CVE-2021-37677

{"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 shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. 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": "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"}}], "problemTypes": [{"descriptions": [{"cweId": "CWE-20", "description": "CWE-20: Improper Input Validation", "lang": "en", "type": "CWE"}]}], "providerMetadata": {"dateUpdated": "2021-08-12T22:35:10.000Z", "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M"}, "references": [{"tags": ["x_refsource_CONFIRM"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qfpc-5pjr-mh26"}, {"tags": ["x_refsource_MISC"], "url": "https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764"}], "source": {"advisory": "GHSA-qfpc-5pjr-mh26", "discovery": "UNKNOWN"}, "title": "Missing validation in shape inference for `Dequantize` in TensorFlow", "x_legacyV4Record": {"CVE_data_meta": {"ASSIGNER": "security-advisories@github.com", "ID": "CVE-2021-37677", "STATE": "PUBLIC", "TITLE": "Missing validation in shape inference for `Dequantize` 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 shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. 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": "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"}}, "problemtype": {"problemtype_data": [{"description": [{"lang": "eng", "value": "CWE-20: Improper Input Validation"}]}]}, "references": {"reference_data": [{"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qfpc-5pjr-mh26", "refsource": "CONFIRM", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qfpc-5pjr-mh26"}, {"name": "https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764"}]}, "source": {"advisory": "GHSA-qfpc-5pjr-mh26", "discovery": "UNKNOWN"}}}, "adp": [{"providerMetadata": {"orgId": "af854a3a-2127-422b-91ae-364da2661108", "shortName": "CVE", "dateUpdated": "2024-08-04T01:23:01.450Z"}, "title": "CVE Program Container", "references": [{"tags": ["x_refsource_CONFIRM", "x_transferred"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qfpc-5pjr-mh26"}, {"tags": ["x_refsource_MISC", "x_transferred"], "url": "https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764"}]}]}, "cveMetadata": {"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "assignerShortName": "GitHub_M", "cveId": "CVE-2021-37677", "datePublished": "2021-08-12T22:35:10.000Z", "dateReserved": "2021-07-29T00:00:00.000Z", "dateUpdated": "2024-08-04T01:23:01.450Z", "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 shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. 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.&#xa0;En las versiones afectadas, el c\u00f3digo de inferencia de forma para \"tf.raw_ops.Dequantize\" presenta una vulnerabilidad que podr\u00eda desencadenar una denegaci\u00f3n de servicio por medio de un error de seguridad si un atacante proporciona argumentos no v\u00e1lidos.&#xa0;La inferencia de forma [implementaci\u00f3n] (https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) usa \"axis\" para seleccionar entre dos valores diferentes para \"minmax_rank \"que luego se usa para recuperar las dimensiones del tensor.&#xa0;Sin embargo, el c\u00f3digo asume que el \"axis\" puede ser \"-1\" o un valor mayor que \"-1\", sin comprobaci\u00f3n para los otros valores.&#xa0;Hemos solucionado el problema en GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764.&#xa0;La correcci\u00f3n ser\u00e1 incluida en TensorFlow versi\u00f3n 2.6.0.&#xa0;Tambi\u00e9n seleccionaremos este commit en TensorFlow versi\u00f3n 2.5."}], "id": "CVE-2021-37677", "lastModified": "2026-06-17T04:00:57.803", "metrics": {"cvssMetricV2": [{"acInsufInfo": false, "baseSeverity": "LOW", "cvssData": {"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, "source": "nvd@nist.gov", "type": "Primary", "userInteractionRequired": false}], "cvssMetricV31": [{"cvssData": {"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, "source": "security-advisories@github.com", "type": "Secondary"}, {"cvssData": {"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, "source": "nvd@nist.gov", "type": "Primary"}]}, "published": "2021-08-12T23:15:08.090", "references": [{"source": "security-advisories@github.com", "tags": ["Patch"], "url": "https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764"}, {"source": "security-advisories@github.com", "tags": ["Vendor Advisory"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qfpc-5pjr-mh26"}, {"source": "af854a3a-2127-422b-91ae-364da2661108", "tags": ["Patch"], "url": "https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764"}, {"source": "af854a3a-2127-422b-91ae-364da2661108", "tags": ["Vendor Advisory"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qfpc-5pjr-mh26"}], "sourceIdentifier": "security-advisories@github.com", "vulnStatus": "Modified", "weaknesses": [{"description": [{"lang": "en", "value": "CWE-20"}], "source": "security-advisories@github.com", "type": "Secondary"}, {"description": [{"lang": "en", "value": "CWE-1284"}], "source": "nvd@nist.gov", "type": "Primary"}]}

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