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Fencer Vulns
high 7.1

CVE-2026-24779 json

vLLM vulnerable to Server-Side Request Forgery (SSRF) in `MediaConnector`

published 2026-01-27 9 mo ago modified 2026-09-10 1 mo ago also EUVD-2026-4711 , GHSA-qh4c-xf7m-gxfc , PYSEC-2026-2020

cvss
7.1
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
0.6%
EPSS 0.6% chance of exploitation in 30 days, percentile 47%
public exploits
0
none known

Summary

vLLM is an inference and serving engine for large language models (LLMs). Prior to version 0.14.1, a Server-Side Request Forgery (SSRF) vulnerability exists in the `MediaConnector` class within the vLLM project's multimodal feature set. The load_from_url and load_from_url_async methods obtain and process media from URLs provided by users, using different Python parsing libraries when restricting the target host. These two parsing libraries have different interpretations of backslashes, which allows the host name restriction to be bypassed. This allows an attacker to coerce the vLLM server into making arbitrary requests to internal network resources. This vulnerability is particularly critical in containerized environments like `llm-d`, where a compromised vLLM pod could be used to scan the internal network, interact with other pods, and potentially cause denial of service or access sensitive data. For example, an attacker could make the vLLM pod send malicious requests to an internal `llm-d` management endpoint, leading to system instability by falsely reporting metrics like the KV cache state. Version 0.14.1 contains a patch for the issue.

Patch / fix

  • pypi vllm 0.14.1
  • Red Hat Red Hat AI Inference Server 3.2 1772160593, 1772160625
  • Red Hat Red Hat AI Inference Server 3.3 1782352847, 1782352919, 1782353093
  • Red Hat Red Hat OpenShift AI 2.25 1772093278, 1776259063, 1783998774, 1783998857
  • Red Hat Red Hat OpenShift AI 3.3 1778264363

Vendor advisories

What the vendors themselves say about their products: affected, fixed or not affected, and what to do.

red hat product security vex CVE-2026-24779 updated cvss 7.1

vLLM: vLLM: Server-Side Request Forgery allows internal network access

  • Red Hat AI Inference Server rhaiis/vllm-tpu-rhel9
    affected: workaround, no fix available
  • Red Hat Enterprise Linux AI (RHEL AI) 3 rhelai3/bootc-cuda-rhel9, rhelai3/bootc-aws-cuda-rhel9, rhelai3/bootc-gcp-cuda-rhel9, rhelai3/bootc-azure-cuda-rhel9
    affected: workaround, no fix planned “Will not fix”
  • Red Hat AI Inference Server 3.2 rhaiis 1772160593, rhaiis 1772160625
    fixed: vendor fix RHSA-2026:3461
  • Red Hat AI Inference Server 3.3 rhaiis/vllm-cuda-rhel9 1782352847, rhaiis/vllm-rocm-rhel9 1782353093, rhaiis/vllm-spyre-rhel9 1782352919
    fixed: vendor fix RHSA-2026:30089
  • Red Hat OpenShift AI 2.25 rhoai 1772093278, rhoai 1776259063, rhoai/odh-vllm-cuda-rhel9 1783998774, rhoai/odh-vllm-rocm-rhel9 1783998857
    fixed: vendor fix RHSA-2026:10184
  • Red Hat OpenShift AI 3.3 rhoai 1778264363
    fixed: vendor fix RHSA-2026:19712
  • Red Hat OpenShift AI (RHOAI) rhoai/odh-kserve-agent-rhel9, rhoai/odh-kserve-router-rhel9, rhoai/odh-kserve-controller-rhel9, rhoai/odh-kserve-storage-initializer-rhel9
    not affected: component not present
  • Red Hat OpenShift AI 2.25 rhoai 1772093237, rhoai 1772093250, rhoai 1772093252, rhoai 1772093260, rhoai 1772093266, rhoai 1772093272, +213 more Red Hat OpenShift AI 3.3 rhoai 1778239104, rhoai 1778262829, rhoai 1778262856, rhoai 1778262893, rhoai 1778262907, rhoai 1778262952, +75 more
    not affected: vulnerable code not present

Red Hat CSAF VEX © Red Hat, Inc., from https://security.access.redhat.com/data/csaf/v2/vex/; changed: reduced to product statuses and remediations. CC BY 4.0 · csaf

CISA SSVC

Exploitation
Proof of concept is public
Automatable
no
Technical impact
partial
Assessed
9 mo ago

Exploit prediction

0.58% chance of exploitation in the next 30 days, higher than 47% of all scored CVEs (FIRST EPSS, 2026-11-08).

Exploits and checks

  • github.com https://github.com/vllm-project/vllm/security/advisories/GHSA-qh4c-xf7m-gxfc referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by version score vector
CNA 3.1 7.1 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:L
CISA ADP 3.1 7.1 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:L
GitHub 3.1 7.1 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:L
OSV 3.1 7.1 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:L

Affected packages

ecosystem package affected fixed in
pypi vllm
<0.14.1
0.14.1

Affected products

  • vllm-project vllm
  • Red Hat Red Hat AI Inference Server 3.2
  • Red Hat Red Hat AI Inference Server 3.3
  • Red Hat Red Hat OpenShift AI 2.25
  • Red Hat Red Hat OpenShift AI 3.3
  • Red Hat Red Hat AI Inference Server
  • Red Hat Red Hat Enterprise Linux AI (RHEL AI) 3
  • Red Hat Red Hat OpenShift AI (RHOAI)

Classification

Weakness
  • CWE-918 Server-Side Request Forgery

References

Sources

Fencer Vulns keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.

CPEs and fixed versions use Anchore's correction of NVD's data: Added CPE configurations because not yet analyzed by NVD.