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.
TorchServe release 0.11.0 includes the fix to address this vulnerability.
References
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 or directly via email to [email protected]. Please do not create a public GitHub issue.
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.
TorchServe release 0.11.0 includes the fix to address this vulnerability.
References
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 or directly via email to [email protected]. Please do not create a public GitHub issue.