{"containers": {"cna": {"affected": [{"product": "tensorflow", "vendor": "tensorflow", "versions": [{"status": "affected", "version": "< 2.1.4"}, {"status": "affected", "version": ">= 2.2.0, < 2.2.3"}, {"status": "affected", "version": ">= 2.3.0, < 2.3.3"}, {"status": "affected", "version": ">= 2.4.0, < 2.4.2"}]}], "descriptions": [{"lang": "en", "value": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L289-L295) computes a modulo operation without validating that the divisor is not zero. Since `vector_num_elements` is determined based on input shapes(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L522-L544), a user can trigger scenarios where this quantity is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range."}], "metrics": [{"cvssV3_1": {"attackComplexity": "HIGH", "attackVector": "LOCAL", "availabilityImpact": "LOW", "baseScore": 2.5, "baseSeverity": "LOW", "confidentialityImpact": "NONE", "integrityImpact": "NONE", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L", "version": "3.1"}}], "problemTypes": [{"descriptions": [{"cweId": "CWE-369", "description": "CWE-369: Divide By Zero", "lang": "en", "type": "CWE"}]}], "providerMetadata": {"dateUpdated": "2021-05-14T19:10:41", "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M"}, "references": [{"tags": ["x_refsource_CONFIRM"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8v"}, {"tags": ["x_refsource_MISC"], "url": "https://github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16"}], "source": {"advisory": "GHSA-x83m-p7pv-ch8v", "discovery": "UNKNOWN"}, "title": "Division by 0 in `QuantizedAdd`", "x_legacyV4Record": {"CVE_data_meta": {"ASSIGNER": "security-advisories@github.com", "ID": "CVE-2021-29549", "STATE": "PUBLIC", "TITLE": "Division by 0 in `QuantizedAdd`"}, "affects": {"vendor": {"vendor_data": [{"product": {"product_data": [{"product_name": "tensorflow", "version": {"version_data": [{"version_value": "< 2.1.4"}, {"version_value": ">= 2.2.0, < 2.2.3"}, {"version_value": ">= 2.3.0, < 2.3.3"}, {"version_value": ">= 2.4.0, < 2.4.2"}]}}]}, "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. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L289-L295) computes a modulo operation without validating that the divisor is not zero. Since `vector_num_elements` is determined based on input shapes(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L522-L544), a user can trigger scenarios where this quantity is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range."}]}, "impact": {"cvss": {"attackComplexity": "HIGH", "attackVector": "LOCAL", "availabilityImpact": "LOW", "baseScore": 2.5, "baseSeverity": "LOW", "confidentialityImpact": "NONE", "integrityImpact": "NONE", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L", "version": "3.1"}}, "problemtype": {"problemtype_data": [{"description": [{"lang": "eng", "value": "CWE-369: Divide By Zero"}]}]}, "references": {"reference_data": [{"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8v", "refsource": "CONFIRM", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8v"}, {"name": "https://github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16"}]}, "source": {"advisory": "GHSA-x83m-p7pv-ch8v", "discovery": "UNKNOWN"}}}, "adp": [{"providerMetadata": {"orgId": "af854a3a-2127-422b-91ae-364da2661108", "shortName": "CVE", "dateUpdated": "2024-08-03T22:11:05.522Z"}, "title": "CVE Program Container", "references": [{"tags": ["x_refsource_CONFIRM", "x_transferred"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8v"}, {"tags": ["x_refsource_MISC", "x_transferred"], "url": "https://github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16"}]}]}, "cveMetadata": {"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "assignerShortName": "GitHub_M", "cveId": "CVE-2021-29549", "datePublished": "2021-05-14T19:10:41", "dateReserved": "2021-03-30T00:00:00", "dateUpdated": "2024-08-03T22:11:05.522Z", "state": "PUBLISHED"}, "dataType": "CVE_RECORD", "dataVersion": "5.1"}

{}

{"configurations": [{"nodes": [{"cpeMatch": [{"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "matchCriteriaId": "323ABCCE-24EB-47CC-87F6-48C101477587", "versionEndExcluding": "2.1.4", "vulnerable": true}, {"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "matchCriteriaId": "64ABA90C-0649-4BB0-89C9-83C14BBDCC0F", "versionEndExcluding": "2.2.3", "versionStartIncluding": "2.2.0", "vulnerable": true}, {"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "matchCriteriaId": "0F83E0CF-CBF6-4C24-8683-3E7A5DC95BA9", "versionEndExcluding": "2.3.3", "versionStartIncluding": "2.3.0", "vulnerable": true}, {"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "matchCriteriaId": "8259531B-A8AC-4F8B-B60F-B69DE4767C03", "versionEndExcluding": "2.4.2", "versionStartIncluding": "2.4.0", "vulnerable": true}], "negate": false, "operator": "OR"}]}], "descriptions": [{"lang": "en", "value": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L289-L295) computes a modulo operation without validating that the divisor is not zero. Since `vector_num_elements` is determined based on input shapes(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L522-L544), a user can trigger scenarios where this quantity is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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;Un atacante puede causar una divisi\u00f3n del tiempo de ejecuci\u00f3n por error cero y denegaci\u00f3n de servicio en \"tf.raw_ops.QuantizedBatchNormWithGlobalNormalization\".&#xa0;Esto es debido a que la implementaci\u00f3n (https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L289-L295) calcula una operaci\u00f3n de m\u00f3dulo sin comprobar que el divisor no es cero.&#xa0;Dado que \"vector_num_elements\" se determina en funci\u00f3n de las formas de entrada (https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L522-L544), un usuario puede desencadenar escenarios donde la catnidad es 0. La correcci\u00f3n ser\u00e1 inclu\u00edda en TensorFlow versi\u00f3n 2.5.0.&#xa0;Tambi\u00e9n seleccionaremos este commit en TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2"}], "id": "CVE-2021-29549", "lastModified": "2024-11-21T06:01:21.570", "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": "HIGH", "attackVector": "LOCAL", "availabilityImpact": "LOW", "baseScore": 2.5, "baseSeverity": "LOW", "confidentialityImpact": "NONE", "integrityImpact": "NONE", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L", "version": "3.1"}, "exploitabilityScore": 1.0, "impactScore": 1.4, "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": "2021-05-14T20:15:12.853", "references": [{"source": "security-advisories@github.com", "tags": ["Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16"}, {"source": "security-advisories@github.com", "tags": ["Exploit", "Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8v"}, {"source": "af854a3a-2127-422b-91ae-364da2661108", "tags": ["Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16"}, {"source": "af854a3a-2127-422b-91ae-364da2661108", "tags": ["Exploit", "Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8v"}], "sourceIdentifier": "security-advisories@github.com", "vulnStatus": "Modified", "weaknesses": [{"description": [{"lang": "en", "value": "CWE-369"}], "source": "security-advisories@github.com", "type": "Secondary"}, {"description": [{"lang": "en", "value": "CWE-369"}], "source": "nvd@nist.gov", "type": "Primary"}]}

{}

{}