CVE-2026-94622

HIGH 8.7

Published 2026-09-21 · Last modified 2026-09-22

vLLM versions through 0.29.0 contain a denial of service vulnerability in the NIXL connector's metadata handling for prefill/decode disaggregated deployments. Attackers can send requests with incomplete kv_transfer_params dictionary entries to trigger an uncaught KeyError in EngineCore scheduling, causing the decode engine to terminate and making all routed requests fail until manual restart.

ELEVATED IMPACT

Severe if exploited (CVSS 8.7), but no known exploitation and low modeled probability. Patch on a normal cadence.

Exploitation likelihood

0.6%chance of exploitation in 30 days · 50th percentile

○ In CISA KEV ○ Catalogued PoC

Impact if exploited

8.7CVSS 4.0 · HIGH

ConfidentialityNone
IntegrityNone
AvailabilityHigh

What an attacker needs

✓Access: Reachable over the network — no local access needed
✓Privileges: No account or privileges required
✓User interaction: No user interaction needed
✓Complexity: No special conditions — reliably repeatable
✓Requirements: No special attack requirements

✓ lowers the bar for an attacker · ⚠ raises it

Proof of concept

No public PoC is currently catalogued.

Search for new PoCs

Search GitHub now — results may be empty or unverified.

Tracked sources are checked daily for recent CVEs, including PoCs published after the original disclosure. A later release appears after a tracked source lists it and a refresh succeeds.

Data snapshot: 2026-10-26T13:52:32.101Z

Affected

Vendors Vllm Project Vllm

Products Vllm

Weakness (CWE)

CWE-248: Uncaught Exception

CVSS vector

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

References and research data (JSON)

Packages and version ranges

Each advisory describes its own package and affected ranges. A boundary applies to that range; it is not a universal upgrade recommendation.

vllm PyPI

pkg:pypi/vllm
ECOSYSTEM range
- All earlier versions (introduced 0)
- Fixed boundary (excluded): 0.30.0
97 explicitly listed affected versions
0.0.1, 0.1.0, 0.1.1, 0.1.2, 0.1.3, 0.1.4, 0.1.5, 0.1.6, 0.1.7, 0.10.0, 0.10.1, 0.10.1.1, 0.10.2, 0.11.0, 0.11.1, 0.11.2, 0.12.0, 0.13.0, 0.14.0, 0.14.1, 0.15.0, 0.15.1, 0.16.0, 0.17.0, 0.17.1, 0.18.0, 0.18.1, 0.19.0, 0.19.1, 0.2.0, 0.2.1, 0.2.1.post1, 0.2.2, 0.2.3, 0.2.4, 0.2.5, 0.2.6, 0.2.7, 0.20.0, 0.20.1, 0.20.2, 0.21.0, 0.22.0, 0.22.1, 0.23.0, 0.24.0, 0.25.0, 0.25.1, 0.26.0, 0.27.0, 0.27.1, 0.28.0, 0.29.0, 0.3.0, 0.3.1, 0.3.2, 0.3.3, 0.4.0, 0.4.0.post1, 0.4.1, 0.4.2, 0.4.3, 0.5.0, 0.5.0.post1, 0.5.1, 0.5.2, 0.5.3, 0.5.3.post1, 0.5.4, 0.5.5, 0.6.0, 0.6.1, 0.6.1.post1, 0.6.1.post2, 0.6.2, 0.6.3, 0.6.3.post1, 0.6.4, 0.6.4.post1, 0.6.5, 0.6.6, 0.6.6.post1, 0.7.0, 0.7.1, 0.7.2, 0.7.3, 0.8.0, 0.8.1, 0.8.2, 0.8.3, 0.8.4, 0.8.5, 0.8.5.post1, 0.9.0, 0.9.0.1, 0.9.1, 0.9.2
Additional upstream package constraints
```
{
  "ecosystem": {},
  "database": {
    "source": "https://github.com/pypa/advisory-database/blob/main/vulns/vllm/PYSEC-2026-4004.yaml"
  }
}
```
PyPA · PYSEC-2026-4004 · Updated 2026-09-30T09:15:02.788366747Z

Vendor product assessments

Showing 32 of 344 vendor product statements; 312 omitted. Read the full vendor advisory.

registry.redhat.io/rhoai/odh-kserve-agent-rhel9@sha256:18eb52b8f8ed403671396e49370216a8a553d79dfe33efb3cae79284eb40643a_ppc64le as a component of Red Hat OpenShift AI 3.4 · fixed

