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archive/Patch now/AIR-2026-0213
closedclosed 26 Sep 2026Patch now2 Disclosed vulnerabilityAI

vLLM Decoder Allocation Resource Limit Bypass Causes GPU Memory Exhaustion

vLLM

vLLM before 0.29.0 contains a resource-limit bypass in PyNvVideoCodec decoder allocation. Attackers can select specific sampler subclasses in video requests to exceed decoder limits and exhaust GPU memory.

disclosed CVENo confirmed exploitation, so this record is tracked as a disclosed vulnerability and not counted as an incident. It moves into the counts if CISA or the vendor confirms exploitation. Why

CVSS
6.3
EPSS
<0.01 · top 72% · 2026-11-13
EPSS scores by FIRST
fix status
Fix status unknown
first report
26 Sep 2026
last update
26 Sep 2026
CVE ids
CVE-2026-100649other records

Timeline · 1

  1. 26 Sep 2026CVE-2026-100649: vLLM before 0.29.0 contains a resource-limit bypass vulnerability in PyNvVideoCodec decoder allocation where sampler subclass…

Sources · 1

Advisories and databases

  1. 2026-09-26
    CVE-2026-100649: vLLM before 0.29.0 contains a resource-limit bypass vulnerability in PyNvVideoCodec decoder allocation where sampler subclass…
    NVD · nvd.nist.gov/vuln/detail/CVE-2026-100649

Titles and links belong to their publishers. The summary above is written by gcdRadar in its own words; data is CC BY-SA 4.0.

Classification

lane
Patch now
AI role
Attack on AI
categories
Infrastructure vulnerability
severity
2 · Disclosed vulnerability
fix status
Fix status unknown
targets
Framework / tooling
owasp llm top 10
LLM03:2025 Supply Chain
mitre atlas
no technique for these categories
tags
resource-exhaustiongpu-memory
dates
happened 26 Sep 2026 · first reported 26 Sep 2026
origin
NVD
Vulnerability record from NVD / the GitHub Advisory Database. This product uses the NVD API but is not endorsed or certified by the NVD.
record
confidence 0.95 · created 2026-10-18 06:33Z · updated 2026-10-18 06:33Z

Lane, AI role, categories and severity come from the classifier; the OWASP and ATLAS rows are derived from the categories. How these are assigned

Copy a brief

This record as a short Markdown brief, for a ticket, a chat or a coding agent.

the brief as text
# vLLM Decoder Allocation Resource Limit Bypass Causes GPU Memory Exhaustion

https://gcdradar.vercel.app/incidents/vllm-decoder-allocation-resource-limit-bypass-causes-gpu-mem · AIR-2026-0213 · closed 2026-09-26

- Lane: Patch now
- Severity: 2 (Disclosed vulnerability)
- Fix status: Fix status unknown
- First reported: 2026-09-26
- AI role: Attack on AI
- Products: vLLM
- CVE ids: CVE-2026-100649
- CVSS: 6.3

## Summary

vLLM before 0.29.0 contains a resource-limit bypass in PyNvVideoCodec decoder allocation. Attackers can select specific sampler subclasses in video requests to exceed decoder limits and exhaust GPU memory.

## What to do

No action recorded; read the sources below and the vendor's advisory.

## Latest updates

- 2026-09-26: CVE-2026-100649: vLLM before 0.29.0 contains a resource-limit bypass vulnerability in PyNvVideoCodec decoder allocation where sampler subclass… (https://nvd.nist.gov/vuln/detail/CVE-2026-100649)

## Sources

- 2026-09-26 NVD: CVE-2026-100649: vLLM before 0.29.0 contains a resource-limit bypass vulnerability in PyNvVideoCodec decoder allocation where sampler subclass… https://nvd.nist.gov/vuln/detail/CVE-2026-100649

Verify against the vendor's advisory before changing production. Data CC BY-SA 4.0, https://gcdradar.vercel.app.

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