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Full vulnerability report · 2026
CVE-2026-40171High confidence

Jupyter Notebook and JupyterLab token theft via stored XSS in help command linker

jupyter · notebook

Official source article: GitHub GHSA-RCH3-82JR-F9W9 ↗. Check the applicable product and release in the original source.

8.4HighCVSS 4.0
Recommended action
Patch only the product branches with a verified fix

High technical severity; prioritise exposed affected systems while verifying vendor guidance. Verified remediation exists for at least one product or source, but 1 structured product or package state remain unresolved. Apply remediation only to the exact product branch confirmed by its source.

Fix availability varies by product
R
Operational reassessment

Published severity in operational context

Open reassessment dashboard →
Published severityHighOperational priority:High, unchanged from published severity.unchanged

Evidence used

  • No CISA KEV confirmation is currently recorded.
  • EPSS is 0.66% 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 jupyter notebook 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: Within 30 daysRemediation target: Within 180 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.

Cross-source reconciliation

Remediation availability differs by product scope

Verified remediation exists for at least one product or source, but 1 structured product or package state remain unresolved. Apply remediation only to the exact product branch confirmed by its source.

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.

8 package states
Package result overrides the generic status

BlackTree has verified remediation for at least one product or source, but the relevant distribution still reports no fixed package for 1 affected package state shown here. Treat those rows as affected with no fix until that distribution publishes a fixed version.

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 · sourcejupyter-notebookNot affectedDebian marks this release not affected (fixed-version marker 0).Not published in this feedDebian Security Tracker ↗Source updated 6 Oct 2026
Debian trixietrixie · sourcejupyterlabAffected, no fix publishedDebian currently tracks this release as open.Not published in this feedDebian Security Tracker ↗Source updated 6 Oct 2026
Debian bookwormbookworm · sourcejupyter-notebookNot affectedDebian marks this release not affected (fixed-version marker 0).Not published in this feedDebian Security Tracker ↗Source updated 6 Oct 2026
Debian forkyforky · sourcejupyter-notebookVendor fix publishedDebian records a fixed source-package version for this release.7.4.7-3Debian Security Tracker ↗Source updated 6 Oct 2026
Debian forkyforky · sourcejupyterlabVendor fix publishedDebian records a fixed source-package version for this release.4.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-3Debian Security Tracker ↗Source updated 6 Oct 2026
Debian sidsid · sourcejupyter-notebookVendor fix publishedDebian records a fixed source-package version for this release.7.4.7-3Debian Security Tracker ↗Source updated 6 Oct 2026
Debian sidsid · sourcejupyterlabVendor fix publishedDebian records a fixed source-package version for this release.4.4.10+ds1+~3.1.0+~0.16.6+~cs1.4.4-3Debian Security Tracker ↗Source updated 6 Oct 2026
Ubuntu 24.04 LTSnoble · esm-appsjupyter-notebookUnder 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 ranges8 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
PyPIjupyterlabECOSYSTEM: introduced 0; fixed 4.5.74.5.7OSV record ↗aggregator derived · 10 Sep 2026
PyPInotebookECOSYSTEM: introduced 7.0.0; fixed 7.5.67.5.6OSV record ↗aggregator derived · 10 Sep 2026
npm@jupyter-notebook/help-extension>= 7.0.0, <= 7.5.57.5.6GitHub advisory ↗upstream repository advisory · 8 May 2026
npm@jupyter-notebook/help-extensionSEMVER: introduced 7.0.0; fixed 7.5.67.5.6OSV record ↗aggregator derived · 10 Sep 2026
npm@jupyterlab/help-extension<= 4.5.64.5.7GitHub advisory ↗upstream repository advisory · 8 May 2026
npm@jupyterlab/help-extensionSEMVER: introduced 0; fixed 4.5.74.5.7OSV record ↗aggregator derived · 10 Sep 2026
pipjupyterlab<= 4.5.64.5.7GitHub advisory ↗upstream repository advisory · 8 May 2026
pipnotebook>= 7.0.0, <= 7.5.57.5.6GitHub advisory ↗upstream repository advisory · 8 May 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-2026-40171 · CSAF 2.0 · revision 3 · finalRed Hat Product SecurityJupyter Notebook: JupyterLab: @jupyter-notebook/help-extension: @jupyterlab/help-extension: Jupyter Notebook and JupyterLab: Session takeover via stored cross-site scripting
47 fixed

The vendor explicitly identifies these products or versions as containing the fix.