Vendor assessment for this product only.

pkg:oci/odh-kserve-agent-rhel9@sha256%3A18eb52b8f8ed403671396e49370216a8a553d79dfe33efb3cae79284eb40643a?arch=ppc64le&repository_url=registry.redhat.io/rhoai/odh-kserve-agent-rhel9&tag=1791468381
- vendor fix: For Red Hat OpenShift AI 3.4.5 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/ Vendor guidance
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-kserve-agent-rhel9@sha256:636ba382740d2c14ace1c03d8474e460dc78929237e1efae7bd2da58605fb9f8_s390x as a component of Red Hat OpenShift AI 3.4 · fixed

Vendor assessment for this product only.

pkg:oci/odh-kserve-agent-rhel9@sha256%3A636ba382740d2c14ace1c03d8474e460dc78929237e1efae7bd2da58605fb9f8?arch=s390x&repository_url=registry.redhat.io/rhoai/odh-kserve-agent-rhel9&tag=1791468381
- vendor fix: For Red Hat OpenShift AI 3.4.5 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/ Vendor guidance
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-kserve-agent-rhel9@sha256:e7063293523536dcb008ff4e9479d05b40a9caa9b0f189318ff1c8362d08602a_amd64 as a component of Red Hat OpenShift AI 3.4 · fixed

Vendor assessment for this product only.

pkg:oci/odh-kserve-agent-rhel9@sha256%3Ae7063293523536dcb008ff4e9479d05b40a9caa9b0f189318ff1c8362d08602a?arch=amd64&repository_url=registry.redhat.io/rhoai/odh-kserve-agent-rhel9&tag=1791468381
- vendor fix: For Red Hat OpenShift AI 3.4.5 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/ Vendor guidance
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-kserve-controller-rhel9@sha256:51997b1a7e5e2f3c0bd76b7d23fda33902843addafcbba6333b27d5c72beb5c4_amd64 as a component of Red Hat OpenShift AI 3.4 · fixed

Vendor assessment for this product only.

pkg:oci/odh-kserve-controller-rhel9@sha256%3A51997b1a7e5e2f3c0bd76b7d23fda33902843addafcbba6333b27d5c72beb5c4?arch=amd64&repository_url=registry.redhat.io/rhoai/odh-kserve-controller-rhel9&tag=1791468368
- vendor fix: For Red Hat OpenShift AI 3.4.5 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/ Vendor guidance
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-kserve-controller-rhel9@sha256:a2967b5e30b4b8c6299abde8dc0fcab8ceb15581aff94dda4f02ac6e6aa05cb7_s390x as a component of Red Hat OpenShift AI 3.4 · fixed

Vendor assessment for this product only.

pkg:oci/odh-kserve-controller-rhel9@sha256%3Aa2967b5e30b4b8c6299abde8dc0fcab8ceb15581aff94dda4f02ac6e6aa05cb7?arch=s390x&repository_url=registry.redhat.io/rhoai/odh-kserve-controller-rhel9&tag=1791468368
- vendor fix: For Red Hat OpenShift AI 3.4.5 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/ Vendor guidance
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-kserve-router-rhel9@sha256:24cf45f8cc50e378b6a7ecb0f42568f6426242af8b2751d60350d04b3817ccd4_s390x as a component of Red Hat OpenShift AI 3.4 · fixed

Vendor assessment for this product only.

pkg:oci/odh-kserve-router-rhel9@sha256%3A24cf45f8cc50e378b6a7ecb0f42568f6426242af8b2751d60350d04b3817ccd4?arch=s390x&repository_url=registry.redhat.io/rhoai/odh-kserve-router-rhel9&tag=1791468401
- vendor fix: For Red Hat OpenShift AI 3.4.5 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/ Vendor guidance
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-kserve-router-rhel9@sha256:3d602b9c38076730a0972ed143ff886d2018ef9ffbcc9ca339ad8dade8bfb05f_ppc64le as a component of Red Hat OpenShift AI 3.4 · fixed

Vendor assessment for this product only.

pkg:oci/odh-kserve-router-rhel9@sha256%3A3d602b9c38076730a0972ed143ff886d2018ef9ffbcc9ca339ad8dade8bfb05f?arch=ppc64le&repository_url=registry.redhat.io/rhoai/odh-kserve-router-rhel9&tag=1791468401
- vendor fix: For Red Hat OpenShift AI 3.4.5 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/ Vendor guidance
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-kserve-router-rhel9@sha256:96ddd9921ce58a1df83c1a89a2046651feaeb2db91e8f48740335ac7096a3457_arm64 as a component of Red Hat OpenShift AI 3.4 · fixed

