High severity · published Aug 21, 2025
CVE-2025-48956
vLLM is an inference and serving engine for large language models (LLMs)
7.5
CVSS
0.6%
EPSS
No
On KEV
Description
vLLM is an inference and serving engine for large language models (LLMs). From 0.1.0 to before 0.10.1.1, a Denial of Service (DoS) vulnerability can be triggered by sending a single HTTP GET request with an extremely large header to an HTTP endpoint. This results in server memory exhaustion, potentially leading to a crash or unresponsiveness. The attack does not require authentication, making it exploitable by any remote user. This vulnerability is fixed in 0.10.1.1.
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)0.6% · higher than 47% of CVEs
Exploited in the wildNo evidence yet
CISA KEVNot listed
Ransomware campaign useNot known
Affected products
Which versions
VL
Vllm · Vllm
0.1.0 before 0.10.1.1 · source: NVD
References
NVD
https://nvd.nist.gov/vuln/detail/CVE-2025-48956
CVE.org
https://www.cve.org/CVERecord?id=CVE-2025-48956
Patch
https://github.com/vllm-project/vllm/commit/d8b736f913a59117803d6701521d2e4861701944
Issue Tracking
https://github.com/vllm-project/vllm/pull/23267
Vendor Advisory
https://github.com/vllm-project/vllm/security/advisories/GHSA-rxc4-3w6r-4v47
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