PT-2026-53622 · Pypi · Torchserve
Publicado
2026-06-29
·
Atualizado
2026-06-29
CVSS v3.1
9.8
Crítica
| Vetor | AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H |
Impact
Remote Server-Side Request Forgery (SSRF)
Issue: TorchServe default configuration lacks proper input validation, enabling third parties to invoke remote HTTP download requests and write files to the disk. This issue could be taken advantage of to compromise the integrity of the system and sensitive data. This issue is present in versions
0.1.0 to 0.8.1.
Mitigation: The user is able to load the model of their choice from any URL that they would like to use. The user of TorchServe is responsible for configuring both the allowed urls and specifying the model URL to be used. A pull request to warn the user when the default value for allowed urls is used has been merged - https://github.com/pytorch/serve/pull/2534. TorchServe release 0.8.2 includes this change.Patches
TorchServe release 0.8.2 includes fixes to address the previously listed issue:
Tags for upgraded DLC release
User can use the following new image tags to pull DLCs that ship with patched TorchServe version 0.8.2:
x86 GPU
- v1.9-pt-ec2-2.0.1-inf-gpu-py310
- v1.8-pt-sagemaker-2.0.1-inf-gpu-py310
x86 CPU
- v1.8-pt-ec2-2.0.1-inf-cpu-py310
- v1.7-pt-sagemaker-2.0.1-inf-cpu-py310
Graviton
- v1.7-pt-graviton-ec2-2.0.1-inf-cpu-py310
- v1.5-pt-graviton-sagemaker-2.0.1-inf-cpu-py310
Neuron
- 1.13.1-neuron-py310-sdk2.13.2-ubuntu20.04
- 1.13.1-neuronx-py310-sdk2.13.2-ubuntu20.04
- 1.13.1-neuronx-py310-sdk2.13.2-ubuntu20.04
The full DLC image URI details can be found at: https://github.com/aws/deep-learning-containers/blob/master/available images.md#available-deep-learning-containers-images
References
https://github.com/pytorch/serve/blob/b3eced56b4d9d5d3b8597aa506a0bcf954d291bc/docs/configuration.md?plain=1#L296
https://github.com/pytorch/serve/pull/2534
https://github.com/pytorch/serve/releases/tag/v0.8.2
https://github.com/aws/deep-learning-containers/blob/master/available images.md#available-deep-learning-containers-images
Credit
We would like to thank Oligo Security for responsibly disclosing this issue and working with us on its resolution.
If you have any questions or comments about this advisory, we ask that you contact AWS/Amazon Security via our vulnerability reporting page](https://aws.amazon.com/security/vulnerability-reporting)) or directly via email to aws-security@amazon.com. Please do not create a public GitHub issue.
Correção
Encontrou algum problema na descrição? Tem algo a acrescentar? Fique à vontade para nos escrever 👾
Identificadores relacionados
Produtos afetados
Torchserve