Vendor assessment for this product only.

pkg:oci/odh-kserve-router-rhel9@sha256%3A96ddd9921ce58a1df83c1a89a2046651feaeb2db91e8f48740335ac7096a3457?arch=arm64&repository_url=registry.redhat.io/rhoai/odh-kserve-router-rhel9&tag=1791468401
- vendor fix: For Red Hat OpenShift AI 3.4.5 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/ Vendor guidance
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-kserve-storage-initializer-rhel9@sha256:006fea51fee2672e37e526aa1d0fdd7e6f6f2dcf428fac12a2cc18b5b8ee8e02_s390x as a component of Red Hat OpenShift AI 3.4 · fixed

Vendor assessment for this product only.

pkg:oci/odh-kserve-storage-initializer-rhel9@sha256%3A006fea51fee2672e37e526aa1d0fdd7e6f6f2dcf428fac12a2cc18b5b8ee8e02?arch=s390x&repository_url=registry.redhat.io/rhoai/odh-kserve-storage-initializer-rhel9&tag=1790958549
- vendor fix: For Red Hat OpenShift AI 3.4.5 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/ Vendor guidance
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-kserve-storage-initializer-rhel9@sha256:35a57dd79362703b69e563f84d18d2ec31359628a246e3c36b52ece728aa9f21_arm64 as a component of Red Hat OpenShift AI 3.4 · fixed

Vendor assessment for this product only.

pkg:oci/odh-kserve-storage-initializer-rhel9@sha256%3A35a57dd79362703b69e563f84d18d2ec31359628a246e3c36b52ece728aa9f21?arch=arm64&repository_url=registry.redhat.io/rhoai/odh-kserve-storage-initializer-rhel9&tag=1790958549
- vendor fix: For Red Hat OpenShift AI 3.4.5 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/ Vendor guidance
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-kserve-storage-initializer-rhel9@sha256:856c7748eb45dbd190fb16fe90a09546ac8febf2f83e41d8068e8ac759442018_amd64 as a component of Red Hat OpenShift AI 3.4 · fixed

Vendor assessment for this product only.

pkg:oci/odh-kserve-storage-initializer-rhel9@sha256%3A856c7748eb45dbd190fb16fe90a09546ac8febf2f83e41d8068e8ac759442018?arch=amd64&repository_url=registry.redhat.io/rhoai/odh-kserve-storage-initializer-rhel9&tag=1790958549
- vendor fix: For Red Hat OpenShift AI 3.4.5 see the following documentation, which will be updated shortly for this release, for important instructions on how to upgrade your cluster and fully apply this errata update: https://docs.redhat.com/en/documentation/red_hat_openshift_ai/ Vendor guidance
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
rhaii/vllm-cpu-rhel9 as a component of Red Hat AI Inference Server · known affected

Vendor assessment for this product only.

pkg:oci/vllm-cpu-rhel9@sha256:5da2be9bd0fa0c7344e8a0b84c0cb8f3a78a1c7fc5fc76db6a7daaa2d71324f9?repository_url=registry.redhat.io/rhaii/vllm-cpu-rhel9
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
- none available: Affected
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
rhaii/vllm-gaudi-rhel9 as a component of Red Hat AI Inference Server · known affected

Vendor assessment for this product only.

pkg:oci/vllm-gaudi-rhel9@sha256:ce1e4fd82dd37d299ce8c64a237971d00faf602f06868c986e81aefa04c283ef?repository_url=registry.redhat.io/rhaii/vllm-gaudi-rhel9
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
- none available: Affected
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
rhaii/vllm-rocm-rhel9 as a component of Red Hat AI Inference Server · known affected

Vendor assessment for this product only.

pkg:oci/vllm-rocm-rhel9@sha256:4d9c1873e151f8c40f13a6b4c71b5f5aea5aca6e75d76a46ccb0784d48932bd7?repository_url=registry.redhat.io/rhaii/vllm-rocm-rhel9
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
- none available: Affected
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
rhaii/vllm-tpu-rhel9 as a component of Red Hat AI Inference Server · known affected

Vendor assessment for this product only.

