CVE-2023-0923
Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.
NVD · uneditedA flaw was found in the Kubernetes service for notebooks in RHODS, where it does not prevent pods from other namespaces and applications from making requests to the Jupyter API. This flaw can lead to file content exposure and other issues.
Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.
dbcve analysis · high confidenceA flaw in the Kubernetes notebook service in RHODS (Red Hat OpenShift Data Science) fails to enforce proper namespace isolation, allowing pods and applications from other namespaces to make unauthorized requests to the Jupyter API. This cross-namespace access vulnerability enables attackers to access file contents and potentially execute arbitrary code within notebook contexts.
Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.
Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.
NVD · CPE data>= 1.22, < 1.22.1-3CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.
From the vector- Attack vector
- Network
- Complexity
- Low
- Privileges
- None
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- High
- Integrity
- High
- Availability
- High
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.
dbcve checksWork through these to decide whether this CVE applies to you.
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Identify RHODS installation and versionRun 'oc get subscription rhoai -n redhat-ods-operator -o jsonpath={.status.currentCSV}' or check the operator namespace for the installed version. Also check 'oc get pods -n redhat-ods-operator' for the rhods-operator version tag.Affected if The installed version is 1.22 or later but earlier than 1.22.1-3 (the version string matches 1.22.x where x is 0-2, or falls between 1.22 and 1.22.1-3).
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Confirm Jupyter API service is deployedRun 'oc get svc jupyterhub -n redhat-ods-applications' or check for notebook-controller pods in the redhat-ods-applications namespace.Affected if The JupyterHub or notebook service exists in the 'redhat-ods-applications' namespace, indicating the vulnerable component is present.
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Verify namespace isolation configurationCheck for existing Kubernetes NetworkPolicies in the redhat-ods-applications namespace: 'oc get networkpolicy -n redhat-ods-applications'. Also verify service role bindings: 'oc get rolebinding -n redhat-ods-applications | grep -i jupyter'.Affected if No NetworkPolicy exists to restrict Jupyter API access to specific namespaces, or overly permissive RBAC bindings allow cross-namespace access.
A user is affected if Red Hat OpenShift Data Science is installed with a version in the range 1.22 to 1.22.1-3 (exclusive of 1.22.1-3) and the Jupyter API service is exposed without namespace isolation controls.
Generated from the published advisory. Verify against your own configuration.
Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.
dbcve · scoped1.22.1-3
Implement Kubernetes NetworkPolicies and/or RBAC controls to restrict Jupyter API access to only authorized namespaces and service accounts within the OpenShift cluster.
1.22.1-3
- Identify the current version of OpenShift Data Science by checking the RHODS operator version in the OpenShift console or via oc CLI
- Review the OpenShift Data Science upgrade documentation at access.redhat.com for pre-upgrade requirements
- Create a backup of any critical data and configurations
- Perform the upgrade to version 1.22.1-3 or later following the documented upgrade procedure
- Verify the Jupyter API authorization controls are functioning correctly post-upgrade by testing cross-namespace access restrictions
Generated from the published advisory — verify against the referenced sources before acting.
- Consultation4.0 h
- Implementation8.0 h
- Testing4.0 h
- Review / QA2.0 h
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Scan for this in your stack
Free · runs locallyCheck whether your project pulls in CVE-2023-0923 — or any other known-vulnerable package — straight from your lock files. Free and open source; it runs locally and uploads nothing.
References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.
Primary sourcesPractitioner notes
ContributedPeer-ranked notes from engineers who’ve handled CVE-2023-0923 in production — separate from our analysis above.
The advisory tells you what broke. It rarely tells you what actually worked. If you’ve dealt with this one, that detail is what the next engineer is searching for.
- The version that genuinely resolved it — not the one the vendor claimed
- A config change or rule that shut the vector down
- A gotcha in the upgrade path that cost you an afternoon
No notes yet
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- Version or environment caveats, and links to real fixes
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