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Fencer Vulns
high 7.5

CVE-2026-5497 json

Unbounded Frame Count in video/jpeg Base64 Data URL Processing Leads to OOM DoS in vllm-project/vllm

published 2026-06-11 4 mo ago modified 2026-10-26 14 d ago also GHSA-wcwg-c5fc-9vrc , PYSEC-2026-2302 , EUVD-2026-36217

cvss
7.5
version 3.0, CNA
cisa kev
Not listed
not in CISA's catalog
epss
0.5%
EPSS 0.5% chance of exploitation in 30 days, percentile 45%
public exploits
0
none known

Summary

vLLM versions 0.8.0 and later are vulnerable to an Out-of-Memory (OOM) Denial of Service (DoS) attack due to unbounded frame count processing in the `VideoMediaIO.load_base64()` method. When processing `video/jpeg` data URLs, the method splits the base64 data string on commas to extract individual JPEG frames without enforcing a frame count limit. An attacker can exploit this by crafting a single API request containing thousands of comma-separated base64-encoded JPEG frames in a data URL, causing the server to decode all frames into memory and crash due to excessive memory consumption. This vulnerability is reachable via the OpenAI-compatible chat completions API and does not require authentication.

Patch / fix

  • pypi vllm 0.19.0
  • vllm-project vllm-project/vllm 0.19.0

Vendor advisories

What the vendors themselves say about their products: affected, fixed or not affected, and what to do.

red hat product security vex CVE-2026-5497 updated cvss 7.5

vllm: vLLM: Denial of Service via unbounded video frame processing

  • Red Hat AI Inference Server rhaii/vllm-tpu-rhel9, rhaiis/vllm-cpu-rhel9, rhaiis/vllm-tpu-rhel9, rhaii/vllm-gaudi-rhel9, rhaiis/vllm-cuda-rhel9, rhaiis/vllm-rocm-rhel9, +3 more
    affected: workaround, no fix available, no fix planned “Will not fix”
  • Red Hat Enterprise Linux AI (RHEL AI) 3 rhelai3/bootc-gaudi-rhel9
    affected: workaround, no fix planned “Will not fix”
  • Red Hat OpenShift AI (RHOAI) rhoai/odh-vllm-gaudi-rhel9
    affected: workaround, no fix available
  • Red Hat AI Inference Server 3.4 rhaii/vllm-cpu-rhel9 1789681128, rhaii/vllm-cpu-rhel9 1790075793, rhaii/vllm-cuda-rhel9 1789681126, rhaii/vllm-cuda-rhel9 1790090131, rhaii/vllm-rocm-rhel9 1789681126, rhaii/vllm-rocm-rhel9 1790109620, +2 more
    fixed: vendor fix RHSA-2026:69466
  • Red Hat Enterprise Linux AI 3.4 rhelai3/bootc-cuda-rhel9 1790868254, rhelai3/bootc-rocm-rhel9 1790614447, rhelai3/bootc-aws-cuda-rhel9 1790881122, rhelai3/bootc-gcp-cuda-rhel9 1790881123, rhelai3/disk-image-cuda-rhel9 1790957417, rhelai3/bootc-azure-cuda-rhel9 1790881120, +1 more
    fixed: vendor fix RHSA-2026:76150
  • Red Hat OpenShift AI 2.25 rhoai/odh-vllm-cuda-rhel9 1791358976, rhoai/odh-vllm-rocm-rhel9 1791282503
    fixed: vendor fix RHSA-2026:87410
  • Red Hat OpenShift AI (RHOAI) rhoai/odh-kserve-agent-rhel9, rhoai/odh-kserve-router-rhel9, rhoai/odh-llm-d-kv-cache-rhel9, rhoai/odh-kserve-controller-rhel9, rhoai/odh-kserve-storage-initializer-rhel9 Red Hat OpenShift AI 2.25 rhoai/odh-rhel9-operator 1792570619, rhoai/odh-vllm-cpu-rhel9 1792018436, rhoai/odh-dashboard-rhel9 1791853525, rhoai/odh-modelmesh-rhel9 1790881700, rhoai/odh-operator-bundle 1792571069, rhoai/odh-caikit-nlp-rhel9 1791448212, +64 more
    not affected: vulnerable code not present

Red Hat CSAF VEX © Red Hat, Inc., from https://security.access.redhat.com/data/csaf/v2/vex/; changed: reduced to product statuses and remediations. CC BY 4.0 · csaf

CISA SSVC

Exploitation
Proof of concept is public
Automatable
yes
Technical impact
partial
Assessed
4 mo ago

Exploit prediction

0.54% chance of exploitation in the next 30 days, higher than 45% of all scored CVEs (FIRST EPSS, 2026-11-08).

Exploits and checks

  • huntr.com https://huntr.com/bounties/7bd92629-b396-4449-8f88-6c0092530eb4 referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by version score vector
CNA 3.0 7.5 CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
CISA ADP 3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
CNA 3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
OSV 3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
GitHub 3.0 7.5 CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Affected packages

ecosystem package affected fixed in
pypi vllm
>=0.8.0, <0.19.0
0.19.0

Affected products

  • vllm-project vllm-project/vllm
  • Red Hat Red Hat AI Inference Server
  • Red Hat Red Hat Enterprise Linux AI (RHEL AI) 3
  • Red Hat Red Hat OpenShift AI (RHOAI)

Classification

Weakness
  • CWE-400 Uncontrolled Resource Consumption
  • CWE-770 Allocation of Resources Without Limits or Throttling

References

Sources

Fencer Vulns keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.