CVE-2026-34753
MEDIUM EPSS 15.6%
Published Apr 6, 20262mo ago · Modified Jun 17, 20261w ago
5.4 CVSS 3.1
Published Apr 6, 2026 2mo ago
Last Modified Jun 17, 2026 1w ago
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.
CVSS Details
Base Score
Exploitability
Impact
Vector string
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:L Attack Vector Network
Attack Complexity Low
Privileges Required Low
User Interaction None
Scope Unchanged
Confidentiality Low
Integrity None
Availability Low
Threat Intelligence
EPSS Exploit Probability
15.6% percentile
Exploit & Patch Status
No Known Exploit
Patch Available
Weaknesses 1
CWE-918 Server-Side Request Forgery (SSRF) Validation
Affected Products 1
| Vendor | Product | Version | Range |
|---|---|---|---|
| vllm | vllm | * | ≥0.16.0 – <0.19.0 |
References 1
- github.com https://github.com/vllm-project/vllm/security/advisories/GHSA-pf3h-qjgv-vcpr
Remediation
- github.com https://github.com/vllm-project/vllm/security/advisories/GHSA-pf3h-qjgv-vcpr