High severity · published Jun 11, 2026
CVE-2026-5497
Unbounded Frame Count in video/jpeg Base64 Data URL Processing Leads to OOM DoS in vllm-project/vllm
7.5
CVSS
0.5%
EPSS
No
On KEV
Description
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.
CVSS vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Attack vector
Network
Complexity
Low
Privileges
None
User interaction
None
Confidentiality
None
Integrity
None
Availability
High
Scope
Unchanged
Exploitation
Is it being used?
Exploit prediction (EPSS)0.5% · higher than 45% of CVEs
Exploited in the wildNo evidence yet
CISA KEVNot listed
Ransomware campaign useNot known
Affected products
Which versions
VL
vllm-project/vllm · vllm-project
before 0.19.0 · source: vendor
VL
Vllm · Vllm
0.8.0 before 0.19.0 · source: NVD
RH
Red Hat AI Inference Server · Red Hat
All versions, or not specified · source: CISA
RH
Red Hat Enterprise Linux AI (RHEL AI) 3 · Red Hat
All versions, or not specified · source: CISA
RH
Red Hat OpenShift AI (RHOAI) · Red Hat
All versions, or not specified · source: CISA