CVE-2023-43654: Torchserve TorchServe Server-Side Request Forgery Vulnerability Vulnerability

CRITICAL
Advisory Identifier: GHSA-8fxr-qfr9-p34w
CVSS 9.8
CWE-918
Published
Advisory Summary

CVE-2023-43654 is a CRITICAL (CVSS 9.8) torchserve server-side request forgery vulnerability vulnerability (CWE-918: Server-Side Request Forgery (SSRF)) affecting Torchserve libraries in the PyPI ecosystem. The issue involves torchserve server-side request forgery vulnerability. Remediation is available by upgrading affected packages to version 0.8.2.

CVE-2023-43654 at a Glance

CVE Identifier CVE-2023-43654
GHSA Identifier GHSA-8fxr-qfr9-p34w
Severity CRITICAL
CVSS v3.1 Base Score 9.8
CWE Classification CWE-918: Server-Side Request Forgery (SSRF)
Affected Product Torchserve
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 9.8

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required None (PR:N)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality High (C:H)
Integrity High (I:H)
Availability High (A:H)

How to Fix CVE-2023-43654

To remediate this vulnerability, upgrade all affected Torchserve dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

torchserve fixed: 0.8.2
pip install torchserve>=0.8.2
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release:

pip show torchserve

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2023-43654, inspect your installed packages using pip:

pip show torchserve

Analyze the terminal output to locate any version of Torchserve in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 0.8.2), your application is affected.

Note: The pip show torchserve command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-918: Server-Side Request Forgery (SSRF), where the web server receives a url or similar request from an upstream component and retrieves the contents of this url, but it does not sufficiently ensure that the request is being sent to the expected destination. In Torchserve, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

## 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](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. ## 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[)](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.

CVE-2023-43654 Affected Torchserve Versions

1 component(s)
Fixed Versions:
0.8.2
Product / Package Ecosystem Affected Versions Fixed Version
torchserve
PyPI
≥ 0.1.0
< 0.8.2
0.8.2

References

Frequently Asked Questions

What is CVE-2023-43654?
CVE-2023-43654 is a security vulnerability in Torchserve involving TorchServe Server-Side Request Forgery vulnerability under CWE-918: Server-Side Request Forgery (SSRF).
Which Torchserve versions are affected?
Affected versions include releases prior to 0.8.2 across affected packages: torchserve.
What version fixes CVE-2023-43654?
Upgrading to 0.8.2 (or the latest patched release for your respective branch) resolves the vulnerability.
Is torchserve affected?
Yes, torchserve is affected in releases prior to 0.8.2. Upgrade your dependency to 0.8.2 or later.
What is the CVSS score of CVE-2023-43654?
CVE-2023-43654 has a CVSS v3.1 base score of 9.8 (CRITICAL) with vector string CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H.
What CWE is associated with CVE-2023-43654?
CVE-2023-43654 is classified under CWE-918: Server-Side Request Forgery (SSRF) (The web server receives a URL or similar request from an upstream component and retrieves the contents of this URL, but it does not sufficiently ensure that the request is being sent to the expected destination.).
How can I check PyPI dependencies for CVE-2023-43654?
Run the dependency tree command: 'pip show torchserve'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-8fxr-qfr9-p34w",
  "modified" : "2023-11-01T06:09:57Z",
  "published" : "2023-10-02T20:39:20Z",
  "aliases" : [ "CVE-2023-43654" ],
  "summary" : "TorchServe Server-Side Request Forgery vulnerability",
  "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.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "torchserve"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0.1.0"
      }, {
        "fixed" : "0.8.2"
      } ]
    } ]
  } ],
  "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",
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  }, {
    "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"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-918" ],
    "severity" : "CRITICAL",
    "github_reviewed" : true,
    "github_reviewed_at" : "2023-10-02T20:39:20Z",
    "nvd_published_at" : "2023-09-28T23:15:09Z"
  }
}