Vulnerabilites related to pytorch - torchserve
CVE-2024-35198 (GCVE-0-2024-35198)
Vulnerability from cvelistv5
Published
2024-07-18 22:40
Modified
2024-08-07 16:00
Severity ?
VLAI Severity ?
EPSS score ?
CWE
- CWE-706 - Use of Incorrectly-Resolved Name or Reference
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.
References
| ▼ | URL | Tags |
|---|---|---|
| https://github.com/pytorch/serve/security/advisories/GHSA-wxcx-gg9c-fwp2 | x_refsource_CONFIRM | |
| https://github.com/pytorch/serve/pull/3082 | x_refsource_MISC | |
| https://github.com/pytorch/serve/releases/tag/v0.11.0 | x_refsource_MISC |
{
"containers": {
"adp": [
{
"metrics": [
{
"other": {
"content": {
"id": "CVE-2024-35198",
"options": [
{
"Exploitation": "none"
},
{
"Automatable": "no"
},
{
"Technical Impact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2024-07-19T16:58:05.654373Z",
"version": "2.0.3"
},
"type": "ssvc"
}
}
],
"providerMetadata": {
"dateUpdated": "2024-07-19T16:58:12.450Z",
"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"shortName": "CISA-ADP"
},
"title": "CISA ADP Vulnrichment"
},
{
"providerMetadata": {
"dateUpdated": "2024-08-02T03:07:46.750Z",
"orgId": "af854a3a-2127-422b-91ae-364da2661108",
"shortName": "CVE"
},
"references": [
{
"name": "https://github.com/pytorch/serve/security/advisories/GHSA-wxcx-gg9c-fwp2",
"tags": [
"x_refsource_CONFIRM",
"x_transferred"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-wxcx-gg9c-fwp2"
},
{
"name": "https://github.com/pytorch/serve/pull/3082",
"tags": [
"x_refsource_MISC",
"x_transferred"
],
"url": "https://github.com/pytorch/serve/pull/3082"
},
{
"name": "https://github.com/pytorch/serve/releases/tag/v0.11.0",
"tags": [
"x_refsource_MISC",
"x_transferred"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.11.0"
}
],
"title": "CVE Program Container"
}
],
"cna": {
"affected": [
{
"product": "serve",
"vendor": "pytorch",
"versions": [
{
"status": "affected",
"version": "\u003e= 0.4.2, \u003c 0.11.0"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "TorchServe is a flexible and easy-to-use tool for serving and scaling PyTorch models in production. TorchServe \u0027s 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."
}
],
"metrics": [
{
"cvssV3_1": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-706",
"description": "CWE-706: Use of Incorrectly-Resolved Name or Reference",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2024-08-07T16:00:46.093Z",
"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"shortName": "GitHub_M"
},
"references": [
{
"name": "https://github.com/pytorch/serve/security/advisories/GHSA-wxcx-gg9c-fwp2",
"tags": [
"x_refsource_CONFIRM"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-wxcx-gg9c-fwp2"
},
{
"name": "https://github.com/pytorch/serve/pull/3082",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/pytorch/serve/pull/3082"
},
{
"name": "https://github.com/pytorch/serve/releases/tag/v0.11.0",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.11.0"
}
],
"source": {
"advisory": "GHSA-wxcx-gg9c-fwp2",
"discovery": "UNKNOWN"
},
"title": "TorchServe bypass allowed_urls configuration"
}
},
"cveMetadata": {
"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"assignerShortName": "GitHub_M",
"cveId": "CVE-2024-35198",
"datePublished": "2024-07-18T22:40:08.176Z",
"dateReserved": "2024-05-10T14:24:24.343Z",
"dateUpdated": "2024-08-07T16:00:46.093Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
CVE-2023-43654 (GCVE-0-2023-43654)
Vulnerability from cvelistv5
Published
2023-09-28 22:10
Modified
2025-02-13 17:13
Severity ?
VLAI Severity ?
EPSS score ?
