · WID-SEC-2026-2437Oracle Communications: Mehrere Schwachstellen

Ein entfernter, anonymer oder authentisierter Angreifer kann mehrere Schwachstellen in Oracle Communications ausnutzen, um die Vertraulichkeit, Integrität und Verfügbarkeit zu gefährden.

Official advisory ↗
BSI · German · WID-SEC-2026-2260IBM Operational Decision Manager: Mehrere Schwachstellen

Ein Angreifer kann mehrere Schwachstellen in IBM Operational Decision Manager ausnutzen, um beliebigen Programmcode auszuführen, um seine Privilegien zu erhöhen, um einen Denial of Service Angriff durchzuführen, um Informationen offenzulegen, um Dateien zu manipulieren, und um Sicherheitsvorkehrungen zu umgehen.

Official advisory ↗
BSI · German · WID-SEC-2026-1067Apache log4j: Mehrere Schwachstellen ermöglichen Manipulation von Dateien

Ein Angreifer kann mehrere Schwachstellen in Apache log4j ausnutzen, um Dateien zu manipulieren.

Official advisory ↗
Cyber Security Agency of Singapore · English · CSA-SB-20260415Security Bulletin 15 April 2026

The Cyber Security Agency of Singapore included this CVE in its official Security Bulletin 15 April 2026, published on 15 April 2026. Open the linked bulletin for the product, severity and reference information published in that issue.

Official advisory ↗
CERT-FR · French · CERTFR-2026-AVI-1256Multiples vulnérabilités dans les produits IBM

ord?id=CVE-2026-31802 Référence CVE CVE-2026-3304 https://www.cve.org/CVERecord?id=CVE-2026-3304 Référence CVE CVE-2026-33671 https://www.cve.org/CVERecord?id=CVE-2026-33671 Référence CVE CVE-2026-33672 https://www.cve.org/CVERecord?id=CVE-2026-33672 Référence CVE CVE-2026-33750 https://www.cve.org/CVERecord?id=CVE-2026-33750 Référence CVE CVE-2026-34043 https://www.cve.org/CVERecord?id=CVE-2026-34043 Référence CVE CVE-2026-34355 https://www.cve.org/CVERecord?id=CVE-2026-34355 Référence CVE CVE-2026-34356 https://www.cve.org/CVERecord?id=CVE-2026-34356 Référence CVE CVE-2026-34477 https://www.cve.org/CVERecord?id=CVE-2026-34477 Référence CVE CVE-2026-34478 https://www.cve.org/CVERecord?id=CVE-2026-34478 Référence CVE CVE-2026-34479 https://www.cve.org/CVERecord?id=CVE-2026-34479 Référence CVE CVE-2026-34480 https://www.cve.org/CVERecord?id=CVE-2026-34480 Référence CVE CVE-2026-34481 https://www.cve.org/CVERecord?id=CVE-2026-34481 Référence CVE CVE-2026-3449 https://www.cve.org/CVERecord?id=CVE-2026-3449 Référence CVE CVE-2026-3520 https://www.cve.org/CVERecord?id=CVE-2026-3520 Référence CVE CVE-2026-39865 https://www.cve.org/CVERecord?id=CVE-2026-39865 Référence CVE CVE-2026-40175 https://www.cve.org/CVERecord?id=CVE-2026-40175 Référence CVE CVE-2026-40895 https://www.cve.org/CVERecord?id=CVE-

Official advisory ↗
CERT-FR · French · CERTFR-2026-AVI-1206Multiples vulnérabilités dans les produits IBM

