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.
CWE
  • CWE-668 - Exposure of Resource to Wrong Sphere
Assigner
Impacted products
Vendor Product Version
pytorch serve Affected: >= 0.3.0, < 0.11.0
Create a notification for this product.
Show details on NVD website

{
  "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",
  "vulnerability-lookup:meta": {
    "fkie_nvd": {
      "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": "2024-11-21T09:19:55.093",
      "metrics": "{\"cvssMetricV31\": [{\"source\": \"security-advisories@github.com\", \"type\": \"Secondary\", \"cvssData\": {\"version\": \"3.1\", \"vectorString\": \"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:H\", \"baseScore\": 8.2, \"baseSeverity\": \"HIGH\", \"attackVector\": \"NETWORK\", \"attackComplexity\": \"LOW\", \"privilegesRequired\": \"NONE\", \"userInteraction\": \"NONE\", \"scope\": \"UNCHANGED\", \"confidentialityImpact\": \"LOW\", \"integrityImpact\": \"NONE\", \"availabilityImpact\": \"HIGH\"}, \"exploitabilityScore\": 3.9, \"impactScore\": 4.2}]}",
      "published": "2024-07-19T02:15:14.777",
      "references": "[{\"url\": \"https://github.com/pytorch/serve/pull/3083\", \"source\": \"security-advisories@github.com\"}, {\"url\": \"https://github.com/pytorch/serve/releases/tag/v0.11.0\", \"source\": \"security-advisories@github.com\"}, {\"url\": \"https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w\", \"source\": \"security-advisories@github.com\"}, {\"url\": \"https://github.com/pytorch/serve/pull/3083\", \"source\": \"af854a3a-2127-422b-91ae-364da2661108\"}, {\"url\": \"https://github.com/pytorch/serve/releases/tag/v0.11.0\", \"source\": \"af854a3a-2127-422b-91ae-364da2661108\"}, {\"url\": \"https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w\", \"source\": \"af854a3a-2127-422b-91ae-364da2661108\"}]",
      "sourceIdentifier": "security-advisories@github.com",
      "vulnStatus": "Awaiting Analysis",
      "weaknesses": "[{\"source\": \"security-advisories@github.com\", \"type\": \"Secondary\", \"description\": [{\"lang\": \"en\", \"value\": \"CWE-668\"}]}]"
    },
    "nvd": "{\"cve\":{\"id\":\"CVE-2024-35199\",\"sourceIdentifier\":\"security-advisories@github.com\",\"published\":\"2024-07-19T02:15:14.777\",\"lastModified\":\"2025-09-04T15:46:54.180\",\"vulnStatus\":\"Analyzed\",\"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.\"}],\"metrics\":{\"cvssMetricV31\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Secondary\",\"cvssData\":{\"version\":\"3.1\",\"vectorString\":\"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:H\",\"baseScore\":8.2,\"baseSeverity\":\"HIGH\",\"attackVector\":\"NETWORK\",\"attackComplexity\":\"LOW\",\"privilegesRequired\":\"NONE\",\"userInteraction\":\"NONE\",\"scope\":\"UNCHANGED\",\"confidentialityImpact\":\"LOW\",\"integrityImpact\":\"NONE\",\"availabilityImpact\":\"HIGH\"},\"exploitabilityScore\":3.9,\"impactScore\":4.2}]},\"weaknesses\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Secondary\",\"description\":[{\"lang\":\"en\",\"value\":\"CWE-668\"}]}],\"configurations\":[{\"nodes\":[{\"operator\":\"OR\",\"negate\":false,\"cpeMatch\":[{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:pytorch:torchserve:*:*:*:*:*:*:*:*\",\"versionStartIncluding\":\"0.3.0\",\"versionEndExcluding\":\"0.11.0\",\"matchCriteriaId\":\"2842A556-E7AC-4040-94D7-332C132F9B0C\"}]}]}],\"references\":[{\"url\":\"https://github.com/pytorch/serve/pull/3083\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Patch\"]},{\"url\":\"https://github.com/pytorch/serve/releases/tag/v0.11.0\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Release Notes\"]},{\"url\":\"https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/pytorch/serve/pull/3083\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Patch\"]},{\"url\":\"https://github.com/pytorch/serve/releases/tag/v0.11.0\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Release Notes\"]},{\"url\":\"https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Patch\",\"Third Party Advisory\"]}]}}",
