GitHub Advisoryadvisory · PyPI

GHSA-8fxr-qfr9-p34w TorchServe Server-Side Request Forgery vulnerability

CRITICAL Published 2023-10-02 Modified 2023-11-01 Official page ↗
Aliases
CVE-2023-43654
Ecosystem
PyPI
Packages
torchserve
Severity
Critical
CVSS vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
Weaknesses
CWE-918
Reviewed
2023-10-02

Affected packages

• PyPI torchserve: >= 0.1.0, < 0.8.2 → fixed in 0.8.2

Description

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: https://github.com/pytorch/serve/releases/tag/v0.8.2 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 [email protected]. Please do not create a public GitHub issue.

Related

Alias · CVE (1)

  • CVE-2023-43654 TorchServe is a tool for serving and scaling PyTorch models in production. vulnerability

Weakness · CWE (1)

  • CWE-918 Server-Side Request Forgery weakness

References