d?id=CVE-2026-33230 Référence CVE CVE-2026-33231 https://www.cve.org/CVERecord?id=CVE-2026-33231 Référence CVE CVE-2026-33236 https://www.cve.org/CVERecord?id=CVE-2026-33236 Référence CVE CVE-2026-33416 https://www.cve.org/CVERecord?id=CVE-2026-33416 Référence CVE CVE-2026-34073 https://www.cve.org/CVERecord?id=CVE-2026-34073 Référence CVE CVE-2026-34197 https://www.cve.org/CVERecord?id=CVE-2026-34197 Référence CVE CVE-2026-34268 https://www.cve.org/CVERecord?id=CVE-2026-34268 Référence CVE CVE-2026-34282 https://www.cve.org/CVERecord?id=CVE-2026-34282 Référence CVE CVE-2026-34477 https://www.cve.org/CVERecord?id=CVE-2026-34477 Référence CVE CVE-2026-34478 https://www.cve.org/CVERecord?id=CVE-2026-34478 Référence CVE CVE-2026-34479 https://www.cve.org/CVERecord?id=CVE-2026-34479 Référence CVE CVE-2026-34480 https://www.cve.org/CVERecord?id=CVE-2026-34480 Référence CVE CVE-2026-34481 https://www.cve.org/CVERecord?id=CVE-2026-34481 Référence CVE CVE-2026-35536 https://www.cve.org/CVERecord?id=CVE-2026-35536 Référence CVE CVE-2026-3621 https://www.cve.org/CVERecord?id=CVE-2026-3621 Référence CVE CVE-2026-3713 https://www.cve.org/CVERecord?id=CVE-2026-3713 Référence CVE CVE-2026-39824 https://www.cve.org/CVERecord?id=CVE-2026-39824 Référence CVE CVE-2026-39892 https://www.cve.org/CVERecord?id=CVE-

Official advisory ↗
CERT-FR · French · CERTFR-2026-AVI-1165Multiples vulnérabilités dans les produits IBM

ord?id=CVE-2026-27970 Référence CVE CVE-2026-28338 https://www.cve.org/CVERecord?id=CVE-2026-28338 Référence CVE CVE-2026-29063 https://www.cve.org/CVERecord?id=CVE-2026-29063 Référence CVE CVE-2026-2950 https://www.cve.org/CVERecord?id=CVE-2026-2950 Référence CVE CVE-2026-32990 https://www.cve.org/CVERecord?id=CVE-2026-32990 Référence CVE CVE-2026-33671 https://www.cve.org/CVERecord?id=CVE-2026-33671 Référence CVE CVE-2026-33672 https://www.cve.org/CVERecord?id=CVE-2026-33672 Référence CVE CVE-2026-33814 https://www.cve.org/CVERecord?id=CVE-2026-33814 Référence CVE CVE-2026-34477 https://www.cve.org/CVERecord?id=CVE-2026-34477 Référence CVE CVE-2026-34478 https://www.cve.org/CVERecord?id=CVE-2026-34478 Référence CVE CVE-2026-34479 https://www.cve.org/CVERecord?id=CVE-2026-34479 Référence CVE CVE-2026-34480 https://www.cve.org/CVERecord?id=CVE-2026-34480 Référence CVE CVE-2026-34481 https://www.cve.org/CVERecord?id=CVE-2026-34481 Référence CVE CVE-2026-35091 https://www.cve.org/CVERecord?id=CVE-2026-35091 Référence CVE CVE-2026-35092 https://www.cve.org/CVERecord?id=CVE-2026-35092 Référence CVE CVE-2026-3621 https://www.cve.org/CVERecord?id=CVE-2026-3621 Référence CVE CVE-2026-38969 https://www.cve.org/CVERecord?id=CVE-2026-38969 Référence CVE CVE-2026-39865 https://www.cve.org/CVERecord?id=CV

Official advisory ↗
CERT-FR · French · CERTFR-2026-AVI-1121Multiples vulnérabilités dans les produits IBM

d?id=CVE-2026-22016 Référence CVE CVE-2026-22018 https://www.cve.org/CVERecord?id=CVE-2026-22018 Référence CVE CVE-2026-22021 https://www.cve.org/CVERecord?id=CVE-2026-22021 Référence CVE CVE-2026-23865 https://www.cve.org/CVERecord?id=CVE-2026-23865 Référence CVE CVE-2026-24733 https://www.cve.org/CVERecord?id=CVE-2026-24733 Référence CVE CVE-2026-24734 https://www.cve.org/CVERecord?id=CVE-2026-24734 Référence CVE CVE-2026-34268 https://www.cve.org/CVERecord?id=CVE-2026-34268 Référence CVE CVE-2026-34282 https://www.cve.org/CVERecord?id=CVE-2026-34282 Référence CVE CVE-2026-34477 https://www.cve.org/CVERecord?id=CVE-2026-34477 Référence CVE CVE-2026-34478 https://www.cve.org/CVERecord?id=CVE-2026-34478 Référence CVE CVE-2026-34479 https://www.cve.org/CVERecord?id=CVE-2026-34479 Référence CVE CVE-2026-34480 https://www.cve.org/CVERecord?id=CVE-2026-34480 Référence CVE CVE-2026-34481 https://www.cve.org/CVERecord?id=CVE-2026-34481 Référence CVE CVE-2026-41254 https://www.cve.org/CVERecord?id=CVE-2026-41254 Référence CVE CVE-2026-46917 https://www.cve.org/CVERecord?id=CVE-2026-46917 Référence CVE CVE-2026-46968 https://www.cve.org/CVERecord?id=CVE-2026-46968 Référence CVE CVE-2026-47010 https://www.cve.org/CVERecord?id=CVE-2026-47010 Référence CVE CVE-2026-47021 https://www.cve.org/CVERecord?id=