  • registry.redhat.io/mta/mta-solution-server-rhel9@sha256:21fab4b77580795980fd60b24ab1d6a3cc159a9246beccd1c19938bca94edd23_amd64 as a component of Red Hat Migration Toolkit for Applications 8.2
  • registry.redhat.io/mta/mta-solution-server-rhel9@sha256:f8c8651cc5fa016003ef4105f28775e0b225472d2c3135e5f37d1e1f748c515e_arm64 as a component of Red Hat Migration Toolkit for Applications 8.2
  • registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:2bb2dd7720012606878cf627b51b0a578c213f0a7bab293da77fd394f899b68c_arm64 as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:31da636a661576db538dac1f9e20faa7dec811b67b11ba9c22ba09b85a0d0547_amd64 as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:349b7afc66fc1b42411b9b0b089cb291f3466b5e4f9fc5efcdaef779c14c9ec2_ppc64le as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:fd758fc7e8578930e174518401a8a6bc5a0d5e975ccd10e500719dbbe8695522_s390x as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9@sha256:3d58932e2758a93f9eafe1581071ba86af3d9a51646eef97b8f6aa9442381ec0_amd64 as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9@sha256:9d22cb7ad2fb916a4ef21df5e8d425e30ba4126987c664c663e9a0c7c8c44191_ppc64le as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9@sha256:c01ab60b30d02f598984730edc6cbb8b40bcd01c78efa44688fd5ec992f57a50_arm64 as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9@sha256:d6eb02550d96ae57e4e3da5fc2c97d04e03915da3503ce89e8e62ba40337dd6e_s390x as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cuda-py312-rhel9@sha256:83294f4da36532bb4ec60345e89b2266fa7db7ddf18c896ecab81b9a94382ca4_amd64 as a component of Red Hat OpenShift AI 2.25
  • registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cuda-py312-rhel9@sha256:929f62a082f56562f4f5962aec079ea97012e50644d97ed45cacfc029eb433c0_arm64 as a component of Red Hat OpenShift AI 2.25
Summary
A flaw was found in Jupyter Notebook and JupyterLab. A stored cross-site scripting (XSS) vulnerability in the help command linker can be exploited by an attacker who crafts a malicious notebook file. When a user interacts with this file, the XSS is triggered, allowing the attacker to steal authentication tokens. Successful exploitation can lead to a complete takeover of the Jupyter session, enabling arbitrary code execution and information disclosure.
Remediation
Before applying this update, make sure all previously released errata relevant to your system have been applied.
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-2026-28153

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 actionPatch only the product branches with a verified fix

High technical severity; prioritise exposed affected systems while verifying vendor guidance. Verified remediation exists for at least one product or source, but 1 structured product or package state remain unresolved. Apply remediation only to the exact product branch confirmed by its source.

Fix availability varies by product
01

What, why and how

In Jupyter Notebook versions 7.0.0 through 7.5.5, JupyterLab versions 4.5.6 and earlier, and the corresponding @jupyter-notebook/help-extension and @jupyterlab/help-extension packages before 7.5.6 and 4.5.7, a stored cross-site scripting issue in the help command linker can be chained with attacker-controlled notebook content to steal authentication tokens with a single click. An attacker can craft a malicious notebook file containing elements that appear indistinguishable from legitimate controls and trigger execution when a user interacts with them. Successful exploitation allows theft of the user's authentication token and complete takeover of the Jupyter session through the REST API, including reading files, creating or modifying files, accessing kernels to execute arbitrary code, and creating terminals for shell access. This issue has been fixed in Notebook 7.5.6, JupyterLab 4.5.7, @jupyter-notebook/help-extension 7.5.6, and @jupyterlab/help-extension 4.5.7. As a workaround, disable the affected help extensions or set allowCommandLinker to false in the sanitizer configuration.

What

In Jupyter Notebook versions 7.0.0 through 7.5.5, JupyterLab versions 4.5.6 and earlier, and the corresponding @jupyter-notebook/help-extension and @jupyterlab/help-extension packages before 7.5.6 and 4.5.7, a stored cross-site scripting issue in the help command linker can be chained with attacker-controlled notebook content to steal authentication tokens with a single click. An attacker can craft a malicious notebook file containing elements that appear indistinguishable from legitimate controls and trigger execution when a user interacts with them. Successful exploitation allows theft of the user's authentication token and complete takeover of the Jupyter session through the REST API, including reading files, creating or modifying files, accessing kernels to execute arbitrary code, and creating terminals for shell access. This issue has been fixed in Notebook 7.5.6, JupyterLab 4.5.7, @jupyter-notebook/help-extension 7.5.6, and @jupyterlab/help-extension 4.5.7. As a workaround, disable the affected help extensions or set allowCommandLinker to false in the sanitizer configuration.

