CVE-2026-94623
CVE-2026-94623: 1 tracked advisory record across Red Hat. Compare vendor sources and published fix guidance.
Compare the source-linked records below. Ratings and product/version details belong to each advisory; they are not a single CVE-wide score or proof that every listed product is affected. How VulniPulse collects and checks evidence.
Vendor advisory comparison
Red Hat
1 advisory- Advisory severityHigh7.5
High [CVE-2026-94623] Denial of Service via NIXL multi-prompt assertion failure
CVE-2026-94623Source published Source updated
Denial of Service via NIXL multi-prompt assertion failure. Red Hat rates this important (CVSS 7.5). Weakness: CWE-617. Affected products named by the advisory: Red Hat AI Inference Server; Red Hat Enterprise Linux AI (RHEL AI) 3; Red Hat OpenShift AI (RHOAI).
- Related products — impact not confirmed
- Red Hat AI Inference Server
- Red Hat Enterprise Linux AI (RHEL AI) 3
- Red Hat OpenShift AI (RHOAI)
- Source-reported affected versions
- 0.29.0
- Source-reported fixed versions
- No fixed-version detail extracted. This does not mean no fix exists.
- Mitigation guidance
- Restrict access to the inference serving port to trusted internal networks, or run vLLM in standard standalone mode without disaggregated NIXL KV-cache transfer. To limit network reachability on host deployments using firewalld, restrict traffic to authorized client addresses: ``` firewall-cmd --permanent --zone=trusted --add-source=<TRUSTED_NETWORK_CIDR> firewall-cmd --permanent --zone=public --remove-port=8000/tcp firewall-cmd --reload ``` In Red Hat OpenShift AI environments, apply a Kubernetes NetworkPolicy to the inference namespace to block ingress traffic from untrusted pods and external routes. Caveats: Limiting network reachability blocks requests from untrusted external clients. Disabling disaggregated NIXL cache transfer requires reconfiguring workloads to run on standalone nodes, which may decrease distributed throughput for large-scale serving. Warning: Reloading firewall rules or modifying cluster deployment manifests can disrupt ongoing connections and will require restarting running serving pods.
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