Official advisory ↗
CERT-FR · French · CERTFR-2026-AVI-1049Multiples vulnérabilités dans Oracle MySQL

org/CVERecord?id=CVE-2025-14821 Référence CVE CVE-2025-68161 https://www.cve.org/CVERecord?id=CVE-2025-68161 Référence CVE CVE-2026-0540 https://www.cve.org/CVERecord?id=CVE-2026-0540 Référence CVE CVE-2026-0964 https://www.cve.org/CVERecord?id=CVE-2026-0964 Référence CVE CVE-2026-0965 https://www.cve.org/CVERecord?id=CVE-2026-0965 Référence CVE CVE-2026-0966 https://www.cve.org/CVERecord?id=CVE-2026-0966 Référence CVE CVE-2026-0967 https://www.cve.org/CVERecord?id=CVE-2026-0967 Référence CVE CVE-2026-0968 https://www.cve.org/CVERecord?id=CVE-2026-0968 Référence CVE CVE-2026-34477 https://www.cve.org/CVERecord?id=CVE-2026-34477 Référence CVE CVE-2026-34478 https://www.cve.org/CVERecord?id=CVE-2026-34478 Référence CVE CVE-2026-34479 https://www.cve.org/CVERecord?id=CVE-2026-34479 Référence CVE CVE-2026-34480 https://www.cve.org/CVERecord?id=CVE-2026-34480 Référence CVE CVE-2026-34481 https://www.cve.org/CVERecord?id=CVE-2026-34481 Référence CVE CVE-2026-41238 https://www.cve.org/CVERecord?id=CVE-2026-41238 Référence CVE CVE-2026-41239 https://www.cve.org/CVERecord?id=CVE-2026-41239 Référence CVE CVE-2026-41240 https://www.cve.org/CVERecord?id=CVE-2026-41240 Référence CVE CVE-2026-49458 https://www.cve.org/CVERecord?id=CVE-2026-49458 Référence CVE CVE-2026-49459 https://www.cve.org/CVERecord?id=

Official advisory ↗
CERT-FR · French · CERTFR-2026-AVI-1032Multiples vulnérabilités dans les produits IBM

d?id=CVE-2026-33870 Référence CVE CVE-2026-33871 https://www.cve.org/CVERecord?id=CVE-2026-33871 Référence CVE CVE-2026-33916 https://www.cve.org/CVERecord?id=CVE-2026-33916 Référence CVE CVE-2026-33937 https://www.cve.org/CVERecord?id=CVE-2026-33937 Référence CVE CVE-2026-33938 https://www.cve.org/CVERecord?id=CVE-2026-33938 Référence CVE CVE-2026-33939 https://www.cve.org/CVERecord?id=CVE-2026-33939 Référence CVE CVE-2026-33940 https://www.cve.org/CVERecord?id=CVE-2026-33940 Référence CVE CVE-2026-33941 https://www.cve.org/CVERecord?id=CVE-2026-33941 Référence CVE CVE-2026-34477 https://www.cve.org/CVERecord?id=CVE-2026-34477 Référence CVE CVE-2026-34478 https://www.cve.org/CVERecord?id=CVE-2026-34478 Référence CVE CVE-2026-34479 https://www.cve.org/CVERecord?id=CVE-2026-34479 Référence CVE CVE-2026-34480 https://www.cve.org/CVERecord?id=CVE-2026-34480 Référence CVE CVE-2026-35091 https://www.cve.org/CVERecord?id=CVE-2026-35091 Référence CVE CVE-2026-35092 https://www.cve.org/CVERecord?id=CVE-2026-35092 Référence CVE CVE-2026-41254 https://www.cve.org/CVERecord?id=CVE-2026-41254 Référence CVE CVE-2026-41417 https://www.cve.org/CVERecord?id=CVE-2026-41417 Référence CVE CVE-2026-42578 https://www.cve.org/CVERecord?id=CVE-2026-42578 Référence CVE CVE-2026-42580 https://www.cve.org/CVERecord?id=