Why

Attacker-controlled content can reach a browser as executable script without sufficient output encoding or sanitisation.

How

An attacker operating through a network path may attempt exploitation with elevated privileges. If successful, the issue may execute code or commands in the affected security context.

What

In Jupyter Notebook versions 7.0.0 through 7.5.5, JupyterLab versions 4.5.6 and earlier, and the corresponding @jupyter-notebook/help-extension and @jupyterlab/help-extension packages before 7.5.6 and 4.5.7, a stored cross-site scripting issue in the help command linker can be chained with attacker-controlled notebook content to steal authentication tokens with a single click. An attacker can craft a malicious notebook file containing elements that appear indistinguishable from legitimate controls and trigger execution when a user interacts with them. Successful exploitation allows theft of the user's authentication token and complete takeover of the Jupyter session through the REST API, including reading files, creating or modifying files, accessing kernels to execute arbitrary code, and creating terminals for shell access. This issue has been fixed in Notebook 7.5.6, JupyterLab 4.5.7, @jupyter-notebook/help-extension 7.5.6, and @jupyterlab/help-extension 4.5.7. As a workaround, disable the affected help extensions or set allowCommandLinker to false in the sanitizer configuration.

Why

Attacker-controlled content can reach a browser as executable script without sufficient output encoding or sanitisation.

How

An attacker operating through a network path may attempt exploitation with elevated privileges. If successful, the issue may execute code or commands in the affected security context.

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 → Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') → execute code or commands in the affected security context
Attack surface
Network
Privileges required
High: elevated access is required
User interaction
Active interaction required
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-79 ↗

CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting'). The product does not neutralize or incorrectly neutralizes user-controllable input before it is placed in output that is used as a web page that is served to other users.

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:H/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/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.PRHighPrivileges required: The attacker needs elevated or administrative privileges.UIActiveUser interaction: A user must take a deliberate action for exploitation to succeed.VCHighVulnerable-system confidentiality: A successful attack can cause a major loss.VIHighVulnerable-system integrity: A successful attack can cause a major loss.VAHighVulnerable-system availability: A successful attack can cause a major loss.SCNoneSubsequent-system confidentiality: No direct loss is represented by this metric.SINoneSubsequent-system integrity: No direct loss is represented by this metric.SANoneSubsequent-system availability: No direct loss is represented by this metric.
Post-exploitation / living off the land
After compromise, an attacker may use built-in shells, scripting engines, scheduled tasks and native network utilities for discovery, persistence or movement. This is a plausible LoTL path, not evidence that it has occurred for every attack.
NetworkRemote code executionCWE-79
A

Official authority intelligence

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

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.
Fix availability varies by product
Affected
Fixed
Action
Use the product-specific evidence above. Patch only products with a verified fixed release, and keep every affected or under-investigation state without a matching fix in the remediation queue.
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 6 May 2026 · Last source change 8 May 2026, 03:55 UTC · CWE-79 · Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')

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-2026-28153
Product sourceCNA
Remediation sourceVendor CSAF · Red Hat Product Security
CWE sourceCNA
NVD statusNVD awaiting enrichment