CWE
- CWE-918 - Server-Side Request Forgery (SSRF)
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.
References
{
"containers": {
"adp": [
{
"providerMetadata": {
"dateUpdated": "2024-08-02T19:44:43.856Z",
"orgId": "af854a3a-2127-422b-91ae-364da2661108",
"shortName": "CVE"
},
"references": [
{
"name": "https://github.com/pytorch/serve/security/advisories/GHSA-8fxr-qfr9-p34w",
"tags": [
"x_refsource_CONFIRM",
"x_transferred"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-8fxr-qfr9-p34w"
},
{
"name": "https://github.com/pytorch/serve/pull/2534",
"tags": [
"x_refsource_MISC",
"x_transferred"
],
"url": "https://github.com/pytorch/serve/pull/2534"
},
{
"name": "https://github.com/pytorch/serve/releases/tag/v0.8.2",
"tags": [
"x_refsource_MISC",
"x_transferred"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.8.2"
},
{
"tags": [
"x_transferred"
],
"url": "http://packetstormsecurity.com/files/175095/PyTorch-Model-Server-Registration-Deserialization-Remote-Code-Execution.html"
}
],
"title": "CVE Program Container"
},
{
"affected": [
{
"cpes": [
"cpe:2.3:a:pytorch:torchserve:*:*:*:*:*:*:*:*"
],
"defaultStatus": "unknown",
"product": "torchserve",
"vendor": "pytorch",
"versions": [
{
"lessThan": "0.8.2",
"status": "affected",
"version": "0.1.0",
"versionType": "custom"
}
]
}
],
"metrics": [
{
"other": {
"content": {
"id": "CVE-2023-43654",
"options": [
{
"Exploitation": "poc"
},
{
"Automatable": "yes"
},
{
"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"
}
CVE-2024-35199 (GCVE-0-2024-35199)
Vulnerability from cvelistv5
Published
2024-07-18 22:40
Modified
2024-08-07 15:59
Severity ?
VLAI Severity ?
EPSS score ?
CWE
- CWE-668 - Exposure of Resource to Wrong Sphere
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.
References
| ▼ | URL | Tags |
|---|---|---|
| https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w | x_refsource_CONFIRM | |
| https://github.com/pytorch/serve/pull/3083 | x_refsource_MISC | |
| https://github.com/pytorch/serve/releases/tag/v0.11.0 | x_refsource_MISC |
{
"containers": {
"adp": [
{
"affected": [
{
"cpes": [
"cpe:2.3:a:pytorch:torchserve:0.3.0:*:*:*:*:*:*:*"
],
"defaultStatus": "unknown",
"product": "torchserve",
"vendor": "pytorch",
"versions": [
{
"lessThan": "0.11.0",
"status": "affected",
"version": "0.3.0",
"versionType": "custom"
}
]
}
],
"metrics": [
{
"other": {
"content": {
"id": "CVE-2024-35199",
"options": [
{
"Exploitation": "none"
},
{
"Automatable": "yes"
},
{
"Technical Impact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2024-07-19T16:50:48.409416Z",
"version": "2.0.3"
},
"type": "ssvc"
}
}
],
"providerMetadata": {
"dateUpdated": "2024-07-19T16:57:14.131Z",
"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"shortName": "CISA-ADP"
},
"title": "CISA ADP Vulnrichment"
},
{
"providerMetadata": {
"dateUpdated": "2024-08-02T03:07:46.885Z",
"orgId": "af854a3a-2127-422b-91ae-364da2661108",
"shortName": "CVE"
},
"references": [
{
"name": "https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w",
"tags": [
"x_refsource_CONFIRM",
"x_transferred"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w"
},
{
"name": "https://github.com/pytorch/serve/pull/3083",
"tags": [
"x_refsource_MISC",
"x_transferred"
],
"url": "https://github.com/pytorch/serve/pull/3083"
},
{
"name": "https://github.com/pytorch/serve/releases/tag/v0.11.0",
"tags": [
"x_refsource_MISC",
"x_transferred"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.11.0"
}
],
"title": "CVE Program Container"
}
],
"cna": {
"affected": [
{
"product": "serve",
"vendor": "pytorch",
"versions": [
{
"status": "affected",
"version": "\u003e= 0.3.0, \u003c 0.11.0"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "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."
