CVE-2024-35198

criticalpriority · track · 0EPSS 0.008 · 56 %ileDEEUUS
grimoire priorityP2 · Scheduled
Exploitable?
—
no known exploitation
Likely / severe?
0.80% (56th) EPSS
CVSS 9.8 · critical
Is it mine?
3 products
Check your exposure
Who says so?
5 sources
cnnvd · enisa_euvd · osv · nvd

EPSS · scored 2026-10-27

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. TorchServe release 0.11.0 includes the fix to address this vulnerability. Users are advised to upgrade. There are no known workarounds for this vulnerability.

01

cvss

Technical severity, 0–10. One row per scoring source.

9.8
010

base score 0–10 · higher = more severe · hover a vector to decode

v3.19.8criticalCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:Hsecondary · ENISA EU
v3.19.8criticalCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:Hsecondary · security-advisories@github.comexploitability 3.9 · impact 5.9
v3.19.8criticalCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:Hsecondary · OSV
v3.19criticalCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H/E:Usecondary · CVSS-BT (t0sche)
02

ssvc

A stakeholder decision — act, attend, or track — from exploitation and impact.

Trackcoordinatorcisa_ssvcUS
03

weaknesses

The CWE weakness classes this flaw belongs to.

CWE-22USCWE-706USCWE-706US
04

affected products (3)

Products and version ranges known to be affected.

05

advisories (3)

Vendor and ecosystem advisories describing this.

  • WID-SEC-W-2024-1687PyTorch: Mehrere SchwachstellenDeutsch2024-07-22csaf · cert_bundDE

    Ein entfernter anonymer Angreifer kann mehrere Schwachstellen in PyTorch ausnutzen, um Sicherheitsmaßnahmen zu umgehen oder einen unspezifischen Angriff durchzuführen.

  • GHSA-wxcx-gg9c-fwp2TorchServe vulnerable to bypass of allowed_urls configuration2024-07-18ghsa · osvUS

    ### Impact 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. ### Patches This issue in TorchServe has been fixed by validating the URL without characters such as ".." before downloading: [#3082](https://github.com/pytorch/serve/pull/3082). TorchServe release 0.11.0 includes the fix to address this vulnerability. ### References * [#3082](https://github.com/pytorch/serve/pull/3082) * [TorchServe release v0.11.0](https://github.com/pytorch/serve/releases/tag/v0.11.0) Thank Kroll Cyber Risk for for responsibly disclosing this issue. If you have any questions or comments about this advisory, we ask that you contact AWS Security via our [vulnerability reporting page](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.

  • PYSEC-2026-554TorchServe vulnerable to bypass of allowed_urls configuration2026-06-29vendor · osvUS

    ### Impact 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. ### Patches This issue in TorchServe has been fixed by validating the URL without characters such as ".." before downloading: [#3082](https://github.com/pytorch/serve/pull/3082). TorchServe release 0.11.0 includes the fix to address this vulnerability. ### References * [#3082](https://github.com/pytorch/serve/pull/3082) * [TorchServe release v0.11.0](https://github.com/pytorch/serve/releases/tag/v0.11.0) Thank Kroll Cyber Risk for for responsibly disclosing this issue. If you have any questions or comments about this advisory, we ask that you contact AWS Security via our [vulnerability reporting page](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.

06

also known as (6)

Other names and identifiers for this entity.

07

sources

Which sources assert this record, and when.

cnnvdenisa_euvdosvnvdcert_bundNVDCVE.orgMITRE
published 2024-07-19modified 2026-06-17
08

references (11)

External citations — patches, advisories, analysis.

scry

Attackers weaponise vulnerabilities like this against internet-exposed services. See what is exposed on your perimeter with a free passive scan.

Free scan