GHSA-4mqg-h5jf-j9m7: Torchserve Remote Code Execution Vulnerability
CRITICALGHSA-4mqg-h5jf-j9m7 is a CRITICAL (CVSS 9.9) remote code execution vulnerability (CWE-913: Improper Control of Dynamically-Managed Code Resources) affecting Torchserve libraries in the PyPI ecosystem. The issue involves torchserve pre-auth remote code execution. Remediation is available by upgrading affected packages to version 0.8.2.
GHSA-4mqg-h5jf-j9m7 at a Glance
Security Impact
CVSS: 9.9
The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H).
How to Fix GHSA-4mqg-h5jf-j9m7
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.
pip install torchserve>=0.8.2Run the following command in your project directory to verify that all resolved dependencies use the patched release:
pip show torchserveHow to Check if You Are Affected
To determine whether your Python environment is affected by GHSA-4mqg-h5jf-j9m7, inspect your installed packages using pip:
pip show torchserveAnalyze 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-913: Improper Control of Dynamically-Managed Code Resources, where the product does not properly restrict reading from or writing to dynamically-managed code resources such as variables, objects, classes, attributes, functions, or executable instructions or statements. 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
GHSA-4mqg-h5jf-j9m7 Affected Torchserve Versions
1 component(s)| Product / Package | Ecosystem | Affected Versions | Fixed Version |
|---|---|---|---|
|
torchserve
|
PyPI |
≥ 0.3.0
< 0.8.2
|
0.8.2
|
References
Frequently Asked Questions
What is GHSA-4mqg-h5jf-j9m7?
Which Torchserve versions are affected?
What version fixes GHSA-4mqg-h5jf-j9m7?
Is torchserve affected?
What is the CVSS score of GHSA-4mqg-h5jf-j9m7?
What CWE is associated with GHSA-4mqg-h5jf-j9m7?
How can I check PyPI dependencies for GHSA-4mqg-h5jf-j9m7?
Machine-readable OSV JSON
OSV v1.5 Schema
{
"schema_version" : "1.4.0",
"id" : "GHSA-4mqg-h5jf-j9m7",
"modified" : "2023-10-02T20:38:07Z",
"published" : "2023-10-02T20:38:07Z",
"aliases" : [ ],
"summary" : "TorchServe Pre-Auth Remote Code Execution",
"details" : "## Impact\n\n**Use of Open Source Library potentially exposed to RCE**\n **Issue**: Use of a version of the SnakeYAML `v1.31 `open source library with multiple issues that potentially exposes the user to unsafe deserialization of Java objects. This could allow third parties to execute arbitrary code on the target system. This issue is present in versions `0.3.0` to `0.8.1`.\n **Mitigation**: A pull request to address this issue has been merged - https://github.com/pytorch/serve/pull/2523. TorchServe release `0.8.2` includes this fix.\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/pull/2523\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:L/UI:N/S:C/C:H/I:H/A:H"
} ],
"affected" : [ {
"package" : {
"ecosystem" : "PyPI",
"name" : "torchserve"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "0.3.0"
}, {
"fixed" : "0.8.2"
} ]
} ]
} ],
"references" : [ {
"type" : "WEB",
"url" : "https://github.com/pytorch/serve/security/advisories/GHSA-4mqg-h5jf-j9m7"
}, {
"type" : "WEB",
"url" : "https://github.com/pytorch/serve/pull/2523"
}, {
"type" : "PACKAGE",
"url" : "https://github.com/pytorch/serve"
} ],
"database_specific" : {
"cwe_ids" : [ "CWE-913" ],
"severity" : "CRITICAL",
"github_reviewed" : true,
"github_reviewed_at" : "2023-10-02T20:38:07Z",
"nvd_published_at" : null
}
}