}
],
"metrics": [
{
"cvssV3_1": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.2,
"baseSeverity": "HIGH",
"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:H",
"version": "3.1"
}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-668",
"description": "CWE-668: Exposure of Resource to Wrong Sphere",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2024-08-07T15:59:53.795Z",
"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"shortName": "GitHub_M"
},
"references": [
{
"name": "https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w",
"tags": [
"x_refsource_CONFIRM"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w"
},
{
"name": "https://github.com/pytorch/serve/pull/3083",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/pytorch/serve/pull/3083"
},
{
"name": "https://github.com/pytorch/serve/releases/tag/v0.11.0",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.11.0"
}
],
"source": {
"advisory": "GHSA-hhpg-v63p-wp7w",
"discovery": "UNKNOWN"
},
"title": "TorchServe gRPC Port Exposure"
}
},
"cveMetadata": {
"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"assignerShortName": "GitHub_M",
"cveId": "CVE-2024-35199",
"datePublished": "2024-07-18T22:40:06.549Z",
"dateReserved": "2024-05-10T14:24:24.343Z",
"dateUpdated": "2024-08-07T15:59:53.795Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
CVE-2023-48299 (GCVE-0-2023-48299)
Vulnerability from cvelistv5
Published
2023-11-21 20:55
Modified
2024-08-02 21:23
Severity ?
VLAI Severity ?
EPSS score ?
CWE
- CWE-22 - Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
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.
References
| ▼ | URL | Tags |
|---|---|---|
| https://github.com/pytorch/serve/security/advisories/GHSA-m2mj-pr4f-h9jp | x_refsource_CONFIRM | |
| https://github.com/pytorch/serve/pull/2634 | x_refsource_MISC | |
| https://github.com/pytorch/serve/commit/bfb3d42396727614aef625143b4381e64142f9bb | x_refsource_MISC | |
| https://github.com/pytorch/serve/releases/tag/v0.9.0 | x_refsource_MISC |
{
"containers": {
"adp": [
{
"providerMetadata": {
"dateUpdated": "2024-08-02T21:23:39.504Z",
"orgId": "af854a3a-2127-422b-91ae-364da2661108",
"shortName": "CVE"
},
"references": [
{
"name": "https://github.com/pytorch/serve/security/advisories/GHSA-m2mj-pr4f-h9jp",
"tags": [
"x_refsource_CONFIRM",
"x_transferred"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-m2mj-pr4f-h9jp"
},
{
"name": "https://github.com/pytorch/serve/pull/2634",
"tags": [
"x_refsource_MISC",
"x_transferred"
],
"url": "https://github.com/pytorch/serve/pull/2634"
},
{
"name": "https://github.com/pytorch/serve/commit/bfb3d42396727614aef625143b4381e64142f9bb",
"tags": [
"x_refsource_MISC",
"x_transferred"
],
"url": "https://github.com/pytorch/serve/commit/bfb3d42396727614aef625143b4381e64142f9bb"
},
{
"name": "https://github.com/pytorch/serve/releases/tag/v0.9.0",
"tags": [
"x_refsource_MISC",
"x_transferred"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.9.0"
}
],
"title": "CVE Program Container"
}
],
"cna": {
"affected": [
{
"product": "serve",
"vendor": "pytorch",
"versions": [
{
"status": "affected",
"version": "\u003e= 0.1.0, \u003c 0.9.0"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "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."