Official advisory ↗
CERT-FR · French · CERTFR-2026-AVI-0986Multiples vulnérabilités dans les produits IBM

d?id=CVE-2026-31669 Référence CVE CVE-2026-31684 https://www.cve.org/CVERecord?id=CVE-2026-31684 Référence CVE CVE-2026-31685 https://www.cve.org/CVERecord?id=CVE-2026-31685 Référence CVE CVE-2026-31709 https://www.cve.org/CVERecord?id=CVE-2026-31709 Référence CVE CVE-2026-31786 https://www.cve.org/CVERecord?id=CVE-2026-31786 Référence CVE CVE-2026-31787 https://www.cve.org/CVERecord?id=CVE-2026-31787 Référence CVE CVE-2026-33870 https://www.cve.org/CVERecord?id=CVE-2026-33870 Référence CVE CVE-2026-33871 https://www.cve.org/CVERecord?id=CVE-2026-33871 Référence CVE CVE-2026-34477 https://www.cve.org/CVERecord?id=CVE-2026-34477 Référence CVE CVE-2026-34478 https://www.cve.org/CVERecord?id=CVE-2026-34478 Référence CVE CVE-2026-34479 https://www.cve.org/CVERecord?id=CVE-2026-34479 Référence CVE CVE-2026-34480 https://www.cve.org/CVERecord?id=CVE-2026-34480 Référence CVE CVE-2026-35177 https://www.cve.org/CVERecord?id=CVE-2026-35177 Référence CVE CVE-2026-39979 https://www.cve.org/CVERecord?id=CVE-2026-39979 Référence CVE CVE-2026-40164 https://www.cve.org/CVERecord?id=CVE-2026-40164 Référence CVE CVE-2026-4046 https://www.cve.org/CVERecord?id=CVE-2026-4046 Référence CVE CVE-2026-41254 https://www.cve.org/CVERecord?id=CVE-2026-41254 Référence CVE CVE-2026-41284 https://www.cve.org/CVERecord?id=CV

Official advisory ↗
CERT-FR · French · CERTFR-2026-AVI-0958Multiples vulnérabilités dans les produits IBM

d?id=CVE-2026-33558 Référence CVE CVE-2026-33750 https://www.cve.org/CVERecord?id=CVE-2026-33750 Référence CVE CVE-2026-33845 https://www.cve.org/CVERecord?id=CVE-2026-33845 Référence CVE CVE-2026-33846 https://www.cve.org/CVERecord?id=CVE-2026-33846 Référence CVE CVE-2026-34040 https://www.cve.org/CVERecord?id=CVE-2026-34040 Référence CVE CVE-2026-34043 https://www.cve.org/CVERecord?id=CVE-2026-34043 Référence CVE CVE-2026-34197 https://www.cve.org/CVERecord?id=CVE-2026-34197 Référence CVE CVE-2026-34268 https://www.cve.org/CVERecord?id=CVE-2026-34268 Référence CVE CVE-2026-34477 https://www.cve.org/CVERecord?id=CVE-2026-34477 Référence CVE CVE-2026-34478 https://www.cve.org/CVERecord?id=CVE-2026-34478 Référence CVE CVE-2026-34479 https://www.cve.org/CVERecord?id=CVE-2026-34479 Référence CVE CVE-2026-34480 https://www.cve.org/CVERecord?id=CVE-2026-34480 Référence CVE CVE-2026-34481 https://www.cve.org/CVERecord?id=CVE-2026-34481 Référence CVE CVE-2026-34483 https://www.cve.org/CVERecord?id=CVE-2026-34483 Référence CVE CVE-2026-34487 https://www.cve.org/CVERecord?id=CVE-2026-34487 Référence CVE CVE-2026-3449 https://www.cve.org/CVERecord?id=CVE-2026-3449 Référence CVE CVE-2026-34500 https://www.cve.org/CVERecord?id=CVE-2026-34500 Référence CVE CVE-2026-3520 https://www.cve.org/CVERecord?id=CVE

