CVE-2021-37651

{"containers": {"cna": {"affected": [{"product": "tensorflow", "vendor": "tensorflow", "versions": [{"status": "affected", "version": ">= 2.5.0, < 2.5.1"}, {"status": "affected", "version": ">= 2.4.0, < 2.4.3"}, {"status": "affected", "version": "< 2.3.4"}]}], "descriptions": [{"lang": "en", "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range."}], "metrics": [{"cvssV3_1": {"attackComplexity": "LOW", "attackVector": "LOCAL", "availabilityImpact": "NONE", "baseScore": 7.1, "baseSeverity": "HIGH", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N", "version": "3.1"}}], "problemTypes": [{"descriptions": [{"cweId": "CWE-125", "description": "CWE-125: Out-of-bounds Read", "lang": "en", "type": "CWE"}]}], "providerMetadata": {"dateUpdated": "2021-08-12T21:00:19.000Z", "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M"}, "references": [{"tags": ["x_refsource_CONFIRM"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hpv4-7p9c-mvfr"}, {"tags": ["x_refsource_MISC"], "url": "https://github.com/tensorflow/tensorflow/commit/0f931751fb20f565c4e94aa6df58d54a003cdb30"}], "source": {"advisory": "GHSA-hpv4-7p9c-mvfr", "discovery": "UNKNOWN"}, "title": "Heap buffer overflow in `FractionalAvgPoolGrad` in TensorFlow", "x_legacyV4Record": {"CVE_data_meta": {"ASSIGNER": "security-advisories@github.com", "ID": "CVE-2021-37651", "STATE": "PUBLIC", "TITLE": "Heap buffer overflow in `FractionalAvgPoolGrad` in TensorFlow"}, "affects": {"vendor": {"vendor_data": [{"product": {"product_data": [{"product_name": "tensorflow", "version": {"version_data": [{"version_value": ">= 2.5.0, < 2.5.1"}, {"version_value": ">= 2.4.0, < 2.4.3"}, {"version_value": "< 2.3.4"}]}}]}, "vendor_name": "tensorflow"}]}}, "data_format": "MITRE", "data_type": "CVE", "data_version": "4.0", "description": {"description_data": [{"lang": "eng", "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range."}]}, "impact": {"cvss": {"attackComplexity": "LOW", "attackVector": "LOCAL", "availabilityImpact": "NONE", "baseScore": 7.1, "baseSeverity": "HIGH", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N", "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-hpv4-7p9c-mvfr", "refsource": "CONFIRM", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hpv4-7p9c-mvfr"}, {"name": "https://github.com/tensorflow/tensorflow/commit/0f931751fb20f565c4e94aa6df58d54a003cdb30", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/commit/0f931751fb20f565c4e94aa6df58d54a003cdb30"}]}, "source": {"advisory": "GHSA-hpv4-7p9c-mvfr", "discovery": "UNKNOWN"}}}, "adp": [{"providerMetadata": {"orgId": "af854a3a-2127-422b-91ae-364da2661108", "shortName": "CVE", "dateUpdated": "2024-08-04T01:23:01.436Z"}, "title": "CVE Program Container", "references": [{"tags": ["x_refsource_CONFIRM", "x_transferred"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hpv4-7p9c-mvfr"}, {"tags": ["x_refsource_MISC", "x_transferred"], "url": "https://github.com/tensorflow/tensorflow/commit/0f931751fb20f565c4e94aa6df58d54a003cdb30"}]}]}, "cveMetadata": {"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "assignerShortName": "GitHub_M", "cveId": "CVE-2021-37651", "datePublished": "2021-08-12T21:00:19.000Z", "dateReserved": "2021-07-29T00:00:00.000Z", "dateUpdated": "2024-08-04T01:23:01.436Z", "state": "PUBLISHED"}, "dataType": "CVE_RECORD", "dataVersion": "5.1"}