pkg:oci/vllm-tpu-rhel9@sha256:0c2ac747d67dc0e80162ff05867dd702e474b2217659f19f28b8e3a0c03a942a?repository_url=registry.redhat.io/rhaii/vllm-tpu-rhel9
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
- no fix planned: Will not fix
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
rhaiis/vllm-cuda-rhel9 as a component of Red Hat AI Inference Server · known affected

Vendor assessment for this product only.

pkg:oci/vllm-cuda-rhel9@sha256:73bbc4560132c4aaa9bbd608ce9560eeae7b30bcc8f014da460afa5622139372?repository_url=registry.redhat.io/rhaiis/vllm-cuda-rhel9
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
- none available: Affected
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
rhaiis/vllm-rocm-rhel9 as a component of Red Hat AI Inference Server · known affected

Vendor assessment for this product only.

pkg:oci/vllm-rocm-rhel9@sha256:37b64a8df90756aae0ee96d2f07765adbce5ed5beb2414ac3845806ad2219cfc?repository_url=registry.redhat.io/rhaiis/vllm-rocm-rhel9
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
- none available: Affected
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
rhelai3/bootc-aws-cuda-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3 · known affected

Vendor assessment for this product only.

pkg:oci/bootc-aws-cuda-rhel9@sha256:a754d4d1126e98f203249414b3831182bb15ee6b3643452f167849defc642e4b?repository_url=registry.redhat.io/rhelai3/bootc-aws-cuda-rhel9
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
- none available: Affected
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
rhelai3/bootc-azure-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3 · known affected

Vendor assessment for this product only.

pkg:oci/bootc-azure-rocm-rhel9@sha256:8ea1233b1fb6b82d0aa69e9e4c47d2df242001280c11a61584066c27c5bec3a5?repository_url=registry.redhat.io/rhelai3/bootc-azure-rocm-rhel9
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
- none available: Affected
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
rhelai3/bootc-gaudi-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3 · known affected

Vendor assessment for this product only.

pkg:oci/bootc-gaudi-rhel9@sha256:e1057b59ca1be9501332abf97230855e85c7df858356be0da9dce230ea7e98e1?repository_url=registry.redhat.io/rhelai3/bootc-gaudi-rhel9
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
- no fix planned: Will not fix
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
rhelai3/bootc-rocm-rhel9 as a component of Red Hat Enterprise Linux AI (RHEL AI) 3 · known affected

Vendor assessment for this product only.

pkg:oci/bootc-rocm-rhel9@sha256:38ce057f97034bbb8eaea574d41cc7eebaeaa9265a4cdd966476dd3fac129c3c?repository_url=registry.redhat.io/rhelai3/bootc-rocm-rhel9
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
- none available: Affected
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
rhoai/odh-vllm-gaudi-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known affected

Vendor assessment for this product only.

pkg:oci/odh-vllm-gaudi-rhel9@sha256:87eec3862eb6ddef445f89dcf6fd89add7ef202ea7c563b1ee7347537fb3e250?repository_url=registry.redhat.io/rhoai/odh-vllm-gaudi-rhel9
- workaround: To reduce exposure to this vulnerability, apply the following operational controls: 1. Disable disaggregated KV transfer: Deploy vLLM instances in a standalone configuration or run unified prefill and decode workers rather than disaggregated roles utilizing the NIXL KV cache transfer connector. 2. Restrict network exposure: Apply OpenShift NetworkPolicies or firewall rules to limit access to vLLM inference ports, permitting traffic only from trusted API gateways or internal clients. Caveats: Disabling disaggregated prefill/decode operation prevents multi-node distributed cache sharing and may reduce inference performance for long-context requests. Network restrictions will prevent access from non-whitelisted IP addresses. Warning: Altering the deployment architecture requires restarting vLLM pods or containers, which will cause a temporary service disruption during workload restart.
- no fix planned: Will not fix
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-ai-gateway-payload-processing-rhel9@sha256:1edfd89a924a83901845cd773012a3aeca70c09a2175a87e83351140efc80485_ppc64le as a component of Red Hat OpenShift AI 3.4 · known not affected

Vendor assessment for this product only.
Reason: vulnerable code not present

pkg:oci/odh-ai-gateway-payload-processing-rhel9@sha256%3A1edfd89a924a83901845cd773012a3aeca70c09a2175a87e83351140efc80485?arch=ppc64le&repository_url=registry.redhat.io/rhoai/odh-ai-gateway-payload-processing-rhel9&tag=1791860396
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-eval-hub-rhel9@sha256:cb8f1ce5d2c2ae7a10d841837c7b18d3856f66869fc45d7bc8b4b193a4edbca8_arm64 as a component of Red Hat OpenShift AI 3.4 · known not affected

