ghsa-8fxr-qfr9-p34w
Vulnerability from github
Published
2023-10-02 20:39
Modified
2023-11-01 06:09
Severity ?
Summary
TorchServe Server-Side Request Forgery vulnerability
Details

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 aws-security@amazon.com. Please do not create a public GitHub issue.

Show details on source website


{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "torchserve"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.1.0"
            },
            {
              "fixed": "0.8.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2023-43654"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-918"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2023-10-02T20:39:20Z",
    "nvd_published_at": "2023-09-28T23:15:09Z",
    "severity": "CRITICAL"
  },
  "details": "## Impact\n**Remote Server-Side Request Forgery (SSRF)**\n    **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`.\n    **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](https://github.com/pytorch/serve/blob/b3eced56b4d9d5d3b8597aa506a0bcf954d291bc/docs/configuration.md?plain=1#L296) 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.\n\n## Patches\n\n## TorchServe release 0.8.2 includes fixes to address the previously listed issue:\n\nhttps://github.com/pytorch/serve/releases/tag/v0.8.2\n\n**Tags for upgraded DLC release**\nUser can use the following new image tags to pull DLCs that ship with patched TorchServe version 0.8.2:\nx86 GPU\n\n* v1.9-pt-ec2-2.0.1-inf-gpu-py310\n* v1.8-pt-sagemaker-2.0.1-inf-gpu-py310\n\nx86 CPU\n\n* v1.8-pt-ec2-2.0.1-inf-cpu-py310\n* v1.7-pt-sagemaker-2.0.1-inf-cpu-py310\n\nGraviton\n\n* v1.7-pt-graviton-ec2-2.0.1-inf-cpu-py310\n* v1.5-pt-graviton-sagemaker-2.0.1-inf-cpu-py310\n\nNeuron\n\n* 1.13.1-neuron-py310-sdk2.13.2-ubuntu20.04\n* 1.13.1-neuronx-py310-sdk2.13.2-ubuntu20.04\n* 1.13.1-neuronx-py310-sdk2.13.2-ubuntu20.04\n\nThe 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\n\n## References\nhttps://github.com/pytorch/serve/blob/b3eced56b4d9d5d3b8597aa506a0bcf954d291bc/docs/configuration.md?plain=1#L296\nhttps://github.com/pytorch/serve/pull/2534\nhttps://github.com/pytorch/serve/releases/tag/v0.8.2\nhttps://github.com/aws/deep-learning-containers/blob/master/available_images.md#available-deep-learning-containers-images\n\n## Credit\nWe would like to thank Oligo Security for responsibly disclosing this issue and working with us on its resolution.\nIf 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[)](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.",
  "id": "GHSA-8fxr-qfr9-p34w",
  "modified": "2023-11-01T06:09:57Z",
  "published": "2023-10-02T20:39:20Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/pytorch/serve/security/advisories/GHSA-8fxr-qfr9-p34w"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2023-43654"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pytorch/serve/pull/2534"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/pytorch/serve"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pytorch/serve/releases/tag/v0.8.2"
    },
    {
      "type": "WEB",
      "url": "http://packetstormsecurity.com/files/175095/PyTorch-Model-Server-Registration-Deserialization-Remote-Code-Execution.html"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "TorchServe Server-Side Request Forgery vulnerability"
}


Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading...

Loading...

Loading...

Sightings

Author Source Type Date

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
  • Confirmed: The vulnerability is confirmed from an analyst perspective.
  • Exploited: This vulnerability was exploited and seen by the user reporting the sighting.
  • Patched: This vulnerability was successfully patched by the user reporting the sighting.
  • Not exploited: This vulnerability was not exploited or seen by the user reporting the sighting.
  • Not confirmed: The user expresses doubt about the veracity of the vulnerability.
  • Not patched: This vulnerability was not successfully patched by the user reporting the sighting.