Introduction
A NodeJS endpoint in the odh-dashboard component of Red Hat OpenShift AI leaks Kubernetes Service Account tokens to unauthorized actors, opening a direct path to cluster resource access. With a CVSS score of 8.5, CVE-2026-5483 represents a significant risk for any organization running OpenShift AI, where the dashboard's service accounts often carry elevated privileges needed to orchestrate machine learning workloads.
Red Hat OpenShift AI builds on top of Red Hat OpenShift to deliver a hybrid AI and MLOps platform. It provides tooling across the full lifecycle of AI and ML experiments, from training and serving to monitoring models. The odh-dashboard is the central user interface and management plane for these activities, making it a high value target in any deployment.
Technical Information
Root Cause
The vulnerability falls under CWE-201: Insertion of Sensitive Information Into Sent Data. The odh-dashboard component exposes a NodeJS endpoint that, when queried, returns Kubernetes Service Account tokens in its response. These tokens are the credentials that services use to authenticate against the Kubernetes API server. The endpoint fails to strip or redact this sensitive material before sending it to the client.
Why This Matters in Context
The odh-dashboard is not a lightweight frontend. It manages custom resources such as OdhApplication and coordinates AI workloads across the cluster. To perform these operations, the service accounts bound to the dashboard typically hold significant Kubernetes RBAC permissions. A token associated with one of these accounts could grant an attacker the ability to list, create, modify, or delete resources well beyond the scope of the dashboard itself.
Attack Flow
Based on the available information, the exploitation path follows these steps:
- An attacker identifies a reachable instance of the
odh-dashboardNodeJS service. In many deployments, the dashboard is exposed via an OpenShift Route or Ingress for user access. - The attacker sends a request to the vulnerable endpoint. The specific endpoint path has not been publicly disclosed by Red Hat.
- The endpoint responds with data that includes one or more Kubernetes Service Account tokens.
- The attacker extracts the token and uses it to authenticate directly against the Kubernetes API server (e.g., via
kubectlor raw API calls). - Depending on the RBAC permissions bound to the compromised service account, the attacker can enumerate secrets, deploy workloads, access persistent volumes, or pivot to other namespaces within the cluster.
Missing Details
The exact vulnerable endpoint path, precise reproduction steps, and a comprehensive list of affected product versions have not been published in the public domain. Administrators should consult the official Red Hat security errata for these specifics.
Affected Systems and Versions
The vulnerability affects the odh-dashboard component within Red Hat OpenShift AI (RHOAI). Red Hat has not publicly disclosed the exact version range in the materials currently available. Organizations should reference advisory RHSA-2026:7397 and Bugzilla entry 2454764 for the definitive list of affected versions and fixed packages.
Vendor Security History
Red Hat operates a dedicated Product Security Center that provides security advisories, maintains a CVE database for tracking vulnerabilities across Red Hat products, and delivers continuous security updates with backporting policies for enterprise lifecycle support. This structured vulnerability management program means that patches and severity classifications for issues like CVE-2026-5483 are typically delivered on a predictable cadence. The publication of RHSA-2026:7397 is consistent with Red Hat's established response process.
References
- NVD Entry for CVE-2026-5483
- Red Hat Security Advisory RHSA-2026:7397
- Red Hat CVE Page for CVE-2026-5483
- Bugzilla: CVE-2026-5483 odh-dashboard Kubernetes Service Account Exposure
- Red Hat OpenShift AI Product Page
- Red Hat Customer Portal: Product Security Center
- Managing Applications in the OpenShift AI Dashboard