}
],
"metrics": [
{
"cvssV3_1": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:N",
"version": "3.1"
}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-22",
"description": "CWE-22: Improper Limitation of a Pathname to a Restricted Directory (\u0027Path Traversal\u0027)",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2023-11-21T20:55:59.504Z",
"orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"shortName": "GitHub_M"
},
"references": [
{
"name": "https://github.com/pytorch/serve/security/advisories/GHSA-m2mj-pr4f-h9jp",
"tags": [
"x_refsource_CONFIRM"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-m2mj-pr4f-h9jp"
},
{
"name": "https://github.com/pytorch/serve/pull/2634",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/pytorch/serve/pull/2634"
},
{
"name": "https://github.com/pytorch/serve/commit/bfb3d42396727614aef625143b4381e64142f9bb",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/pytorch/serve/commit/bfb3d42396727614aef625143b4381e64142f9bb"
},
{
"name": "https://github.com/pytorch/serve/releases/tag/v0.9.0",
"tags": [
"x_refsource_MISC"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.9.0"
}
],
"source": {
"advisory": "GHSA-m2mj-pr4f-h9jp",
"discovery": "UNKNOWN"
},
"title": "TorchServe ZipSlip"
}
},
"cveMetadata": {
"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
"assignerShortName": "GitHub_M",
"cveId": "CVE-2023-48299",
"datePublished": "2023-11-21T20:55:59.504Z",
"dateReserved": "2023-11-14T17:41:15.571Z",
"dateUpdated": "2024-08-02T21:23:39.504Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
Vulnerability from fkie_nvd
Published
2023-09-28 23:15
Modified
2024-11-21 08:24
Severity ?
10.0 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
9.8 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
9.8 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
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.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| pytorch | torchserve | * |
{
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:pytorch:torchserve:*:*:*:*:*:*:*:*",
"matchCriteriaId": "1C72B515-779F-4815-B20E-80DF998B771B",
"versionEndExcluding": "0.8.2",
"versionStartIncluding": "0.1.0",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"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."
},
{
"lang": "es",
"value": "TorchServe es una herramienta para servir y escalar modelos de PyTorch en producci\u00f3n. La configuraci\u00f3n predeterminada de TorchServe carece de una validaci\u00f3n de entrada adecuada, lo que permite a terceros invocar solicitudes de descarga HTTP remotas y escribir archivos en el disco. Se podr\u00eda aprovechar este problema para comprometer la integridad del sistema y los datos confidenciales. Este problema est\u00e1 presente en las versiones 0.1.0 a 0.8.1. Un usuario puede cargar el modelo de su elecci\u00f3n desde cualquier URL que desee utilizar. El usuario de TorchServe es responsable de configurar las URL permitidas y especificar la URL modelo que se utilizar\u00e1. En PR #2534 se fusion\u00f3 una solicitud de extracci\u00f3n para advertir al usuario cuando se utiliza el valor predeterminado para Allow_urls. La versi\u00f3n 0.8.2 de TorchServe incluye este cambio. Se recomienda a los usuarios que actualicen. No se conocen workarounds para este problema."
}
],
"id": "CVE-2023-43654",
"lastModified": "2024-11-21T08:24:33.150",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 10.0,
"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"
},
"exploitabilityScore": 3.9,
"impactScore": 6.0,
"source": "security-advisories@github.com",
"type": "Secondary"
},
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 5.9,
"source": "nvd@nist.gov",
"type": "Primary"
}
]
},
"published": "2023-09-28T23:15:09.627",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
"Exploit",
"Third Party Advisory",
"VDB Entry"
],
"url": "http://packetstormsecurity.com/files/175095/PyTorch-Model-Server-Registration-Deserialization-Remote-Code-Execution.html"
},
{
"source": "security-advisories@github.com",
"tags": [
"Issue Tracking"
],
"url": "https://github.com/pytorch/serve/pull/2534"
},
{
"source": "security-advisories@github.com",
"tags": [
"Release Notes"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.8.2"
},
{
"source": "security-advisories@github.com",
"tags": [
"Vendor Advisory"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-8fxr-qfr9-p34w"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Exploit",
"Third Party Advisory",
"VDB Entry"
],
"url": "http://packetstormsecurity.com/files/175095/PyTorch-Model-Server-Registration-Deserialization-Remote-Code-Execution.html"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Issue Tracking"
],
"url": "https://github.com/pytorch/serve/pull/2534"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Release Notes"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.8.2"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Vendor Advisory"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-8fxr-qfr9-p34w"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-918"
}
],
"source": "security-advisories@github.com",
"type": "Primary"
}
]
}
Vulnerability from fkie_nvd
Published
2023-11-21 21:15
Modified
2024-11-21 08:31
Severity ?