Official advisory ↗
CERT-FR · French · CERTFR-2026-AVI-0920Multiples vulnérabilités dans Oracle Weblogic

sion 15.1.1.0.0 Résumé De multiples vulnérabilités ont été découvertes dans Oracle Weblogic. Elles permettent à un attaquant de provoquer une atteinte à la confidentialité des données et une atteinte à l'intégrité des données. Solutions Se référer au bulletin de sécurité de l'éditeur pour l'obtention des correctifs (cf. section Documentation). Documentation Bulletin de sécurité Oracle Weblogic cpujul2026 du 21 juillet 2026 https://www.oracle.com/security-alerts/cpujul2026.html Référence CVE CVE-2025-68161 https://www.cve.org/CVERecord?id=CVE-2025-68161 Référence CVE CVE-2026-34477 https://www.cve.org/CVERecord?id=CVE-2026-34477 Référence CVE CVE-2026-34478 https://www.cve.org/CVERecord?id=CVE-2026-34478 Référence CVE CVE-2026-34479 https://www.cve.org/CVERecord?id=CVE-2026-34479 Référence CVE CVE-2026-34480 https://www.cve.org/CVERecord?id=CVE-2026-34480 Référence CVE CVE-2026-34481 https://www.cve.org/CVERecord?id=CVE-2026-34481 Référence CVE CVE-2026-5598 https://www.cve.org/CVERecord?id=CVE-2026-5598 Référence CVE CVE-2026-60153 https://www.cve.org/CVERecord?id=CVE-2026-60153 Référence CVE CVE-2026-60196 https://www.cve.org/CVERecord?id=CVE-2026-60196 Référence CVE CVE-2026-60198 https://www.cve.org/CVERecord?id=CVE-2026-60198 Référence CVE CVE-2026-60199 https://www.cve.org/CVERecord?id=CV

Official advisory ↗
CERT-FR · French · CERTFR-2026-AVI-0810Multiples vulnérabilités dans les produits IBM

d?id=CVE-2026-25680 Référence CVE CVE-2026-25681 https://www.cve.org/CVERecord?id=CVE-2026-25681 Référence CVE CVE-2026-27136 https://www.cve.org/CVERecord?id=CVE-2026-27136 Référence CVE CVE-2026-33814 https://www.cve.org/CVERecord?id=CVE-2026-33814 Référence CVE CVE-2026-33870 https://www.cve.org/CVERecord?id=CVE-2026-33870 Référence CVE CVE-2026-33871 https://www.cve.org/CVERecord?id=CVE-2026-33871 Référence CVE CVE-2026-34268 https://www.cve.org/CVERecord?id=CVE-2026-34268 Référence CVE CVE-2026-34282 https://www.cve.org/CVERecord?id=CVE-2026-34282 Référence CVE CVE-2026-34477 https://www.cve.org/CVERecord?id=CVE-2026-34477 Référence CVE CVE-2026-34478 https://www.cve.org/CVERecord?id=CVE-2026-34478 Référence CVE CVE-2026-34479 https://www.cve.org/CVERecord?id=CVE-2026-34479 Référence CVE CVE-2026-34480 https://www.cve.org/CVERecord?id=CVE-2026-34480 Référence CVE CVE-2026-39821 https://www.cve.org/CVERecord?id=CVE-2026-39821 Référence CVE CVE-2026-40175 https://www.cve.org/CVERecord?id=CVE-2026-40175 Référence CVE CVE-2026-40895 https://www.cve.org/CVERecord?id=CVE-2026-40895 Référence CVE CVE-2026-42033 https://www.cve.org/CVERecord?id=CVE-2026-42033 Référence CVE CVE-2026-42034 https://www.cve.org/CVERecord?id=CVE-2026-42034 Référence CVE CVE-2026-42035 https://www.cve.org/CVERecord?id=

Official advisory ↗
CERT-FR · French · CERTFR-2026-AVI-0698Multiples vulnérabilités dans les produits IBM

