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CVSS: 9.8EPSS: 0%CPEs: 1EXPL: 0

TorchServe is a flexible and easy-to-use tool for serving and scaling PyTorch models in production. TorchServe 's check on allowed_urls configuration can be by-passed if the URL contains characters such as ".." but it does not prevent the model from being downloaded into the model store. Once a file is downloaded, it can be referenced without providing a URL the second time, which effectively bypasses the allowed_urls security check. Customers using PyTorch inference Deep Learning Containers (DLC) through Amazon SageMaker and EKS are not affected. This issue in TorchServe has been fixed by validating the URL without characters such as ".." before downloading see PR #3082. • https://github.com/pytorch/serve/pull/3082 https://github.com/pytorch/serve/releases/tag/v0.11.0 https://github.com/pytorch/serve/security/advisories/GHSA-wxcx-gg9c-fwp2 • CWE-706: Use of Incorrectly-Resolved Name or Reference •

CVSS: 8.2EPSS: 0%CPEs: 1EXPL: 0

TorchServe is a flexible and easy-to-use tool for serving and scaling PyTorch models in production. In affected versions the two gRPC ports 7070 and 7071, are not bound to [localhost](http://localhost/) by default, so when TorchServe is launched, these two interfaces are bound to all interfaces. Customers using PyTorch inference Deep Learning Containers (DLC) through Amazon SageMaker and EKS are not affected. This issue in TorchServe has been fixed in PR #3083. TorchServe release 0.11.0 includes the fix to address this vulnerability. • https://github.com/pytorch/serve/pull/3083 https://github.com/pytorch/serve/releases/tag/v0.11.0 https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w • CWE-668: Exposure of Resource to Wrong Sphere •

CVSS: 5.3EPSS: 0%CPEs: 1EXPL: 0

TorchServe is a tool for serving and scaling PyTorch models in production. Starting in version 0.1.0 and prior to version 0.9.0, using the model/workflow management API, there is a chance of uploading potentially harmful archives that contain files that are extracted to any location on the filesystem that is within the process permissions. Leveraging this issue could aid third-party actors in hiding harmful code in open-source/public models, which can be downloaded from the internet, and take advantage of machines running Torchserve. The ZipSlip issue in TorchServe has been fixed by validating the paths of files contained within a zip archive before extracting them. TorchServe release 0.9.0 includes fixes to address the ZipSlip vulnerability. • https://github.com/pytorch/serve/commit/bfb3d42396727614aef625143b4381e64142f9bb https://github.com/pytorch/serve/pull/2634 https://github.com/pytorch/serve/releases/tag/v0.9.0 https://github.com/pytorch/serve/security/advisories/GHSA-m2mj-pr4f-h9jp • CWE-22: Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal') •

CVSS: 10.0EPSS: 14%CPEs: 1EXPL: 2

TorchServe is a tool for serving and scaling PyTorch models in production. 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. A user is able to load the model of their choice from any URL that they would like to use. • https://github.com/OligoCyberSecurity/CVE-2023-43654 http://packetstormsecurity.com/files/175095/PyTorch-Model-Server-Registration-Deserialization-Remote-Code-Execution.html https://github.com/pytorch/serve/pull/2534 https://github.com/pytorch/serve/releases/tag/v0.8.2 https://github.com/pytorch/serve/security/advisories/GHSA-8fxr-qfr9-p34w - • CWE-918: Server-Side Request Forgery (SSRF) •