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CVE-2026-34753

vLLM affected by Server-Side Request Forgery (SSRF) in `download_bytes_from_url `

Published: Apr 6, 2026Updated: Apr 20, 2026 Sources: CVE List NVDCWE-918
5.4MEDIUM
NVD MITRE
EPSS Score
0.2%
Top 84.5%
CISA KEV
Not in KEV
Exploits
No Known Exploits
Remediation
Patch Available

Description

vLLM is an inference and serving engine for large language models (LLMs). From 0.16.0 to before 0.19.0, a server-side request forgery (SSRF) vulnerability in download_bytes_from_url allows any actor who can control batch input JSON to make the vLLM batch runner issue arbitrary HTTP/HTTPS requests from the server, without any URL validation or domain restrictions. This can be used to target internal services (e.g. cloud metadata endpoints or internal HTTP APIs) reachable from the vLLM host. This vulnerability is fixed in 0.19.0.

No summary for this CVE yet.

CVSS Vector Breakdown

AV:NAC:LPR:LUI:NS:UC:LI:NA:L
Exploitability
AV:NAttack Vector
Network
AC:LAttack Complexity
Low
PR:LPrivileges Required
Low
UI:NUser Interaction
None
Scope
S:UScope
Unchanged
Impact
C:LConfidentiality
Low
I:NIntegrity
None
A:LAvailability
Low
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Weaknesses

CWE-918

Affected Products

vllmvllm
Mixed
AI / ML / llm-serving-inference
vllmvllm-project
Mixed
AI / ML / llm-serving-inference
vllmoss-projectAI / MLaka aibrix
vllm-projectoss-projectAI / MLaka vllm, vllm-project/vllm

Exploitability

Official Patch Available

Attack Graph

Products CVE Techniques Tactics

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MITRE ATT&CK

2 techniques
Command and Control
Initial Access
View detailed technique mapping

References

https://github.com/vllm-project/vllm/security/advisories/GHSA-pf3h-qjgv-vcpr
github.com

Timeline

Published
Apr 6, 2026
Last Updated
Apr 20, 2026

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