Advisory Weakness Curation

TorchServe vulnerable to bypass of allowed_urls configuration ### Impact TorchServe's check on allowed_urls configuration can be by-passed if the URL contains characters such as ".." but it does not prevent the model from being downloaded into the model store. Once a file is downloaded, it can be referenced without providing a URL the second time, which effectively bypasses the allowed_urls security check. Customers using PyTorch inference Deep Learning Containers (DLC) through Amazon SageMaker and EKS are not affected. ### Patches This issue in TorchServe has been fixed by validating the URL without characters such as ".." before downloading: #3082 https://github.com/pytorch/serve/pull/3082. TorchServe release 0.11.0 includes the fix to address this vulnerability. ### References * #3082 https://github.com/pytorch/serve/pull/3082 * 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 vulnerable to bypass of allowed_urls configuration TorchServe's check on allowed_urls configuration can be by-passed if the URL contains characters such as ".." but it does not prevent the model from being downloaded into the model store. Once a file is downloaded, it can be referenced without providing a URL the second time, which effectively bypasses the allowed_urls security check. Customers using PyTorch inference Deep Learning Containers (DLC) through Amazon SageMaker and EKS are not affected.