GHSA-9PCC-GVX5-R5WM Remote Code Execution Vulnerability in vLLM Multi-Node Cluster Configuration

Affected Environments Note that this issue only affects the V0 engine, which has been off by default since v0.8.0. Further, the issue only applies to a deployment using tensor parallelism across multiple hosts, which we do not expect to be a common deployment pattern. Since V0 is has been off by...

Deserialization of Untrusted Data

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Deserialization of Untrusted Data via the SUB ZeroMQ socket, where the deserialization is performed using the unsafe pickle library. An attacker on...

Remote Code Execution Vulnerability in vLLM Multi-Node Cluster Configuration

Affected Environments Note that this issue only affects the V0 engine, which has been off by default since v0.8.0. Further, the issue only applies to a deployment using tensor parallelism across multiple hosts, which we do not expect to be a common deployment pattern. Since V0 is has been off by...

PT-2025-19899

Name of the Vulnerable Software and Affected Versions vllm versions 0.5.2 through 0.8.5.post1 Description The issue exists in the V0 engine of vLLM, which uses ZeroMQ for multi-node communication. When data is received on the SUB ZeroMQ socket, it is deserialized with pickle, allowing for potenti...

vLLM 代码问题漏洞

vLLM is a vLLM open source high throughput and memory efficient inference and service engine for LLM. A code issue vulnerability exists in vLLM that stems from insecure deserialization and could lead to remote code execution...

CVE-2025-32444 vulnerabilities

Vulnerabilities for packages: py3.10-vllm-cuda-12.6...

CVE-2025-46560 vulnerabilities

Vulnerabilities for packages: py3.10-vllm-cuda-11.8...

GHSA-VC6M-HM49-G9QG vulnerabilities

Vulnerabilities for packages: py3.10-vllm-cuda-11.8...

GHSA-HJ4W-HM2G-P6W5 vulnerabilities

Vulnerabilities for packages: py3.10-vllm-cuda-12.6...

CVE-2025-30202 vulnerabilities

Vulnerabilities for packages: py3.10-vllm-cuda-11.8...

CVE-2025-30202

A flaw was found in vLLM's multi-node setup, which exposes sensitive data over a ZeroMQ XPUB socket bound to all interfaces. This vulnerability allows unauthorized clients to intercept and read internal communications if they can access the network. Mitigation Mitigation for this issue is either...

PYSEC-2025-42

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.6.5 and prior to 0.8.5, having vLLM integration with mooncake, are vulnerable to remote code execution due to using pickle based serialization over unsecured ZeroMQ sockets. The vulnerab...

CVE-2025-32444

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.6.5 and prior to 0.8.5, having vLLM integration with mooncake, are vulnerable to remote code execution due to using pickle based serialization over unsecured ZeroMQ sockets. The vulnerab...

CVE-2025-30202

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.5.2 and prior to 0.8.5 are vulnerable to denial of service and data exposure via ZeroMQ on multi-node vLLM deployment. In a multi-node vLLM deployment, vLLM uses ZeroMQ for some multi-no...

Deserialization of Untrusted Data

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Deserialization of Untrusted Data in the Mooncake integration. An attacker can execute arbitrary code by sending malicious payloads to a pickle base...

CVE-2025-32444

vLLM (0.6.5–0.8.4) with mooncake integration is vulnerable to remote code execution due to pickle-based serialization over unsecured ZeroMQ sockets that were listening on all interfaces. This could be exploited remotely; non-mooncake deployments are not affected. The issue is fixed in vLLM 0.8.5....

CVE-2025-32444 vLLM Vulnerable to Remote Code Execution via Mooncake Integration

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.6.5 and prior to 0.8.5, having vLLM integration with mooncake, are vulnerable to remote code execution due to using pickle based serialization over unsecured ZeroMQ sockets. The vulnerab...

CVE-2025-46560 vLLM phi4mm: Quadratic Time Complexity in Input Token Processing​ leads to denial of service

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.8.0 and prior to 0.8.5 are affected by a critical performance vulnerability in the input preprocessing logic of the multimodal tokenizer. The code dynamically replaces placeholder tokens...

Inefficient Algorithmic Complexity

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Inefficient Algorithmic Complexity through the inputprocessorforphi4mm function. An attacker can cause the application to consume excessive resource...

CVE-2025-46560 vLLM phi4mm: Quadratic Time Complexity in Input Token Processing​ leads to denial of service

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.8.0 and prior to 0.8.5 are affected by a critical performance vulnerability in the input preprocessing logic of the multimodal tokenizer. The code dynamically replaces placeholder tokens...