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{"affected": [{"affectedData": [{"product": "tensorflow", "vendor": "tensorflow", "versions": [{"status": "affected", "version": ">= 2.5.0, < 2.5.1"}, {"status": "affected", "version": ">= 2.4.0, < 2.4.3"}, {"status": "affected", "version": "< 2.3.4"}]}], "source": "security-advisories@github.com"}], "configurations": [{"nodes": [{"cpeMatch": [{"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "matchCriteriaId": "0F83C081-51CC-415F-A8C0-0A44C75E2CD6", "versionEndExcluding": "2.3.4", "versionStartIncluding": "2.3.0", "vulnerable": true}, {"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "matchCriteriaId": "BD3F2BF8-EBA9-42BF-8F9B-D918B880B15A", "versionEndExcluding": "2.4.3", "versionStartIncluding": "2.4.0", "vulnerable": true}, {"criteria": "cpe:2.3:a:google:tensorflow:2.5.0:*:*:*:*:*:*:*", "matchCriteriaId": "D03E99A7-4E3D-427D-A156-C0713E9FB02A", "vulnerable": true}, {"criteria": "cpe:2.3:a:google:tensorflow:2.6.0:rc0:*:*:*:*:*:*", "matchCriteriaId": "70FA6E48-6C57-40CA-809F-4E3D07CBF348", "vulnerable": true}, {"criteria": "cpe:2.3:a:google:tensorflow:2.6.0:rc1:*:*:*:*:*:*", "matchCriteriaId": "42187561-E491-434D-828C-F36701446634", "vulnerable": true}, {"criteria": "cpe:2.3:a:google:tensorflow:2.6.0:rc2:*:*:*:*:*:*", "matchCriteriaId": "C66B61C8-450A-4C5E-9174-F970D6DEE778", "vulnerable": true}], "negate": false, "operator": "OR"}]}], "cveTags": [], "descriptions": [{"lang": "en", "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range."}, {"lang": "es", "value": "TensorFlow es una plataforma de c\u00f3digo abierto de extremo a extremo para el aprendizaje autom\u00e1tico. En las versiones afectadas, la implementaci\u00f3n \"tf.raw_ops.FractionalAvgPoolGrad\" puede ser enga\u00f1ada para acceder a datos fuera de l\u00edmites de los b\u00faferes asignados a la pila. La [implementaci\u00f3n](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) no comprueba que el tensor de entrada no est\u00e9 vac\u00edo. As\u00ed, el c\u00f3digo construye un \"EigenDoubleMatrixMap\" vac\u00edo y luego accede a este buffer con \u00edndices que est\u00e1n fuera del \u00e1rea vac\u00eda. Hemos parcheado el problema en el commit 0f931751fb20f565c4e94aa6df58d54a003cdb30 de GitHub. La correcci\u00f3n ser\u00e1 incluida en TensorFlow versi\u00f3n 2.6.0. Tambi\u00e9n seleccionaremos este commit en TensorFlow versi\u00f3n 2.5.1, TensorFlow versi\u00f3n 2.4.3, y TensorFlow versi\u00f3n 2.3.4, ya que estos tambi\u00e9n est\u00e1n afectados y todav\u00eda en el rango de soporte."}], "id": "CVE-2021-37651", "lastModified": "2026-06-17T04:00:54.543", "metrics": {"cvssMetricV2": [{"acInsufInfo": false, "baseSeverity": "MEDIUM", "cvssData": {"accessComplexity": "LOW", "accessVector": "LOCAL", "authentication": "NONE", "availabilityImpact": "PARTIAL", "baseScore": 4.6, "confidentialityImpact": "PARTIAL", "integrityImpact": "PARTIAL", "vectorString": "AV:L/AC:L/Au:N/C:P/I:P/A:P", "version": "2.0"}, "exploitabilityScore": 3.9, "impactScore": 6.4, "obtainAllPrivilege": false, "obtainOtherPrivilege": false, "obtainUserPrivilege": false, "source": "nvd@nist.gov", "type": "Primary", "userInteractionRequired": false}], "cvssMetricV31": [{"cvssData": {"attackComplexity": "LOW", "attackVector": "LOCAL", "availabilityImpact": "NONE", "baseScore": 7.1, "baseSeverity": "HIGH", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N", "version": "3.1"}, "exploitabilityScore": 1.8, "impactScore": 5.2, "source": "security-advisories@github.com", "type": "Secondary"}, {"cvssData": {"attackComplexity": "LOW", "attackVector": "LOCAL", "availabilityImpact": "HIGH", "baseScore": 7.8, "baseSeverity": "HIGH", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "version": "3.1"}, "exploitabilityScore": 1.8, "impactScore": 5.9, "source": "nvd@nist.gov", "type": "Primary"}]}, "published": "2021-08-12T21:15:08.170", "references": [{"source": "security-advisories@github.com", "tags": ["Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/commit/0f931751fb20f565c4e94aa6df58d54a003cdb30"}, {"source": "security-advisories@github.com", "tags": ["Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hpv4-7p9c-mvfr"}, {"source": "af854a3a-2127-422b-91ae-364da2661108", "tags": ["Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/commit/0f931751fb20f565c4e94aa6df58d54a003cdb30"}, {"source": "af854a3a-2127-422b-91ae-364da2661108", "tags": ["Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hpv4-7p9c-mvfr"}], "sourceIdentifier": "security-advisories@github.com", "vulnStatus": "Modified", "weaknesses": [{"description": [{"lang": "en", "value": "CWE-125"}], "source": "security-advisories@github.com", "type": "Secondary"}, {"description": [{"lang": "en", "value": "CWE-787"}], "source": "nvd@nist.gov", "type": "Primary"}]}

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