gsd-2022-23594
Vulnerability from gsd
Modified
2023-12-13 01:19
Details
Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.
Aliases
Aliases
CVE-2022-23594


To clipboard 

{
   GSD: {
      alias: "CVE-2022-23594",
      description: "Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.",
      id: "GSD-2022-23594",
      references: [
         "https://www.suse.com/security/cve/CVE-2022-23594.html",
      ],
   },
   gsd: {
      metadata: {
         exploitCode: "unknown",
         remediation: "unknown",
         reportConfidence: "confirmed",
         type: "vulnerability",
      },
      osvSchema: {
         aliases: [
            "CVE-2022-23594",
         ],
         details: "Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.",
         id: "GSD-2022-23594",
         modified: "2023-12-13T01:19:34.924682Z",
         schema_version: "1.4.0",
      },
   },
   namespaces: {
      "cve.org": {
         CVE_data_meta: {
            ASSIGNER: "security-advisories@github.com",
            ID: "CVE-2022-23594",
            STATE: "PUBLIC",
            TITLE: "Out of bounds read in Tensorflow",
         },
         affects: {
            vendor: {
               vendor_data: [
                  {
                     product: {
                        product_data: [
                           {
                              product_name: "tensorflow",
                              version: {
                                 version_data: [
                                    {
                                       version_value: ">= 2.7.0, < 2.8.0",
                                    },
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                  value: "Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.",
               },
            ],
         },
         impact: {
            cvss: {
               attackComplexity: "LOW",
               attackVector: "LOCAL",
               availabilityImpact: "HIGH",
               baseScore: 8.8,
               baseSeverity: "HIGH",
               confidentialityImpact: "HIGH",
               integrityImpact: "HIGH",
               privilegesRequired: "LOW",
               scope: "CHANGED",
               userInteraction: "NONE",
               vectorString: "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H",
               version: "3.1",
            },
         },
         problemtype: {
            problemtype_data: [
               {
                  description: [
                     {
                        lang: "eng",
                        value: "CWE-125: Out-of-bounds Read",
                     },
                  ],
               },
            ],
         },
         references: {
            reference_data: [
               {
                  name: "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9x52-887g-fhc2",
                  refsource: "CONFIRM",
                  url: "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9x52-887g-fhc2",
               },
               {
                  name: "https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/ir/importexport",
                  refsource: "MISC",
                  url: "https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/ir/importexport",
               },
            ],
         },
         source: {
            advisory: "GHSA-9x52-887g-fhc2",
            discovery: "UNKNOWN",
         },
      },
      "gitlab.com": {
         advisories: [
            {
               affected_range: "==2.7.0",
               affected_versions: "Version 2.7.0",
               cvss_v2: "AV:L/AC:L/Au:N/C:N/I:N/A:P",
               cvss_v3: "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
               cwe_ids: [
                  "CWE-1035",
                  "CWE-125",
                  "CWE-787",
                  "CWE-937",
               ],
               date: "2022-02-11",
               description: "Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow  makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.",
               fixed_versions: [
                  "2.7.1",
               ],
               identifier: "CVE-2022-23594",
               identifiers: [
                  "GHSA-9x52-887g-fhc2",
                  "CVE-2022-23594",
               ],
               not_impacted: "All versions before 2.7.0, all versions after 2.7.0",
               package_slug: "pypi/tensorflow-cpu",
               pubdate: "2022-02-09",
               solution: "Upgrade to version 2.7.1 or above.",
               title: "Out-of-bounds Write",
               urls: [
                  "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9x52-887g-fhc2",
                  "https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/ir/importexport",
                  "https://nvd.nist.gov/vuln/detail/CVE-2022-23594",
                  "https://github.com/advisories/GHSA-9x52-887g-fhc2",
               ],
               uuid: "3549d890-9806-40af-ad5d-cee729e1a2dc",
            },
            {
               affected_range: "==2.7.0",
               affected_versions: "Version 2.7.0",
               cvss_v2: "AV:L/AC:L/Au:N/C:N/I:N/A:P",
               cvss_v3: "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
               cwe_ids: [
                  "CWE-1035",
                  "CWE-125",
                  "CWE-787",
                  "CWE-937",
               ],
               date: "2022-02-11",
               description: "Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow  makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.",
