CVE-2026-34753: vLLM Server-Side Request Forgery in batch runner

# CVE-2026-34753: vLLM Server-Side Request Forgery in batch runner

https://gcdradar.vercel.app/incidents/cve-2026-34753-vllm-server-side-request-forgery-in-batch-run · AIR-2026-0553 · closed 2026-04-03

- Lane: Patch now
- Severity: 2 (Disclosed vulnerability)
- Fix status: Fix status unknown
- First reported: 2026-04-03
- AI role: Attack on AI
- Products: vLLM
- CVE ids: CVE-2026-34753
- CVSS: 5.4

## Summary

An SSRF flaw in vLLM allows actors controlling batch input JSON to trigger arbitrary HTTP requests from the server. This exposes internal services and cloud metadata endpoints.

## What to do

No action recorded; read the sources below and the vendor's advisory.

## Latest updates

- 2026-04-06: CVE-2026-34753: vLLM is an inference and serving engine for large language models (LLMs). (https://nvd.nist.gov/vuln/detail/CVE-2026-34753)
- 2026-04-03: CVE-2026-34753: vLLM: Server-Side Request Forgery (SSRF) in `download_bytes_from_url ` (https://github.com/advisories/GHSA-pf3h-qjgv-vcpr)

## Sources

- 2026-04-03 GitHub Advisory Database: CVE-2026-34753: vLLM: Server-Side Request Forgery (SSRF) in `download_bytes_from_url ` https://github.com/advisories/GHSA-pf3h-qjgv-vcpr
- 2026-04-06 NVD: CVE-2026-34753: vLLM is an inference and serving engine for large language models (LLMs). https://nvd.nist.gov/vuln/detail/CVE-2026-34753

Verify against the vendor's advisory before changing production. Data CC BY-SA 4.0, https://gcdradar.vercel.app.