5.3 (Medium) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:N
5.3 (Medium) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:N
5.3 (Medium) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:N
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.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| pytorch | torchserve | * |
{
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:pytorch:torchserve:*:*:*:*:*:*:*:*",
"matchCriteriaId": "F958D5AE-E57F-4C08-A946-D75B9857CD1B",
"versionEndExcluding": "0.9.0",
"versionStartIncluding": "0.1.0",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "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."
},
{
"lang": "es",
"value": "TorchServe es una herramienta para servir y escalar modelos de PyTorch en producci\u00f3n. A partir de la versi\u00f3n 0.1.0 y antes de la versi\u00f3n 0.9.0, al utilizar la API de administraci\u00f3n de modelo/flujo de trabajo, existe la posibilidad de cargar archivos potencialmente da\u00f1inos que contengan archivos extra\u00eddos a cualquier ubicaci\u00f3n del sistema de archivos que est\u00e9 dentro de los permisos del proceso. Aprovechar este problema podr\u00eda ayudar a terceros a ocultar c\u00f3digo da\u00f1ino en modelos p\u00fablicos/de c\u00f3digo abierto, que se pueden descargar de Internet, y aprovechar las m\u00e1quinas que ejecutan Torchserve. El problema de Zipslip en TorchServe se solucion\u00f3 validando las rutas de los archivos contenidos en un archivo zip antes de extraerlos. La versi\u00f3n 0.9.0 de TorchServe incluye correcciones para abordar la vulnerabilidad Zipslip."
}
],
"id": "CVE-2023-48299",
"lastModified": "2024-11-21T08:31:26.243",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:N",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 1.4,
"source": "security-advisories@github.com",
"type": "Secondary"
},
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:N",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 1.4,
"source": "nvd@nist.gov",
"type": "Primary"
}
]
},
"published": "2023-11-21T21:15:09.077",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
"Patch"
],
"url": "https://github.com/pytorch/serve/commit/bfb3d42396727614aef625143b4381e64142f9bb"
},
{
"source": "security-advisories@github.com",
"tags": [
"Patch"
],
"url": "https://github.com/pytorch/serve/pull/2634"
},
{
"source": "security-advisories@github.com",
"tags": [
"Release Notes"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.9.0"
},
{
"source": "security-advisories@github.com",
"tags": [
"Patch",
"Vendor Advisory"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-m2mj-pr4f-h9jp"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch"
],
"url": "https://github.com/pytorch/serve/commit/bfb3d42396727614aef625143b4381e64142f9bb"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch"
],
"url": "https://github.com/pytorch/serve/pull/2634"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Release Notes"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.9.0"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch",
"Vendor Advisory"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-m2mj-pr4f-h9jp"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-22"
}
],
"source": "security-advisories@github.com",
"type": "Primary"
}
]
}
Vulnerability from fkie_nvd
Published
2024-07-19 02:15
Modified
2025-09-04 15:46
Severity ?
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.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| pytorch | torchserve | * |
{
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:pytorch:torchserve:*:*:*:*:*:*:*:*",
"matchCriteriaId": "2842A556-E7AC-4040-94D7-332C132F9B0C",
"versionEndExcluding": "0.11.0",
"versionStartIncluding": "0.3.0",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "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."
