vLLM: Request-selected PyNvVideoCodec GPU decode bypasses static VRAM reservation
Key facts
- Attack vector
- Network
- Privileges required
- Low
- User interaction
- None
- Attack complexity
- Low
- Impact type
- Denial of service
- Confidentiality · integrity · availability
- None · None · High
- Fix status
- Partial Red Hat: 2 fixed, 3 without a fix
Attack profile from CVSS 3.1 · CNA. Fix status from CNA, GitHub and Red Hat. Impact type from CWE-400.
Summary
vLLM is an inference and serving engine for large language models. Prior to 0.28.0, request bodies for Chat Completions and Responses can set media_io_kwargs.video.video_backend to pynvvideocodec, and MediaConnector.fetch_video forwards that choice to VideoMediaIO even when startup configuration selected a software decoder. The engine's _reserve_mm_ipc_gpu_memory logic budgets decoder memory only from static configuration, so the request-selected VIDEO_LOADER_REGISTRY backend can create a CUDA context, decoder surfaces, and decoded-frame allocations that were not removed from the engine's KV-cache budget. An attacker able to submit video requests to a video-capable GPU deployment with PyNvVideoCodec installed can exhaust shared GPU memory, causing request failures, worker crashes, or denial of service. The first release containing the fix is version 0.28.0.
Why it matters now
SSVC decision points
CISA ADP · SSVC 2.0.3
- Exploitation
- Poc
- Automatable
- No
- Technical impact
- Partial
The decision (Track, Attend, Act) also depends on your mission and well-being impact; see CISA's SSVC guide.
Affected products
| Vendor | Product | Affected versions | Fixed in | Status | Source |
|---|---|---|---|---|---|
| vllm-project | vllm | before 0.28.0 | 0.28.0 | Patch available | CNA |
| — | vllm (PyPI) | before 0.28.0 | 0.28.0 | Patch available | GHSA-8pw2-6jv3-mj5j |
- vllm Vendorvllm-project Affected before 0.28.0 Fixed in 0.28.0 Patch available CNA
- vllm (PyPI) Vendor— Affected before 0.28.0 Fixed in 0.28.0 Patch available GHSA-8pw2-6jv3-mj5j
Remediation
- Fix · CNA vllm (vllm-project) Fixed in 0.28.0
- Fix · GHSA-8pw2-6jv3-mj5j vllm (PyPI) Fixed in 0.28.0 Advisory →
Red Hat 7 advisories
- RHSA-2026:92452 Released 2026-10-29 · Red Hat rating CriticalRed Hat Enterprise Linux AI 3.5.2 enhancement update
- Red Hat Enterprise Linux AI 3.5 registry.redhat.io/rhelai3/bootc-aws-cuda-rhel9, registry.redhat.io/rhelai3/bootc-azure-cuda-rhel9, registry.redhat.io/rhelai3/bootc-azure-rocm-rhel9 +3
- RHSA-2026:92449 Released 2026-10-29 · Red Hat rating CriticalRed Hat Enterprise Linux AI 3.5.2 enhancement update
- Red Hat Enterprise Linux AI 3.5 registry.redhat.io/rhelai3/disk-image-cuda-rhel9
- RHSA-2026:82415 Released 2026-10-13 · Red Hat rating CriticalRed Hat AI Inference 3.5.2 (cpu)
- Red Hat AI Inference Server 3.5 registry.redhat.io/rhaii/vllm-cpu-rhel9
Show 4 more Red Hat advisories
- RHSA-2026:82371 Released 2026-10-13 · Red Hat rating CriticalRed Hat AI Inference 3.5.2 (spyre)
- Red Hat AI Inference Server 3.5 registry.redhat.io/rhaii/vllm-spyre-rhel9
- RHSA-2026:82368 Released 2026-10-13 · Red Hat rating CriticalRed Hat AI Inference 3.5.2 (cuda)
- Red Hat AI Inference Server 3.5 registry.redhat.io/rhaii/vllm-cuda-rhel9
- RHSA-2026:82061 Released 2026-10-13 · Red Hat rating CriticalRed Hat AI Inference Tech Preview 3.5.2 (Gaudi)
- Red Hat AI Inference Server 3.5 registry.redhat.io/rhaii/vllm-gaudi-rhel9
- RHSA-2026:82059 Released 2026-10-13 · Red Hat rating CriticalRed Hat AI Inference 3.5.2 (ROCm)
- Red Hat AI Inference Server 3.5 registry.redhat.io/rhaii/vllm-rocm-rhel9
Vendor assessments
Red Hat
Red Hat rating: Moderate. Red Hat's page for this CVE →
| Product | Status | Plan or fix |
|---|---|---|
| Red Hat AI Inference Server | Affected | No fix yet: Fix deferred |
| Red Hat Enterprise Linux AI (RHEL AI) 3 | Affected | No fix yet: Fix deferred |
| Red Hat OpenShift AI (RHOAI) | Affected | No fix yet: Fix deferred |
| Red Hat AI Inference Server 3.5 | Fixed | RHSA-2026:82059, RHSA-2026:82061, RHSA-2026:82368, RHSA-2026:82371, RHSA-2026:82415 |
| Red Hat Enterprise Linux AI 3.5 | Fixed | RHSA-2026:92449, RHSA-2026:92452 |
Timeline
- 2026-10-02 Threatist record created from CVE-2026-69147
- 2026-10-03 Alias added: GHSA-8pw2-6jv3-mj5j
- 2026-10-13 Fix available: RHSA-2026:82061 · Red Hat
- 2026-10-13 Fix available: RHSA-2026:82059 · Red Hat
- 2026-10-13 Fix available: Red Hat AI Inference Server 3.5 · Red Hat
- 2026-10-14 Fix available: RHSA-2026:82368 · Red Hat
- 2026-10-14 Fix available: RHSA-2026:82415 · Red Hat
- 2026-10-14 Fix available: RHSA-2026:82371 · Red Hat
- 2026-10-15 Affected versions changed · Red Hat
- 2026-10-30 Fix available: RHSA-2026:92452 · Red Hat
- 2026-10-30 Fix available: RHSA-2026:92449 · Red Hat
- 2026-10-30 Fix available: Red Hat Enterprise Linux AI 3.5 · Red Hat
References
Patch 3
More vllm-project vulnerabilities
- TI-2024-10229 Remote Code Execution in vllm-project/vllm CVSS 3.0CRITICAL 9.8
- TI-2024-08404 Remote Code Execution in vllm-project/vllm CVSS 3.1CRITICAL 9.8
- TI-2026-36017 vLLM: OpenAI auth bypass CVSS 3.1CRITICAL 9.1
- TI-2026-63056 vLLM before 0.28.0 Denial of Service via negative token ID CVSS 4.0HIGH 8.7
- TI-2026-04308 Hardcoded trust_remote_code=True in vllm-project/vllm Bypasses User Security Control CVSS 3.0HIGH 8.8
- TI-2026-39137 vLLM: Remote DoS in vLLM via Invalid Recovered Token Reinjection CVSS 3.1HIGH 7.5
Sources
- CVE-2026-69147 · CVE Program
- CVE-2026-69147 · NVD
- FIRST EPSS
- GHSA-8pw2-6jv3-mj5j · GitHub Advisory Database · CC BY 4.0
- CVE-2026-69147 · Red Hat security data · CC BY 4.0
This product uses the NVD API but is not endorsed or certified by the NVD. Sources and licences