CVE-2024-35199

TorchServe is a flexible and easy-to-use tool for serving and scaling PyTorch models in production. In affected versions the two gRPC ports 7070 and 7071, are not bound to [localhost](http://localhost/) by default, so when TorchServe is launched, these two interfaces are bound to all interfaces. Customers using PyTorch inference Deep Learning Containers (DLC) through Amazon SageMaker and EKS are not affected. This issue in TorchServe has been fixed in PR #3083. TorchServe release 0.11.0 includes the fix to address this vulnerability. Users are advised to upgrade. There are no known workarounds for this vulnerability.

TorchServe is a flexible and easy-to-use tool for serving and scaling PyTorch models in production. In affected versions the two gRPC ports 7070 and 7071, are not bound to [localhost](http://localhost/) by default, so when TorchServe is launched, these two interfaces are bound to all interfaces. Customers using PyTorch inference Deep Learning Containers (DLC) through Amazon SageMaker and EKS are not affected. This issue in TorchServe has been fixed in PR #3083. TorchServe release 0.11.0 includes the fix to address this vulnerability. Users are advised to upgrade. There are no known workarounds for this vulnerability.

### Impact The two gRPC ports 7070 and 7071, are not bound to [localhost](http://localhost/) by default, so when TorchServe is launched, these two interfaces are bound to all interfaces. Customers using PyTorch inference Deep Learning Containers (DLC) through Amazon SageMaker and EKS are not affected. ### Patches This issue in TorchServe has been fixed in [#3083](https://github.com/pytorch/serve/pull/3083). TorchServe release 0.11.0 includes the fix to address this vulnerability. ### References * [#3083](https://github.com/pytorch/serve/pull/3083) * [TorchServe release v0.11.0](https://github.com/pytorch/serve/releases/tag/v0.11.0) Thank Kroll Cyber Risk for for responsibly disclosing this issue. If you have any questions or comments about this advisory, we ask that you contact AWS Security via our [vulnerability reporting page](https://aws.amazon.com/security/vulnerability-reporting) or directly via email to [aws-security@amazon.com](mailto:aws-security@amazon.com). Please do not create a public GitHub issue.

### Impact The two gRPC ports 7070 and 7071, are not bound to [localhost](http://localhost/) by default, so when TorchServe is launched, these two interfaces are bound to all interfaces. Customers using PyTorch inference Deep Learning Containers (DLC) through Amazon SageMaker and EKS are not affected. ### Patches This issue in TorchServe has been fixed in [#3083](https://github.com/pytorch/serve/pull/3083). TorchServe release 0.11.0 includes the fix to address this vulnerability. ### References * [#3083](https://github.com/pytorch/serve/pull/3083) * [TorchServe release v0.11.0](https://github.com/pytorch/serve/releases/tag/v0.11.0) Thank Kroll Cyber Risk for for responsibly disclosing this issue. If you have any questions or comments about this advisory, we ask that you contact AWS Security via our [vulnerability reporting page](https://aws.amazon.com/security/vulnerability-reporting) or directly via email to [aws-security@amazon.com](mailto:aws-security@amazon.com). Please do not create a public GitHub issue.

TorchServe es una herramienta flexible y fácil de usar para servir y escalar modelos PyTorch en producción. En las versiones afectadas, los dos puertos gRPC 7070 y 7071 no están vinculados a [localhost](http://localhost/) de forma predeterminada, por lo que cuando se inicia TorchServe, estas dos interfaces están vinculadas a todas las interfaces. Los clientes que utilizan contenedores de aprendizaje profundo (DLC) de inferencia de PyTorch a través de Amazon SageMaker y EKS no se ven afectados. Este problema en TorchServe se solucionó en PR #3083. La versión 0.11.0 de TorchServe incluye la solución para abordar esta vulnerabilidad. Se recomienda a los usuarios que actualicen. No se conocen workarounds para esta vulnerabilidad.