Vendor assessment for this product only.
Reason: vulnerable code not present

pkg:oci/odh-eval-hub-rhel9@sha256%3Acb8f1ce5d2c2ae7a10d841837c7b18d3856f66869fc45d7bc8b4b193a4edbca8?arch=arm64&repository_url=registry.redhat.io/rhoai/odh-eval-hub-rhel9&tag=1791852583
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-llama-stack-core-rhel9@sha256:0aa47e4978f9ff14ca7e1341d4b26621cb8c271f0dff6fc8324c72afa5dbd17b_arm64 as a component of Red Hat OpenShift AI 3.4 · known not affected

Vendor assessment for this product only.
Reason: vulnerable code not present

pkg:oci/odh-llama-stack-core-rhel9@sha256%3A0aa47e4978f9ff14ca7e1341d4b26621cb8c271f0dff6fc8324c72afa5dbd17b?arch=arm64&repository_url=registry.redhat.io/rhoai/odh-llama-stack-core-rhel9&tag=1790958470
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-maas-controller-rhel9@sha256:e305c12082dbed64798cc8ce855362f5703559f141308a7a0523f94d13886107_ppc64le as a component of Red Hat OpenShift AI 3.4 · known not affected

Vendor assessment for this product only.
Reason: vulnerable code not present

pkg:oci/odh-maas-controller-rhel9@sha256%3Ae305c12082dbed64798cc8ce855362f5703559f141308a7a0523f94d13886107?arch=ppc64le&repository_url=registry.redhat.io/rhoai/odh-maas-controller-rhel9&tag=1791790095
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-mod-arch-autorag-rhel9@sha256:72b8f8d8a63c0664a729ec7afbfaa3e9ddb41d299253ed110b7358a91f55d144_ppc64le as a component of Red Hat OpenShift AI 3.4 · known not affected

Vendor assessment for this product only.
Reason: vulnerable code not present

pkg:oci/odh-mod-arch-autorag-rhel9@sha256%3A72b8f8d8a63c0664a729ec7afbfaa3e9ddb41d299253ed110b7358a91f55d144?arch=ppc64le&repository_url=registry.redhat.io/rhoai/odh-mod-arch-autorag-rhel9&tag=1791860994
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-model-performance-data-rhel9@sha256:4ce3053cb04fdcdb6e2dfc5ba8f51cbd78d0d32c83f9e66ce376d273a592080f_ppc64le as a component of Red Hat OpenShift AI 3.4 · known not affected

Vendor assessment for this product only.
Reason: vulnerable code not present

pkg:oci/odh-model-performance-data-rhel9@sha256%3A4ce3053cb04fdcdb6e2dfc5ba8f51cbd78d0d32c83f9e66ce376d273a592080f?arch=ppc64le&repository_url=registry.redhat.io/rhoai/odh-model-performance-data-rhel9&tag=1790958081
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-pipeline-runtime-minimal-cpu-py312-rhel9@sha256:a320d0547d3267d7ce0a3e004a44aed47d91b885ffe9840a65715e32a08ae0ec_arm64 as a component of Red Hat OpenShift AI 3.4 · known not affected

Vendor assessment for this product only.
Reason: vulnerable code not present

pkg:oci/odh-pipeline-runtime-minimal-cpu-py312-rhel9@sha256%3Aa320d0547d3267d7ce0a3e004a44aed47d91b885ffe9840a65715e32a08ae0ec?arch=arm64&repository_url=registry.redhat.io/rhoai/odh-pipeline-runtime-minimal-cpu-py312-rhel9&tag=1791829069
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-th06-cuda130-torch210-py312-rhel9@sha256:7e0fb9bebdad1ebdef398243022fbfb29f6bd5673c00c4635745e0a92545ab60_arm64 as a component of Red Hat OpenShift AI 3.4 · known not affected

Vendor assessment for this product only.
Reason: vulnerable code not present

pkg:oci/odh-th06-cuda130-torch210-py312-rhel9@sha256%3A7e0fb9bebdad1ebdef398243022fbfb29f6bd5673c00c4635745e0a92545ab60?arch=arm64&repository_url=registry.redhat.io/rhoai/odh-th06-cuda130-torch210-py312-rhel9&tag=1791961113
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
registry.redhat.io/rhoai/odh-trustyai-vllm-orchestrator-gateway-rhel9@sha256:7b75fd02b3628b485fa58e89db548116c941941ec5da885767357e752bd03dd5_ppc64le as a component of Red Hat OpenShift AI 3.4 · known not affected

