CVE-2026-115913: vllm · Unthrottled Resource Allocation
Affects vllmSource CVE Database V5
Not known to be exploited · CVSS 6.5 Medium : upgrade to 0.32.0 when convenient.
Data as of 26 Oct 2026, 17:30 UTC
- Patch
- Available – fixed in 0.32.0
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:HExploitation evidence
Disclosed: evidence found.
CVE published 26 Oct 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors
A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.
What to do
Upgrade vllm to 0.32.0.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| vllm-projectvllm | Affected
| Fixed in
|
PyPIvllmpkg:pypi/vllmOther threats | Affected
| Fixed in
|
Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.
AI-suggested
Upgrade vLLM to version 0.32.0 or later, where the issue is fixed. No other mitigation is required as the vulnerability is addressed by this official fix.
Description
vLLM versions prior to 0.32.0 contain a resource allocation vulnerability in the Phi-4 multimodal audio encoder. The default use of eager attention causes large attention matrices to be fully materialized in GPU memory when processing long audio clips, leading to quadratic memory consumption. This can result in out-of-memory conditions that terminate the EngineCore process, affecting all users. The issue is resolved in version 0.32.0.
References
- github.com/vllm-project/vllm/security/advisories/GHSA-8397-8qf6-f2gm (opens in a new tab)
- github.com/vllm-project/vllm/pull/60614 (opens in a new tab)
- github.com/vllm-project/vllm/commit/3d52578e13454de0bb8352cac988347cdcc89928 (opens in a new tab)
- github.com/vllm-project/vllm/releases/tag/v0.32.0 (opens in a new tab)