d?id=CVE-2026-33750 Référence CVE CVE-2026-33870 https://www.cve.org/CVERecord?id=CVE-2026-33870 Référence CVE CVE-2026-33871 https://www.cve.org/CVERecord?id=CVE-2026-33871 Référence CVE CVE-2026-33891 https://www.cve.org/CVERecord?id=CVE-2026-33891 Référence CVE CVE-2026-33894 https://www.cve.org/CVERecord?id=CVE-2026-33894 Référence CVE CVE-2026-33895 https://www.cve.org/CVERecord?id=CVE-2026-33895 Référence CVE CVE-2026-33896 https://www.cve.org/CVERecord?id=CVE-2026-33896 Référence CVE CVE-2026-34268 https://www.cve.org/CVERecord?id=CVE-2026-34268 Référence CVE CVE-2026-34477 https://www.cve.org/CVERecord?id=CVE-2026-34477 Référence CVE CVE-2026-34478 https://www.cve.org/CVERecord?id=CVE-2026-34478 Référence CVE CVE-2026-34479 https://www.cve.org/CVERecord?id=CVE-2026-34479 Référence CVE CVE-2026-34480 https://www.cve.org/CVERecord?id=CVE-2026-34480 Référence CVE CVE-2026-39373 https://www.cve.org/CVERecord?id=CVE-2026-39373 Référence CVE CVE-2026-39892 https://www.cve.org/CVERecord?id=CVE-2026-39892 Référence CVE CVE-2026-40175 https://www.cve.org/CVERecord?id=CVE-2026-40175 Référence CVE CVE-2026-40895 https://www.cve.org/CVERecord?id=CVE-2026-40895 Référence CVE CVE-2026-41168 https://www.cve.org/CVERecord?id=CVE-2026-41168 Référence CVE CVE-2026-41205 https://www.cve.org/CVERecord?id=

Official advisory ↗
CERT-FR · French · CERTFR-2026-AVI-0627Multiples vulnérabilités dans les produits Splunk

d?id=CVE-2026-33055 Référence CVE CVE-2026-33056 https://www.cve.org/CVERecord?id=CVE-2026-33056 Référence CVE CVE-2026-33186 https://www.cve.org/CVERecord?id=CVE-2026-33186 Référence CVE CVE-2026-33228 https://www.cve.org/CVERecord?id=CVE-2026-33228 Référence CVE CVE-2026-33810 https://www.cve.org/CVERecord?id=CVE-2026-33810 Référence CVE CVE-2026-33870 https://www.cve.org/CVERecord?id=CVE-2026-33870 Référence CVE CVE-2026-33871 https://www.cve.org/CVERecord?id=CVE-2026-33871 Référence CVE CVE-2026-34073 https://www.cve.org/CVERecord?id=CVE-2026-34073 Référence CVE CVE-2026-34477 https://www.cve.org/CVERecord?id=CVE-2026-34477 Référence CVE CVE-2026-34478 https://www.cve.org/CVERecord?id=CVE-2026-34478 Référence CVE CVE-2026-34480 https://www.cve.org/CVERecord?id=CVE-2026-34480 Référence CVE CVE-2026-34871 https://www.cve.org/CVERecord?id=CVE-2026-34871 Référence CVE CVE-2026-34872 https://www.cve.org/CVERecord?id=CVE-2026-34872 Référence CVE CVE-2026-34873 https://www.cve.org/CVERecord?id=CVE-2026-34873 Référence CVE CVE-2026-34874 https://www.cve.org/CVERecord?id=CVE-2026-34874 Référence CVE CVE-2026-34875 https://www.cve.org/CVERecord?id=CVE-2026-34875 Référence CVE CVE-2026-34876 https://www.cve.org/CVERecord?id=CVE-2026-34876 Référence CVE CVE-2026-34877 https://www.cve.org/CVERecord?id=

Official advisory ↗
JVN iPedia · Japanese · JVNDB-2026-012618Apache Software FoundationのApache Log4jにおける複数の脆弱性

Apache Log4j Core の Rfc5424Layout (https://logging.apache.org/log4j/2.x/manual/layouts.html#RFC5424Layout) は、バージョン 2.21.0 から 2.25.3 までにおいて、セキュリティに関わる設定属性の非公開の名前変更により、CRLF シーケンスを利用したログインジェクションの脆弱性を引き起こしています。ストリームベースの syslog サービスを直接 Rfc5424Layout で設定しているユーザーに影響を及ぼす2つの異なる問題があります。* newLineEscape 属性が静かに名前変更されており、TCP フレーミング (RFC 6587) ユーザーの改行エスケープ機能が失われ、ログ出力において CRLF インジェクションのリスクが発生しています。* useTlsMessageFormat 属性も静かに名前変更されており、TLS フレーミング (RFC 5425) ユーザーは改行がエスケープされない非フレームTCP (RFC 6587) に静かにダウングレードされてしまいます。SyslogAppender のユーザーは影響を受けません。なぜなら、その設定属性は変更されていないからです。ユーザーはこの問題を修正した Apache Log4j Core 2.25.4 へのアップグレードを推奨されています。

Official advisory ↗
03

Patch and workaround

Operational remediation based on structured source evidence.

