01 Record
CVE-2026-69147
vLLM: Request-selected PyNvVideoCodec GPU decode bypasses static VRAM reservation
MediumPUBLISHEDCNA: GitHub_M
CNA base score6.5 CVSS v3.xCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
02 Description
vLLM: Request-selected PyNvVideoCodec GPU decode bypasses static VRAM reservation
03 Exploitation and scoring
- Exploitation
- Public exploit code exists. CISA's assessment records a public proof of concept. That is not a report of exploitation in the wild.
- SSVC decision
- ExploitationpocPublic proof-of-concept exploit code exists. Not a report of exploitation in the wild.
- AutomatablenoAt least one step from reconnaissance to exploitation cannot be reliably automated.
- Technical ImpactpartialSuccessful exploitation gives limited control of the vulnerable component.
- EPSS probability
- 0.58% probability of exploitation activity in the next 30 days.
- EPSS percentile
- Equal to or higher than the score of 47.5% of scored records. A rank, not a probability.
- NVD base score
- 6.5 (CVSS v3.x), scored by the NVD independently of the CNA.
- NVD CVSS vector
- CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- NVD analysis status
- Analyzed. NVD last modified this record on 2026-10-07.
- Red Hat severity
- Moderate. Red Hat's rating for its own products, not a CVSS rating.
Exploit-prediction scores from FIRST. Independent scoring and analysis status from the NVD. Vendor severity from Red Hat. Exploitation assessment and catalog membership from CISA.
04 Metadata
- Published
- 2026-09-16 17:49Z1 MO AGO
- Last updated
- 2026-09-16 18:37Z1 MO AGO
- Reserved
- 2026-08-03
- Assigning CNA
- GitHub_M
- Record state
- PUBLISHED
- Severity
- Medium (CVSS 6.5)
- CNA CVSS vector
- CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- Weaknesses
- Data version
- 5.2
- Document digest
- cc19006755bbfe35d4c247bb48f0f7644e3a395747fc4a5013990d1d645899a9
05 Affected products
VendorProductVersionsPlatforms
06 References
- github.comhttps://github.com/vllm-project/vllm/security/advisories/GHSA-8pw2-6jv3-mj5j
- github.comhttps://github.com/vllm-project/vllm/pull/47259
- github.comhttps://github.com/vllm-project/vllm/commit/283893c72292ede38d277e3cd2b9b64c3e4f1dda
- github.comhttps://github.com/vllm-project/vllm/commit/ba22152096b2484faa3579624a253d54804d876d