Описание
A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Affected by this issue is the function torch.mkldnn_max_pool2d. The manipulation leads to denial of service. An attack has to be approached locally. The exploit has been disclosed to the public and may be used. The real existence of this vulnerability is still doubted at the moment. The security policy of the project warns to use unknown models which might establish malicious effects.
A flaw was found in PyTorch. This vulnerability allows denial of service via local exploitation.
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 |
|---|---|---|---|---|
| OpenShift Lightspeed | openshift-lightspeed-tech-preview/lightspeed-service-api-rhel9 | Fix deferred | ||
| 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/docling-serve-rhel9 | Not affected |
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Дополнительная информация
Статус:
3.3 Low
CVSS3
Связанные уязвимости
A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Affected by this issue is the function torch.mkldnn_max_pool2d. The manipulation leads to denial of service. An attack has to be approached locally. The exploit has been disclosed to the public and may be used. The real existence of this vulnerability is still doubted at the moment. The security policy of the project warns to use unknown models which might establish malicious effects.
A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Affected by this issue is the function torch.mkldnn_max_pool2d. The manipulation leads to denial of service. An attack has to be approached locally. The exploit has been disclosed to the public and may be used. The real existence of this vulnerability is still doubted at the moment. The security policy of the project warns to use unknown models which might establish malicious effects.
A vulnerability, which was classified as problematic, has been found i ...
3.3 Low
CVSS3