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Review reviewHigh

CVE-2026-5497

vllm-project vllm-project/vllm, Red Hat AI Inference Server, Red Hat Enterprise Linux AI (RHEL AI) 3

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...

CVSS
7.5
EPSS
0.54%
42.4% percentile
CISA KEV
Not listed
Published
2026.06.11
PRIORITY ASSESSMENT

Review review

The CVSS severity warrants an early asset and exposure review.

Known exploitationNot established by KEV
Exploit probability0.54%
Technical severityCVSS 7.5

Vulnerability overview

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...

Affected product and versions

Product
vllm-project vllm-project/vllm, Red Hat AI Inference Server, Red Hat Enterprise Linux AI (RHEL AI) 3
Affected versions
>= unspecified < 0.19.0, >= 0.8.0 < 0.19.0
Fixed versions
0.19.0

Recommended response sequence

Confirm exposure before applying a vendor-supported change.

Full remediation guide
  1. 1
    Identify

    Confirm that vllm-project vllm-project/vllm, Red Hat AI Inference Server, Red Hat Enterprise Linux AI (RHEL AI) 3 and an affected version are present.

  2. 2
    Prioritize

    Combine exploitation signals with asset exposure and business criticality.

  3. 3
    Remediate

    Follow the vendor advisory or supported update path and preserve rollback options.

  4. 4
    Verify

    Recheck the version, service health, access paths, and relevant logs.

Technical data

CVSS vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
CWE
CWE-400, CWE-770
CVE-2026-5497 — vllm-project vllm-project/vllm, Red Hat AI Inference Server, Red Hat Enterprise Linux AI (RHEL AI) 3 | SECUFOCUS NOW