CVE-2021-29521

{"containers": {"cna": {"affected": [{"product": "tensorflow", "vendor": "tensorflow", "versions": [{"status": "affected", "version": "< 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. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3."}], "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-131", "description": "CWE-131: Incorrect Calculation of Buffer Size", "lang": "en", "type": "CWE"}]}], "providerMetadata": {"dateUpdated": "2021-05-14T19:35:49.000Z", "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M"}, "references": [{"tags": ["x_refsource_CONFIRM"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm"}, {"tags": ["x_refsource_MISC"], "url": "https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5"}], "source": {"advisory": "GHSA-hr84-fqvp-48mm", "discovery": "UNKNOWN"}, "title": "Segfault in SparseCountSparseOutput", "x_legacyV4Record": {"CVE_data_meta": {"ASSIGNER": "security-advisories@github.com", "ID": "CVE-2021-29521", "STATE": "PUBLIC", "TITLE": "Segfault in SparseCountSparseOutput"}, "affects": {"vendor": {"vendor_data": [{"product": {"product_data": [{"product_name": "tensorflow", "version": {"version_data": [{"version_value": "< 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. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3."}]}, "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-131: Incorrect Calculation of Buffer Size"}]}]}, "references": {"reference_data": [{"name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm", "refsource": "CONFIRM", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm"}, {"name": "https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5"}]}, "source": {"advisory": "GHSA-hr84-fqvp-48mm", "discovery": "UNKNOWN"}}}, "adp": [{"providerMetadata": {"orgId": "af854a3a-2127-422b-91ae-364da2661108", "shortName": "CVE", "dateUpdated": "2024-08-03T22:11:05.725Z"}, "title": "CVE Program Container", "references": [{"tags": ["x_refsource_CONFIRM", "x_transferred"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm"}, {"tags": ["x_refsource_MISC", "x_transferred"], "url": "https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5"}]}]}, "cveMetadata": {"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "assignerShortName": "GitHub_M", "cveId": "CVE-2021-29521", "datePublished": "2021-05-14T19:35:49.000Z", "dateReserved": "2021-03-30T00:00:00.000Z", "dateUpdated": "2024-08-03T22:11:05.725Z", "state": "PUBLISHED"}, "dataType": "CVE_RECORD", "dataVersion": "5.1"}

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{"affected": [{"affectedData": [{"product": "tensorflow", "vendor": "tensorflow", "versions": [{"status": "affected", "version": "< 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": "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. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3."}, {"lang": "es", "value": "TensorFlow es una plataforma de c\u00f3digo abierto de extremo a extremo para el aprendizaje autom\u00e1tico.&#xa0;Especificar una forma densa negativa en \"tf.raw_ops.SparseCountSparseOutput\" resulta en un error de segmentaci\u00f3n que es eliminado de la biblioteca est\u00e1ndar ya que los invariantes \"std::vector\" son rotos.&#xa0;Esto es debido a que la implementaci\u00f3n (https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) asume que el primer elemento de la forma densa es siempre positivo y lo usa para inicializar un \"BatchedMap(T)\" (es decir, \"std::vector (absl::flat_hash_map(int64, T))\" (https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) estructura de datos.&#xa0;Si el tensor de \"shape\" presenta m\u00e1s de un elemento,\"num_batches\" es el primer valor en \"shape\".&#xa0;Asegurarse de que el argumento \"dense_shape\" sea una forma de tensor v\u00e1lida (es decir, que todos los elementos no sean negativos) resuelve este problema.&#xa0;La correcci\u00f3n ser\u00e1 incluida en TensorFlow versi\u00f3n 2.5.0.&#xa0;Tambi\u00e9n seleccionaremos este commit en TensorFlow versi\u00f3n 2.4.2 y TensorFlow versi\u00f3n 2.3.3"}], "id": "CVE-2021-29521", "lastModified": "2026-06-17T03:47:49.623", "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": "2021-05-14T20:15:11.567", "references": [{"source": "security-advisories@github.com", "tags": ["Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5"}, {"source": "security-advisories@github.com", "tags": ["Exploit", "Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm"}, {"source": "af854a3a-2127-422b-91ae-364da2661108", "tags": ["Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5"}, {"source": "af854a3a-2127-422b-91ae-364da2661108", "tags": ["Exploit", "Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm"}], "sourceIdentifier": "security-advisories@github.com", "vulnStatus": "Modified", "weaknesses": [{"description": [{"lang": "en", "value": "CWE-131"}], "source": "security-advisories@github.com", "type": "Secondary"}]}

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