},
{
"lang": "es",
"value": "TorchServe es una herramienta flexible y f\u00e1cil de usar para servir y escalar modelos PyTorch en producci\u00f3n. En las versiones afectadas, los dos puertos gRPC 7070 y 7071 no est\u00e1n vinculados a [localhost](http://localhost/) de forma predeterminada, por lo que cuando se inicia TorchServe, estas dos interfaces est\u00e1n vinculadas a todas las interfaces. Los clientes que utilizan contenedores de aprendizaje profundo (DLC) de inferencia de PyTorch a trav\u00e9s de Amazon SageMaker y EKS no se ven afectados. Este problema en TorchServe se solucion\u00f3 en PR #3083. La versi\u00f3n 0.11.0 de TorchServe incluye la soluci\u00f3n para abordar esta vulnerabilidad. Se recomienda a los usuarios que actualicen. No se conocen workarounds para esta vulnerabilidad."
}
],
"id": "CVE-2024-35199",
"lastModified": "2025-09-04T15:46:54.180",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.2,
"baseSeverity": "HIGH",
"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 4.2,
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
},
"published": "2024-07-19T02:15:14.777",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
"Patch"
],
"url": "https://github.com/pytorch/serve/pull/3083"
},
{
"source": "security-advisories@github.com",
"tags": [
"Release Notes"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.11.0"
},
{
"source": "security-advisories@github.com",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch"
],
"url": "https://github.com/pytorch/serve/pull/3083"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Release Notes"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.11.0"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Analyzed",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-668"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}
Vulnerability from fkie_nvd
Published
2024-07-19 02:15
Modified
2025-09-04 15:43
Severity ?
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.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| pytorch | torchserve | * |
{
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:pytorch:torchserve:*:*:*:*:*:*:*:*",
"matchCriteriaId": "44161383-FECC-4722-B2F1-D1162C00B26F",
"versionEndExcluding": "0.11.0",
"versionStartIncluding": "0.4.2",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "TorchServe is a flexible and easy-to-use tool for serving and scaling PyTorch models in production. TorchServe \u0027s 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."
},
{
"lang": "es",
"value": "TorchServe es una herramienta flexible y f\u00e1cil de usar para servir y escalar modelos PyTorch en producci\u00f3n. La verificaci\u00f3n de TorchServe en la configuraci\u00f3n de Allow_urls se puede omitir si la URL contiene caracteres como \"..\" pero no impide que el modelo se descargue en la tienda de modelos. Una vez que se descarga un archivo, se puede hacer referencia a \u00e9l sin proporcionar una URL la segunda vez, lo que efectivamente evita la verificaci\u00f3n de seguridad de Allow_urls. Los clientes que utilizan contenedores de aprendizaje profundo (DLC) de inferencia de PyTorch a trav\u00e9s de Amazon SageMaker y EKS no se ven afectados. Este problema en TorchServe se solucion\u00f3 validando la URL sin caracteres como \"..\" antes de descargar, consulte PR #3082. La versi\u00f3n 0.11.0 de TorchServe incluye la soluci\u00f3n para solucionar esta vulnerabilidad. Se recomienda a los usuarios que actualicen. No se conocen workarounds para esta vulnerabilidad."
}
],
"id": "CVE-2024-35198",
"lastModified": "2025-09-04T15:43:52.833",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 5.9,
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
},
"published": "2024-07-19T02:15:14.150",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
"Patch"
],
"url": "https://github.com/pytorch/serve/pull/3082"
},
{
"source": "security-advisories@github.com",
"tags": [
"Release Notes"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.11.0"
},
{
"source": "security-advisories@github.com",
"tags": [
"Third Party Advisory"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-wxcx-gg9c-fwp2"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch"
],
"url": "https://github.com/pytorch/serve/pull/3082"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Release Notes"
],
"url": "https://github.com/pytorch/serve/releases/tag/v0.11.0"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Third Party Advisory"
],
"url": "https://github.com/pytorch/serve/security/advisories/GHSA-wxcx-gg9c-fwp2"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Analyzed",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-706"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
}
]
}