CVE-2021-29580

{"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. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. 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-908", "description": "CWE-908: Use of Uninitialized Resource", "lang": "en", "type": "CWE"}]}], "providerMetadata": {"dateUpdated": "2021-05-14T19:15:43.000Z", "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M"}, "references": [{"tags": ["x_refsource_CONFIRM"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgp"}, {"tags": ["x_refsource_MISC"], "url": "https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925"}], "source": {"advisory": "GHSA-x8h6-xgqx-jqgp", "discovery": "UNKNOWN"}, "title": "Undefined behavior and `CHECK`-fail in `FractionalMaxPoolGrad`", "x_legacyV4Record": {"CVE_data_meta": {"ASSIGNER": "security-advisories@github.com", "ID": "CVE-2021-29580", "STATE": "PUBLIC", "TITLE": "Undefined behavior and `CHECK`-fail in `FractionalMaxPoolGrad`"}, "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. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. 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-908: Use of Uninitialized Resource"}]}]}, "references": {"reference_data": [{"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgp", "refsource": "CONFIRM", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgp"}, {"name": "https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925"}]}, "source": {"advisory": "GHSA-x8h6-xgqx-jqgp", "discovery": "UNKNOWN"}}}, "adp": [{"providerMetadata": {"orgId": "af854a3a-2127-422b-91ae-364da2661108", "shortName": "CVE", "dateUpdated": "2024-08-03T22:11:06.079Z"}, "title": "CVE Program Container", "references": [{"tags": ["x_refsource_CONFIRM", "x_transferred"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgp"}, {"tags": ["x_refsource_MISC", "x_transferred"], "url": "https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925"}]}]}, "cveMetadata": {"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "assignerShortName": "GitHub_M", "cveId": "CVE-2021-29580", "datePublished": "2021-05-14T19:15:43.000Z", "dateReserved": "2021-03-30T00:00:00.000Z", "dateUpdated": "2024-08-03T22:11:06.079Z", "state": "PUBLISHED"}, "dataType": "CVE_RECORD", "dataVersion": "5.1"}

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{"affected": [{"affectedData": [{"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"}]}], "source": "security-advisories@github.com"}], "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"}]}], "cveTags": [], "descriptions": [{"lang": "en", "value": "TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. 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;La implementaci\u00f3n de \"tf.raw_ops.FractionalMaxPoolGrad\" desencadena un comportamiento indefinido si uno de los tensores de entrada est\u00e1 vac\u00edo.&#xa0;El c\u00f3digo tambi\u00e9n es vulnerable a un ataque de denegaci\u00f3n de servicio, ya que una condici\u00f3n \"CHECK\" se vuelve falsa y aborta el proceso.&#xa0;La implementaci\u00f3n (https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) no comprueba que los tensores de entrada y salida no est\u00e1n vac\u00edos y presentan el mismo rango.&#xa0;Cada una de estas suposiciones no comprobadas es responsable de los problemas anteriores.&#xa0;La correcci\u00f3n ser\u00e1 incluida en TensorFlow versi\u00f3n 2.5.0.&#xa0;Tambi\u00e9n seleccionaremos este compromiso en TensorFlow versi\u00f3n 2.4.2, TensorFlow versi\u00f3n 2.3.3, TensorFlow versi\u00f3n 2.2.3 y TensorFlow versi\u00f3n 2.1.4, ya que estos tambi\u00e9n est\u00e1n afectados y a\u00fan est\u00e1n en el rango admitido"}], "id": "CVE-2021-29580", "lastModified": "2026-06-17T03:47:57.340", "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": "2021-05-14T20:15:14.293", "references": [{"source": "security-advisories@github.com", "tags": ["Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925"}, {"source": "security-advisories@github.com", "tags": ["Exploit", "Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgp"}, {"source": "af854a3a-2127-422b-91ae-364da2661108", "tags": ["Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925"}, {"source": "af854a3a-2127-422b-91ae-364da2661108", "tags": ["Exploit", "Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgp"}], "sourceIdentifier": "security-advisories@github.com", "vulnStatus": "Modified", "weaknesses": [{"description": [{"lang": "en", "value": "CWE-908"}], "source": "security-advisories@github.com", "type": "Secondary"}]}

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