Vendor assessment for this product only.
Reason: vulnerable code not present

pkg:oci/odh-trustyai-vllm-orchestrator-gateway-rhel9@sha256%3A7b75fd02b3628b485fa58e89db548116c941941ec5da885767357e752bd03dd5?arch=ppc64le&repository_url=registry.redhat.io/rhoai/odh-trustyai-vllm-orchestrator-gateway-rhel9&tag=1791363252
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
rhoai/odh-th-torch-cuda-py312-rhel9 as a component of Red Hat OpenShift AI (RHOAI) · known not affected

Vendor assessment for this product only.
Reason: vulnerable code not in execute path

pkg:oci/odh-th-torch-cuda-py312-rhel9@sha256:efd7b3607b699092c68359d20ef0d0043114191a097637667c0d2cf78fbea702?repository_url=registry.redhat.io/rhoai/odh-th-torch-cuda-py312-rhel9
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00

Known Affected Software Configurations

Vendor	Product	Version range
Vllm	Vllm	≤ 0.29.0

All CVSS metrics

HIGH 8.7 v4.0 · CNA Primary
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
HIGH 7.5 v3.1 · CNA Primary
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
HIGH 8.7 v4.0 · NVD Secondary
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
HIGH 7.5 v3.1 · NVD Secondary
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

References

Patches & mitigations

https://github.com/vllm-project/vllm/pull/54807 issue-trackingpatchIssue TrackingPatchFIXvendor-referenceCVE record · VulnCheck · Updated 2026-09-21T22:04:10.761Z
NVD · CVE-2026-94622 · Updated 2026-09-29T12:47:29.283
PyPA · PYSEC-2026-4004
PyPA · PYSEC-2026-4004 · Updated 2026-09-30T09:15:02.788366747Z
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00

Advisories

https://www.vulncheck.com/advisories/vllm-through-0.29.0-denial-of-service-via-incomplete-nixl-kv-transfer-metadata third-party-advisoryThird Party AdvisoryADVISORYvendor-referenceCVE record · VulnCheck · Updated 2026-09-21T22:04:10.761Z
NVD · CVE-2026-94622 · Updated 2026-09-29T12:47:29.283
PyPA · PYSEC-2026-4004
PyPA · PYSEC-2026-4004 · Updated 2026-09-30T09:15:02.788366747Z
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
https://osv.dev/vulnerability/PYSEC-2026-4004 ADVISORYPyPA · PYSEC-2026-4004
PyPA · PYSEC-2026-4004 · Updated 2026-09-30T09:15:02.788366747Z
https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-94622.json vendor-advisoryRed Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
https://euvd.enisa.europa.eu/vulnerability/EUVD-2026-84216 ADVISORYEUVD · EUVD-2026-84216

Technical & other

https://github.com/vllm-project/vllm/blob/v0.29.0/vllm/distributed/kv_transfer/kv_connector/v1/nixl/metadata.py#L294-L312 technical-descriptionProductWEBvendor-referenceCVE record · VulnCheck · Updated 2026-09-21T22:04:10.761Z
NVD · CVE-2026-94622 · Updated 2026-09-29T12:47:29.283
PyPA · PYSEC-2026-4004
PyPA · PYSEC-2026-4004 · Updated 2026-09-30T09:15:02.788366747Z
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
https://github.com/vllm-project/vllm productProductPACKAGEvendor-referenceCVE record · VulnCheck · Updated 2026-09-21T22:04:10.761Z
NVD · CVE-2026-94622 · Updated 2026-09-29T12:47:29.283
PyPA · PYSEC-2026-4004
PyPA · PYSEC-2026-4004 · Updated 2026-09-30T09:15:02.788366747Z
Red Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
https://access.redhat.com/security/cve/CVE-2026-94622 vendor-referenceRed Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
https://bugzilla.redhat.com/show_bug.cgi?id=2538247 vendor-referenceRed Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
https://www.cve.org/CVERecord?id=CVE-2026-94622 vendor-referenceRed Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
https://nvd.nist.gov/vuln/detail/CVE-2026-94622 vendor-referenceRed Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00
https://access.redhat.com/errata/RHSA-2026:84734 vendor-remediationRed Hat · CVE-2026-94622 · Updated 2026-10-19T11:31:51+00:00

Sources: NVD · CVE.org · EPSS