Deserialization of Untrusted Data Affecting py3.10-vllm-cuda-12.6 package, versions <0.8.5-r1
Threat Intelligence
The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
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Start learning- Snyk IDSNYK-CHAINGUARDLATEST-PY310VLLMCUDA126-10004395
- published2 May 2025
- disclosed30 Apr 2025
Introduced: 30 Apr 2025
NewCVE-2025-32444 (opens in a new tab)How to fix?
Upgrade Chainguard py3.10-vllm-cuda-12.6 to version 0.8.5-r1 or higher.
NVD Description
Note: Versions mentioned in the description apply only to the upstream py3.10-vllm-cuda-12.6 package and not the py3.10-vllm-cuda-12.6 package as distributed by Chainguard.
See How to fix? for Chainguard relevant fixed versions and status.
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 vulnerable sockets were set to listen on all network interfaces, increasing the likelihood that an attacker is able to reach the vulnerable ZeroMQ sockets to carry out an attack. vLLM instances that do not make use of the mooncake integration are not vulnerable. This issue has been patched in version 0.8.5.
References
- https://github.com/vllm-project/vllm/blob/32b14baf8a1f7195ca09484de3008063569b43c5/vllm/distributed/kv_transfer/kv_pipe/mooncake_pipe.py#L179
- https://github.com/vllm-project/vllm/commit/a5450f11c95847cf51a17207af9a3ca5ab569b2c
- https://github.com/vllm-project/vllm/security/advisories/GHSA-hj4w-hm2g-p6w5
- https://github.com/vllm-project/vllm/security/advisories/GHSA-x3m8-f7g5-qhm7