    "vulnrichment": {
      "containers": "{\"adp\": [{\"title\": \"CVE Program Container\", \"references\": [{\"url\": \"https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w\", \"name\": \"https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w\", \"tags\": [\"x_refsource_CONFIRM\", \"x_transferred\"]}, {\"url\": \"https://github.com/pytorch/serve/pull/3083\", \"name\": \"https://github.com/pytorch/serve/pull/3083\", \"tags\": [\"x_refsource_MISC\", \"x_transferred\"]}, {\"url\": \"https://github.com/pytorch/serve/releases/tag/v0.11.0\", \"name\": \"https://github.com/pytorch/serve/releases/tag/v0.11.0\", \"tags\": [\"x_refsource_MISC\", \"x_transferred\"]}], \"providerMetadata\": {\"orgId\": \"af854a3a-2127-422b-91ae-364da2661108\", \"shortName\": \"CVE\", \"dateUpdated\": \"2024-08-02T03:07:46.885Z\"}}, {\"title\": \"CISA ADP Vulnrichment\", \"metrics\": [{\"other\": {\"type\": \"ssvc\", \"content\": {\"id\": \"CVE-2024-35199\", \"role\": \"CISA Coordinator\", \"options\": [{\"Exploitation\": \"none\"}, {\"Automatable\": \"yes\"}, {\"Technical Impact\": \"partial\"}], \"version\": \"2.0.3\", \"timestamp\": \"2024-07-19T16:50:48.409416Z\"}}}], \"affected\": [{\"cpes\": [\"cpe:2.3:a:pytorch:torchserve:0.3.0:*:*:*:*:*:*:*\"], \"vendor\": \"pytorch\", \"product\": \"torchserve\", \"versions\": [{\"status\": \"affected\", \"version\": \"0.3.0\", \"lessThan\": \"0.11.0\", \"versionType\": \"custom\"}], \"defaultStatus\": \"unknown\"}], \"providerMetadata\": {\"orgId\": \"134c704f-9b21-4f2e-91b3-4a467353bcc0\", \"shortName\": \"CISA-ADP\", \"dateUpdated\": \"2024-07-19T16:57:09.394Z\"}}], \"cna\": {\"title\": \"TorchServe gRPC Port Exposure\", \"source\": {\"advisory\": \"GHSA-hhpg-v63p-wp7w\", \"discovery\": \"UNKNOWN\"}, \"metrics\": [{\"cvssV3_1\": {\"scope\": \"UNCHANGED\", \"version\": \"3.1\", \"baseScore\": 8.2, \"attackVector\": \"NETWORK\", \"baseSeverity\": \"HIGH\", \"vectorString\": \"CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:H\", \"integrityImpact\": \"NONE\", \"userInteraction\": \"NONE\", \"attackComplexity\": \"LOW\", \"availabilityImpact\": \"HIGH\", \"privilegesRequired\": \"NONE\", \"confidentialityImpact\": \"LOW\"}}], \"affected\": [{\"vendor\": \"pytorch\", \"product\": \"serve\", \"versions\": [{\"status\": \"affected\", \"version\": \"\u003e= 0.3.0, \u003c 0.11.0\"}]}], \"references\": [{\"url\": \"https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w\", \"name\": \"https://github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7w\", \"tags\": [\"x_refsource_CONFIRM\"]}, {\"url\": \"https://github.com/pytorch/serve/pull/3083\", \"name\": \"https://github.com/pytorch/serve/pull/3083\", \"tags\": [\"x_refsource_MISC\"]}, {\"url\": \"https://github.com/pytorch/serve/releases/tag/v0.11.0\", \"name\": \"https://github.com/pytorch/serve/releases/tag/v0.11.0\", \"tags\": [\"x_refsource_MISC\"]}], \"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.\"}], \"problemTypes\": [{\"descriptions\": [{\"lang\": \"en\", \"type\": \"CWE\", \"cweId\": \"CWE-668\", \"description\": \"CWE-668: Exposure of Resource to Wrong Sphere\"}]}], \"providerMetadata\": {\"orgId\": \"a0819718-46f1-4df5-94e2-005712e83aaa\", \"shortName\": \"GitHub_M\", \"dateUpdated\": \"2024-08-07T15:59:53.795Z\"}}}",
      "cveMetadata": "{\"cveId\": \"CVE-2024-35199\", \"state\": \"PUBLISHED\", \"dateUpdated\": \"2024-08-07T15:59:53.795Z\", \"dateReserved\": \"2024-05-10T14:24:24.343Z\", \"assignerOrgId\": \"a0819718-46f1-4df5-94e2-005712e83aaa\", \"datePublished\": \"2024-07-18T22:40:06.549Z\", \"assignerShortName\": \"GitHub_M\"}",
      "dataType": "CVE_RECORD",
      "dataVersion": "5.1"
    }
  }
}


Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

Sightings

Author Source Type Date

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.


Loading…

Detection rules are retrieved from Rulezet.

Loading…

Loading…