Описание
vLLM is an inference and serving engine for large language models. In a multi-node vLLM deployment using the V0 engine, vLLM uses ZeroMQ for some multi-node communication purposes. The secondary vLLM hosts open a SUB
ZeroMQ socket and connect to an XPUB
socket on the primary vLLM host. When data is received on this SUB
socket, it is deserialized with pickle
. This is unsafe, as it can be abused to execute code on a remote machine. Since the vulnerability exists in a client that connects to the primary vLLM host, this vulnerability serves as an escalation point. If the primary vLLM host is compromised, this vulnerability could be used to compromise the rest of the hosts in the vLLM deployment. Attackers could also use other means to exploit the vulnerability without requiring access to the primary vLLM host. One example would be the use of ARP cache poisoning to redirect traffic to a malicious endpoint used to deliver a payload with arbitrary code to execute on the target machine. 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 default since v0.8.0 and the fix is fairly invasive, the maintainers of vLLM have decided not to fix this issue. Instead, the maintainers recommend that users ensure their environment is on a secure network in case this pattern is in use. The V1 engine is not affected by this issue.
A flaw was found in vLLM's multi-node configuration, which is vulnerable to remote code execution due to unsafe deserialization using pickle over a ZeroMQ SUB socket. If the primary vLLM host is compromised, attackers can escalate privileges and execute arbitrary code on connected secondary hosts.
Отчет
No Red Hat products are affected by these vulnerabilities. These vulnerabilities are marked as high severity due to their direct impact on security and data confidentiality in multi-node vLLM deployments.The use of unsafe deserialization with pickle over a ZeroMQ SUB socket allows an attacker to execute arbitrary code remotely. If the primary vLLM node is compromised, this flaw can be used to escalate privileges and execute malicious code on secondary hosts, impacting the entire deployment. This lack of input validation and the insecure use of serialization mechanisms significantly increase the exploitability of this issue, leading to its classification as a high severity vulnerability. In RHOAI, vLLM is not included by default in RHOAI deployment as an operator or controller . Hence, RHOAI is not-affected.
Меры по смягчению последствий
Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability.
Затронутые пакеты
Платформа | Пакет | Состояние | Рекомендация | Релиз |
---|---|---|---|---|
Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-amd-rhel9 | Not affected | ||
Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-aws-nvidia-rhel9 | Not affected | ||
Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-azure-amd-rhel9 | Not affected | ||
Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-azure-nvidia-rhel9 | Not affected | ||
Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-gcp-nvidia-rhel9 | Not affected | ||
Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-ibm-nvidia-rhel9 | Not affected | ||
Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-intel-rhel9 | Not affected | ||
Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/bootc-nvidia-rhel9 | Not affected | ||
Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/instructlab-amd-rhel9 | Not affected | ||
Red Hat Enterprise Linux AI (RHEL AI) | rhelai1/instructlab-intel-rhel9 | Not affected |
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Дополнительная информация
Статус:
EPSS
8.8 High
CVSS3
Связанные уязвимости
vLLM is an inference and serving engine for large language models. In a multi-node vLLM deployment using the V0 engine, vLLM uses ZeroMQ for some multi-node communication purposes. The secondary vLLM hosts open a `SUB` ZeroMQ socket and connect to an `XPUB` socket on the primary vLLM host. When data is received on this `SUB` socket, it is deserialized with `pickle`. This is unsafe, as it can be abused to execute code on a remote machine. Since the vulnerability exists in a client that connects to the primary vLLM host, this vulnerability serves as an escalation point. If the primary vLLM host is compromised, this vulnerability could be used to compromise the rest of the hosts in the vLLM deployment. Attackers could also use other means to exploit the vulnerability without requiring access to the primary vLLM host. One example would be the use of ARP cache poisoning to redirect traffic to a malicious endpoint used to deliver a payload with arbitrary code to execute on the target machine
vLLM is an inference and serving engine for large language models. In ...
Remote Code Execution Vulnerability in vLLM Multi-Node Cluster Configuration
EPSS
8.8 High
CVSS3