Status
?Patch availability is based on structured fixed-version fields and authoritative update references. If no fix is verified, check the vendor advisory before making a change.
Patch available
Affected
Fixed
Action
Before applying the update, back up your existing installation, including all applications, configuration files, databases and database settings. The References section of this erratum contains a download link (you must log in to download the update).
Workaround
No verified workaround is recorded. If business-safe, reduce exposure to the affected interface and allow only trusted sources until authoritative guidance is available.
04

Evidence and provenance

Published 10 Apr 2026 · Last source change 10 Apr 2026, 17:50 UTC · CWE-684 · Incorrect Provision of Specified Functionality

CVE recordCVE.org · 5.2
CVSS sourceCNA
EPSS source
?The date BlackTree first stored a score for this CVE from the daily FIRST EPSS feed.
FIRST · tracked since 2026-08-14
European sourceENISA EUVD · EUVD-2026-21408
Product sourceVendor CSAF · Red Hat Product Security
Remediation sourceVendor CSAF · Red Hat Product Security
CWE sourceCNA
NVD statusNVD enriched

Core structured fields are present and their contributing authorities are shown above.

Material change intelligence

What changed after publication

View recent updates ↗
  1. Affected versionsThe structured affected or fixed version information changed.
    Before
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; log4j-core as a component of Red Hat JBoss Enterprise Application Platform 7; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat AMQ Broker 7.13.6; Red Hat AMQ Broker 7.14.1; Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.12; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.12; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    After
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; log4j-core as a component of Red Hat JBoss Enterprise Application Platform 7; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat AMQ Broker 7.13.6; Red Hat AMQ Broker 7.14.1; Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.13; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.13; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    Red Hat Product Security ↗
  2. Affected versionsThe structured affected or fixed version information changed.
    Before
    2.21.0 < 2.25.4; 3.0.0-beta1 ≤ 3.0.0-beta3 · Fixed: An authoritative update reference is available, but the fixed version is not recorded in the structured CVE fields. Check the linked vendor advisory for the applicable release.
    After
    2.21.0 < 2.25.4; 3.0.0-beta1 ≤ 3.0.0-beta3 · Fixed: Before applying the update, back up your existing installation, including all applications, configuration files, databases and database settings. The References section of this erratum contains a download link (you must log in to download the update).
    Red Hat Product Security ↗
  3. Vendor guidanceAuthoritative vendor guidance changed from remediation: access.redhat.com/CVE-2026-34478 to remediation: access.redhat.com/CVE-2026-34478.
    Before
    remediation: access.redhat.com/CVE-2026-34478
    After
    remediation: access.redhat.com/CVE-2026-34478
    Red Hat Product Security ↗
  4. Affected versionsThe structured affected or fixed version information changed.
    Before
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat AMQ Broker 7; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.12; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.12; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    After
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; log4j-core as a component of Red Hat JBoss Enterprise Application Platform 7; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat AMQ Broker 7.13.6; Red Hat AMQ Broker 7.14.1; Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.12; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.12; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    Red Hat Product Security ↗
  5. Affected versionsThe structured affected or fixed version information changed.
    Before
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat AMQ Broker 7; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.4; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.4; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    After
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat AMQ Broker 7; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.12; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.12; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    Red Hat Product Security ↗
  6. Affected versionsThe structured affected or fixed version information changed.
    Before
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat AMQ Broker 7; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; log4j-core as a component of Red Hat JBoss Enterprise Application Platform 7; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.4; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.4; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    After
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat AMQ Broker 7; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.4; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.4; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    Red Hat Product Security ↗
  7. Affected versionsThe structured affected or fixed version information changed.
    Before
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat AMQ Broker 7; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; log4j-core as a component of Red Hat JBoss Enterprise Application Platform 7; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.9; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.9; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    After
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat AMQ Broker 7; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; log4j-core as a component of Red Hat JBoss Enterprise Application Platform 7; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.4; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.4; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    Red Hat Product Security ↗