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
    >=7.0.0, <= 7.5.5; <=4.5.6; <= 4.5.6; >=7.0.0,<= 7.5.5 · Fixed: No fixed version is explicitly recorded in the structured CVE data.
    After
    >=7.0.0, <= 7.5.5; <=4.5.6; <= 4.5.6; >=7.0.0,<= 7.5.5 · Fixed: Before applying this update, make sure all previously released errata relevant to your system have been applied.
    Red Hat Product Security ↗
  2. Remediation statusRemediation status changed from Awaiting fix to Patch available.
    Before
    Awaiting fix
    After
    Patch available
    Red Hat Product Security ↗
  3. Affected versionsThe structured affected or fixed version information changed.
    Before
    rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · Fixed: registry.redhat.io/mta/mta-solution-server-rhel9@sha256:21fab4b77580795980fd60b24ab1d6a3cc159a9246beccd1c19938bca94edd23_amd64 as a component of Red Hat Migration Toolkit for Applications 8.2; registry.redhat.io/mta/mta-solution-server-rhel9@sha256:f8c8651cc5fa016003ef4105f28775e0b225472d2c3135e5f37d1e1f748c515e_arm64 as a component of Red Hat Migration Toolkit for Applications 8.2; registry.redhat.io/rhoai/odh-th06-cpu-torch210-py312-rhel9@sha256:cdd7d9f982c1f8a94dd4aad43e705274aae1bf0942e0442e60c3973f9c198f23_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-th06-cpu-torch210-py312-rhel9@sha256:f753fdf16a2ebb4241fad71636dea159251e3d54fffcfa9cfd2342271b2d5485_arm64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-th06-cuda130-torch210-py312-rhel9@sha256:5e8cac66dc108c958173412601f1c37e777f53209ff9166add58a011823c87f6_arm64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-th06-cuda130-torch210-py312-rhel9@sha256:ea69ab01a3aaeba9b4db8abbace9014a3044e0f0f13fb7aaaef93acf72f50248_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-th06-rocm64-torch291-py312-rhel9@sha256:b2a253f3dc063a8e1cee441640cce13fcf04918ce453be8f5d488301b1458a91_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:85b77613b0c457e6ddf6c189439f8ff4f14c46ce3e5270f2ddc3b8c59c0d4c20_arm64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:a2c7a670ce95fee5f840960268830f936836663179baf3711219fb9f47339f0a_ppc64le as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:d42aafacf60f441165985ee9b3218cefe0632024b04ae4067cba72b441168a10_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:ff5dea366ee3bc3fd2d1f1f25ab498292bb6c0d02686bbcc13adf4a6e45bfd97_s390x as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9@sha256:267a1971db99ac6de716aa3daf2fa3bc54c473599c5cfcaa2f2d5950b4ffa605_ppc64le as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9@sha256:652fef843e3f43bbfc661a023a693e0acc1dd40c51fd9a6b68e098e6f51fa259_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9@sha256:dc6309e731f39b40f0c9cf9f0eae51ead4f005cae3b72a928f0e5abcf7627a66_s390x as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9@sha256:fc2e2c22e539cb2fe274a0f5ffca4f2761dfff6e5337c88d2257f3767c67efc6_arm64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cuda-py312-rhel9@sha256:18e07656d5aff0c6650f5822aa9d18e81e1310d836ba8ac4c3aa4041a0515448_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cuda-py312-rhel9@sha256:3fc5100f548f5d3ff1b071045803247067374b17dfa249ccafece7789f8f8f03_arm64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-rocm-py312-rhel9@sha256:5f444c198a3821075628b64f05c0cca00792d115d90db80699d71baa5bfd3c13_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9@sha256:190a1cbd8d62718270e459f7a7480d86234491b98b62e42d8ff4729e81b01eed_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9@sha256:e15a412f74c1a63d3228cf473766769cc25245c29f84f189b82998fea7ed0524_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9@sha256:3f3cd6198802052e0fc671b9dcbe125c0bd20d4ba1c51d31d732e5356625eca6_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9@sha256:76860835384964a716661f95118671da6e36bb4d527b44f55d3759d1459e2a6c_arm64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9@sha256:13a0e218aa285b526eed89feaa529e6f24a9b1b2bea0615629e570c1eddc997f_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9@sha256:7c87a18cf11f29594218f740fbd309831cc6948c60390c77666128e26567453c_arm64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9@sha256:945800fe8ee72610795c7ff98c16405b8c5d51e3c6dea7b65e85bbf7a3fbedb6_ppc64le as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9@sha256:ba3298973fcee334a785208bad7928c87212b35a2bd49bf0e83875e240481e95_s390x as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9@sha256:c78ea41efa92d8e87111cb254c1943ae285b326c68a0749c5b77c12ceb8209b5_amd64 as a component of Red Hat OpenShift AI 3.4