               fixed_versions: [
                  "2.7.1",
               ],
               identifier: "CVE-2022-23594",
               identifiers: [
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                  "CVE-2022-23594",
               ],
               not_impacted: "All versions before 2.7.0, all versions after 2.7.0",
               package_slug: "pypi/tensorflow-gpu",
               pubdate: "2022-02-09",
               solution: "Upgrade to version 2.7.1 or above.",
               title: "Out-of-bounds Write",
               urls: [
                  "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9x52-887g-fhc2",
                  "https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/ir/importexport",
                  "https://nvd.nist.gov/vuln/detail/CVE-2022-23594",
                  "https://github.com/advisories/GHSA-9x52-887g-fhc2",
               ],
               uuid: "bf967abd-05a2-41da-bc6b-0719d84d1f7c",
            },
            {
               affected_range: "==2.7.0",
               affected_versions: "Version 2.7.0",
               cvss_v2: "AV:L/AC:L/Au:N/C:N/I:N/A:P",
               cvss_v3: "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
               cwe_ids: [
                  "CWE-1035",
                  "CWE-125",
                  "CWE-937",
               ],
               date: "2022-02-10",
               description: "Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.",
               fixed_versions: [
                  "2.7.1",
               ],
               identifier: "CVE-2022-23594",
               identifiers: [
                  "CVE-2022-23594",
                  "GHSA-9x52-887g-fhc2",
               ],
               not_impacted: "All versions before 2.7.0, all versions after 2.7.0",
               package_slug: "pypi/tensorflow",
               pubdate: "2022-02-04",
               solution: "Upgrade to version 2.7.1 or above.",
               title: "Out-of-bounds Read",
               urls: [
                  "https://nvd.nist.gov/vuln/detail/CVE-2022-23594",
                  "https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/ir/importexport",
                  "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9x52-887g-fhc2",
               ],
               uuid: "d735c73e-0b03-4ae3-82b6-ada24444259f",
            },
         ],
      },
      "nvd.nist.gov": {
         configurations: {
            CVE_data_version: "4.0",
            nodes: [
               {
                  children: [],
                  cpe_match: [
                     {
                        cpe23Uri: "cpe:2.3:a:google:tensorflow:2.7.0:*:*:*:*:*:*:*",
                        cpe_name: [],
                        vulnerable: true,
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            data_type: "CVE",
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            description: {
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                     value: "Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.",
                  },
               ],
            },
            problemtype: {
               problemtype_data: [
                  {
                     description: [
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                        {
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            references: {
               reference_data: [
                  {
                     name: "https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/ir/importexport",
                     refsource: "MISC",
                     tags: [
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                     url: "https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/ir/importexport",
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         },
         impact: {
            baseMetricV2: {
               acInsufInfo: false,
               cvssV2: {
                  accessComplexity: "LOW",
                  accessVector: "LOCAL",
                  authentication: "NONE",
                  availabilityImpact: "PARTIAL",
                  baseScore: 2.1,
                  confidentialityImpact: "NONE",
                  integrityImpact: "NONE",
                  vectorString: "AV:L/AC:L/Au:N/C:N/I:N/A:P",
                  version: "2.0",
               },
               exploitabilityScore: 3.9,
               impactScore: 2.9,
               obtainAllPrivilege: false,
               obtainOtherPrivilege: false,
               obtainUserPrivilege: false,
               severity: "LOW",
               userInteractionRequired: false,
            },
            baseMetricV3: {
               cvssV3: {
                  attackComplexity: "LOW",
                  attackVector: "LOCAL",
                  availabilityImpact: "HIGH",
                  baseScore: 5.5,
                  baseSeverity: "MEDIUM",
                  confidentialityImpact: "NONE",
                  integrityImpact: "NONE",
                  privilegesRequired: "LOW",
                  scope: "UNCHANGED",
                  userInteraction: "NONE",
                  vectorString: "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
                  version: "3.1",
               },
               exploitabilityScore: 1.8,
               impactScore: 3.6,
            },
         },
         lastModifiedDate: "2022-02-10T18:15Z",
         publishedDate: "2022-02-04T23:15Z",
      },
   },
}


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