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10 vulnerabilities by pytorch
CVE-2025-32434 (GCVE-0-2025-32434)
Vulnerability from cvelistv5 – Published: 2025-04-18 15:48 – Updated: 2025-12-01 07:05
VLAI?
Summary
PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0.
Severity ?
CWE
- CWE-502 - Deserialization of Untrusted Data
Assigner
References
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CVE-2024-7804 (GCVE-0-2024-7804)
Vulnerability from cvelistv5 – Published: 2025-03-20 10:11 – Updated: 2025-04-01 16:46
VLAI?
This CVE ID has been rejected or withdrawn by its CVE Numbering Authority.
Show details on NVD website{
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CVE-2024-6577 (GCVE-0-2024-6577)
Vulnerability from cvelistv5 – Published: 2025-03-20 10:10 – Updated: 2025-03-20 18:19
VLAI?
Summary
In the latest version of pytorch/serve, the script 'upload_results_to_s3.sh' references the S3 bucket 'benchmarkai-metrics-prod' without ensuring its ownership or confirming its accessibility. This could lead to potential security vulnerabilities or unauthorized access to the bucket if it is not properly secured or claimed by the appropriate entity. The issue may result in data breaches, exposure of proprietary information, or unauthorized modifications to stored data.
Severity ?
6.3 (Medium)
CWE
- CWE-840 - Business Logic Errors
Assigner
References
Impacted products
| Vendor | Product | Version | ||
|---|---|---|---|---|
| pytorch | pytorch/serve |
Affected:
unspecified , ≤ latest
(custom)
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CVE-2025-2149 (GCVE-0-2025-2149)
Vulnerability from cvelistv5 – Published: 2025-03-10 12:31 – Updated: 2025-03-10 14:08
VLAI?
Summary
A vulnerability was found in PyTorch 2.6.0+cu124. It has been rated as problematic. Affected by this issue is the function nnq_Sigmoid of the component Quantized Sigmoid Module. The manipulation of the argument scale/zero_point leads to improper initialization. The attack needs to be approached locally. The complexity of an attack is rather high. The exploitation is known to be difficult. The exploit has been disclosed to the public and may be used.
Severity ?
CWE
- CWE-665 - Improper Initialization
Assigner
References
| URL | Tags | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
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Credits
Default436352 (VulDB User)
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CVE-2025-2148 (GCVE-0-2025-2148)
Vulnerability from cvelistv5 – Published: 2025-03-10 12:00 – Updated: 2025-03-10 14:10
VLAI?
Summary
A vulnerability was found in PyTorch 2.6.0+cu124. It has been declared as critical. Affected by this vulnerability is the function torch.ops.profiler._call_end_callbacks_on_jit_fut of the component Tuple Handler. The manipulation of the argument None leads to memory corruption. The attack can be launched remotely. The complexity of an attack is rather high. The exploitation appears to be difficult.
Severity ?
CWE
- CWE-119 - Memory Corruption
Assigner
References
| URL | Tags | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
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Credits
Default436352 (VulDB User)
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CVE-2024-35198 (GCVE-0-2024-35198)
Vulnerability from cvelistv5 – Published: 2024-07-18 22:40 – Updated: 2024-08-07 16:00
VLAI?
Summary
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.
Severity ?
9.8 (Critical)
CWE
- CWE-706 - Use of Incorrectly-Resolved Name or Reference
Assigner
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CVE-2024-35199 (GCVE-0-2024-35199)
Vulnerability from cvelistv5 – Published: 2024-07-18 22:40 – Updated: 2024-08-07 15:59
VLAI?
Summary
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. Users are advised to upgrade. There are no known workarounds for this vulnerability.
Severity ?
8.2 (High)
CWE
- CWE-668 - Exposure of Resource to Wrong Sphere
Assigner
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CVE-2024-5480 (GCVE-0-2024-5480)
Vulnerability from cvelistv5 – Published: 2024-06-06 18:17 – Updated: 2024-10-02 15:34
VLAI?
This CVE ID has been rejected or withdrawn by its CVE Numbering Authority.
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CVE-2023-48299 (GCVE-0-2023-48299)
Vulnerability from cvelistv5 – Published: 2023-11-21 20:55 – Updated: 2024-08-02 21:23
VLAI?
Summary
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.
Severity ?
5.3 (Medium)
CWE
- CWE-22 - Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
Assigner
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CVE-2023-43654 (GCVE-0-2023-43654)
Vulnerability from cvelistv5 – Published: 2023-09-28 22:10 – Updated: 2025-02-13 17:13
VLAI?
Summary
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. 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 in PR #2534. TorchServe release 0.8.2 includes this change. Users are advised to upgrade. There are no known workarounds for this issue.
Severity ?
10 (Critical)
CWE
- CWE-918 - Server-Side Request Forgery (SSRF)
Assigner
References
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"Technical Impact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2024-09-23T18:11:45.025680Z",
"version": "2.0.3"
},
"type": "ssvc"
}
}
],
"providerMetadata": {
"dateUpdated": "2024-09-23T18:12:51.982Z",
"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"shortName": "CISA-ADP"
},
"title": "CISA ADP Vulnrichment"
}
],
"cna": {
"affected": [
{
"product": "serve",
"vendor": "pytorch",
"versions": [
{
"status": "affected",
"version": "\u003e= 0.1.0, \u003c 0.8.2"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "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. 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 in PR #2534. TorchServe release 0.8.2 includes this change. Users are advised to upgrade. There are no known workarounds for this issue."
}
],
"metrics": [
{
"cvssV3_1": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 10,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "CHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H",
"version": "3.1"
}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-918",
"description": "CWE-918: Server-Side Request Forgery (SSRF)",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2023-10-13T15:06:29.225Z",
"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"shortName": "GitHub_M"
},
"references": [
{
"name": "https://github.com/pytorch/serve/security/advisories/GHSA-8fxr-qfr9-p34w",
"tags": [
"x_refsource_CONFIRM"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-8fxr-qfr9-p34w"
},
{
"name": "https://github.com/pytorch/serve/pull/2534",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/pytorch/serve/pull/2534"
},
{
"name": "https://github.com/pytorch/serve/releases/tag/v0.8.2",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.8.2"
},
{
"url": "http://packetstormsecurity.com/files/175095/PyTorch-Model-Server-Registration-Deserialization-Remote-Code-Execution.html"
}
],
"source": {
"advisory": "GHSA-8fxr-qfr9-p34w",
"discovery": "UNKNOWN"
},
"title": "TorchServe Server-Side Request Forgery"
}
},
"cveMetadata": {
"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"assignerShortName": "GitHub_M",
"cveId": "CVE-2023-43654",
"datePublished": "2023-09-28T22:10:09.497Z",
"dateReserved": "2023-09-20T15:35:38.147Z",
"dateUpdated": "2025-02-13T17:13:27.341Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}