    After
    Fixed: registry.redhat.io/mta/mta-solution-server-rhel9@sha256:21fab4b77580795980fd60b24ab1d6a3cc159a9246beccd1c19938bca94edd23_amd64 as a component of Red Hat Migration Toolkit for Applications 8.2; registry.redhat.io/mta/mta-solution-server-rhel9@sha256:f8c8651cc5fa016003ef4105f28775e0b225472d2c3135e5f37d1e1f748c515e_arm64 as a component of Red Hat Migration Toolkit for Applications 8.2; registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:2bb2dd7720012606878cf627b51b0a578c213f0a7bab293da77fd394f899b68c_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:31da636a661576db538dac1f9e20faa7dec811b67b11ba9c22ba09b85a0d0547_amd64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:349b7afc66fc1b42411b9b0b089cb291f3466b5e4f9fc5efcdaef779c14c9ec2_ppc64le as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:fd758fc7e8578930e174518401a8a6bc5a0d5e975ccd10e500719dbbe8695522_s390x as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9@sha256:3d58932e2758a93f9eafe1581071ba86af3d9a51646eef97b8f6aa9442381ec0_amd64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9@sha256:9d22cb7ad2fb916a4ef21df5e8d425e30ba4126987c664c663e9a0c7c8c44191_ppc64le as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9@sha256:c01ab60b30d02f598984730edc6cbb8b40bcd01c78efa44688fd5ec992f57a50_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cpu-py312-rhel9@sha256:d6eb02550d96ae57e4e3da5fc2c97d04e03915da3503ce89e8e62ba40337dd6e_s390x as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cuda-py312-rhel9@sha256:83294f4da36532bb4ec60345e89b2266fa7db7ddf18c896ecab81b9a94382ca4_amd64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-cuda-py312-rhel9@sha256:929f62a082f56562f4f5962aec079ea97012e50644d97ed45cacfc029eb433c0_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-minimal-rocm-py312-rhel9@sha256:a66be05a313a9d90338d9e2525cf457698c2032c8fd10074f2c264ef60301ebb_amd64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9@sha256:61c02bb05464c792a3602e49e6312798cb59c4c1c57ddcaf130ff25c7752b390_amd64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9@sha256:66b60600846f5b73d140d152d5d25b93585eae35eea8fe4c82561e36a5694201_amd64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9@sha256:befe556164f87749e15a72c234a7592ae73257a08eb065feafd7b202493365b7_amd64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9@sha256:70bbd701b998d71acace1c813470f38a9259d4894a99786b31fadb932ad1aeff_amd64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9@sha256:922a9c86c44e5579bdd7b06ab7c19860a46d62ab44d2dc1283e0b956de37c7dc_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9@sha256:dbf1e1e786eec9b8b0f281b7257d0b1a1821cd13dcbd71e28dd0214b8bb397bd_amd64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9@sha256:2f4ab0e14df06f0e558bb73eeb2ee7b7bdab3cf013a012aca27580f986642677_ppc64le as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9@sha256:71338ad87a37ab508b7ae1b34e9a645449493669a305d987c43b024ed1e1d3fc_arm64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9@sha256:cae4b49256f75492270c222d88d9b9fb201095b4276e95b7fc258c10260c81b7_amd64 as a component of Red Hat OpenShift AI 2.25; registry.redhat.io/rhoai/odh-th06-cpu-torch210-py312-rhel9@sha256:cdd7d9f982c1f8a94dd4aad43e705274aae1bf0942e0442e60c3973f9c198f23_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-th06-cpu-torch210-py312-rhel9@sha256:f753fdf16a2ebb4241fad71636dea159251e3d54fffcfa9cfd2342271b2d5485_arm64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-th06-cuda130-torch210-py312-rhel9@sha256:5e8cac66dc108c958173412601f1c37e777f53209ff9166add58a011823c87f6_arm64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-th06-cuda130-torch210-py312-rhel9@sha256:ea69ab01a3aaeba9b4db8abbace9014a3044e0f0f13fb7aaaef93acf72f50248_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-th06-rocm64-torch291-py312-rhel9@sha256:b2a253f3dc063a8e1cee441640cce13fcf04918ce453be8f5d488301b1458a91_amd64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:85b77613b0c457e6ddf6c189439f8ff4f14c46ce3e5270f2ddc3b8c59c0d4c20_arm64 as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:a2c7a670ce95fee5f840960268830f936836663179baf3711219fb9f47339f0a_ppc64le as a component of Red Hat OpenShift AI 3.4; registry.redhat.io/rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9@sha256:d42aafacf60f441165985ee9b3218cefe0632024b04ae4067cba72b441168a10_amd64 as a component of Red Hat OpenShift AI 3.4; and 17 more
    Red Hat Product Security ↗
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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-2026-40171 · cve.blacktree.nl