  8. Affected versionsThe structured affected or fixed version information changed.
    Before
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat AMQ Broker 7; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; log4j-core as a component of Red Hat JBoss Enterprise Application Platform 7; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.5; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.5; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    After
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat AMQ Broker 7; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; log4j-core as a component of Red Hat JBoss Enterprise Application Platform 7; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.9; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.9; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    Red Hat Product Security ↗
  9. Affected versionsThe structured affected or fixed version information changed.
    Before
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat AMQ Broker 7; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; log4j-core as a component of Red Hat JBoss Enterprise Application Platform 7; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.9; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.9; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    After
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat AMQ Broker 7; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; log4j-core as a component of Red Hat JBoss Enterprise Application Platform 7; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.5; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.5; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    Red Hat Product Security ↗
  10. Affected versionsThe structured affected or fixed version information changed.
    Before
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat AMQ Broker 7; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; log4j-core as a component of Red Hat JBoss Enterprise Application Platform 7; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.7; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.7; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    After
    redhat-user-workloads/rhaiis-cuda-ubi9-3-2-2 as a component of Red Hat AI Inference Server; redhat-user-workloads/rhaiis-cuda-ubi9-3-3 as a component of Red Hat AI Inference Server; log4j-core as a component of Red Hat AMQ Broker 7; log4j-core as a component of Red Hat build of Apache Camel - HawtIO 4; log4j-core as a component of Red Hat build of Apicurio Registry 2; log4j-core as a component of Red Hat build of Apicurio Registry 3; log4j-core as a component of Red Hat build of OptaPlanner 8; log4j-jcl as a component of Red Hat Enterprise Linux 9; log4j-slf4j as a component of Red Hat Enterprise Linux 9; log4j.src as a component of Red Hat Enterprise Linux 9; bazel7.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; bazel8.src as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-aws-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-azure-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; redhat-user-workloads/bootc-cuda-gcp-3-3 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; rhelai3/bootc-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3; log4j-core as a component of Red Hat JBoss Enterprise Application Platform 7; rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI); log4j-core as a component of streams for Apache Kafka 2 · Fixed: Red Hat Data Grid 8.6.1; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:b26253f0a6c6b9e8c8458ecb07e79e9f87ff313491fffc31e342e32bce0a2b3e_arm64 as a component of Red Hat Offline Knowledge Portal 1.2.9; registry.redhat.io/offline-knowledge-portal/rhokp-rhel9@sha256:ec8b14b7a170b689a19cee7820888e81ddc3affc2faada6cc6139644f328bd36_amd64 as a component of Red Hat Offline Knowledge Portal 1.2.9; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:9d8bfb9faa6990854fb39096d9069cb1062fab42d21271499dc5d397e2f4dce4_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-modelmesh-rhel9@sha256:a4d875b52966a2f31d5ea3f1c73620b013702cd570f922792ee125fd23644c5c_amd64 as a component of Red Hat OpenShift AI 2.25; Red Hat build of Apache Camel 4.18.1.P1 for Spring Boot 3.5.16; Streams for Apache Kafka 3.2.1
    Red Hat Product Security ↗
Material fields only · duplicate refreshes suppressed · history retained for the configured operational retention period
CVE published
Fixed release or patch reference recorded
Fixed release recorded from official guidance
Fixed release recorded from official guidance
ENISA EUVD · EUVD-2026-21408↗Red Hat Product Security security advisory↗CVE authority or vendor reference↗Vendor advisory↗Vendor advisory↗Official CVE record (CNA and ADP data)↗NVD record↗
Technical terms and abbreviations used in this report
CVE
Common Vulnerabilities and Exposures: the public identifier for one disclosed vulnerability.
CVSS
Common Vulnerability Scoring System: a technical severity framework; it is not patching priority by itself.
EPSS
Exploit Prediction Scoring System: FIRST's estimate of the probability that exploitation activity will be observed in the next 30 days; it is a forecast, not confirmation.
CWE
Common Weakness Enumeration: the standard category describing the underlying software or hardware weakness.
CNA
CVE Numbering Authority: an organisation authorised to assign and publish CVE records.
CISA ADP
Cybersecurity and Infrastructure Security Agency Authorized Data Publisher: structured enrichment added to a CVE record.
NVD
National Vulnerability Database: NIST's enrichment service for CVE records.
CERT / CSIRT
A computer security incident response team that publishes warnings or coordinates incident response.
PoC
Proof of concept: public material that demonstrates or helps reproduce exploitation.
CSAF
Common Security Advisory Framework: a machine-readable format for security advisories.
LoTL
Living off the land: abuse of legitimate tools or system functions during an attack.
Free version - for non-commercial use only.CVE-2026-34478 · cve.blacktree.nl