CVE-2020-26271

{"containers": {"cna": {"affected": [{"product": "tensorflow", "vendor": "tensorflow", "versions": [{"status": "affected", "version": "< 1.15.5"}, {"status": "affected", "version": ">= 2.0.0, < 2.0.4"}, {"status": "affected", "version": ">= 2.1.0, < 2.1.3"}, {"status": "affected", "version": ">= 2.2.0, < 2.2.2"}, {"status": "affected", "version": ">= 2.3.0, < 2.3.2"}]}], "descriptions": [{"lang": "en", "value": "In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input slot of the dst node (given by input_index). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0."}], "metrics": [{"cvssV3_1": {"attackComplexity": "LOW", "attackVector": "LOCAL", "availabilityImpact": "LOW", "baseScore": 4.4, "baseSeverity": "MEDIUM", "confidentialityImpact": "NONE", "integrityImpact": "LOW", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L", "version": "3.1"}}], "problemTypes": [{"descriptions": [{"cweId": "CWE-125", "description": "CWE-125 Out-of-bounds Read", "lang": "en", "type": "CWE"}]}], "providerMetadata": {"dateUpdated": "2020-12-10T22:10:14.000Z", "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "shortName": "GitHub_M"}, "references": [{"tags": ["x_refsource_CONFIRM"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw"}, {"tags": ["x_refsource_MISC"], "url": "https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b"}], "source": {"advisory": "GHSA-q263-fvxm-m5mw", "discovery": "UNKNOWN"}, "title": "Heap out of bounds access in MakeEdge in TensorFlow", "x_legacyV4Record": {"CVE_data_meta": {"ASSIGNER": "security-advisories@github.com", "ID": "CVE-2020-26271", "STATE": "PUBLIC", "TITLE": "Heap out of bounds access in MakeEdge in TensorFlow"}, "affects": {"vendor": {"vendor_data": [{"product": {"product_data": [{"product_name": "tensorflow", "version": {"version_data": [{"version_value": "< 1.15.5"}, {"version_value": ">= 2.0.0, < 2.0.4"}, {"version_value": ">= 2.1.0, < 2.1.3"}, {"version_value": ">= 2.2.0, < 2.2.2"}, {"version_value": ">= 2.3.0, < 2.3.2"}]}}]}, "vendor_name": "tensorflow"}]}}, "data_format": "MITRE", "data_type": "CVE", "data_version": "4.0", "description": {"description_data": [{"lang": "eng", "value": "In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input slot of the dst node (given by input_index). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0."}]}, "impact": {"cvss": {"attackComplexity": "LOW", "attackVector": "LOCAL", "availabilityImpact": "LOW", "baseScore": 4.4, "baseSeverity": "MEDIUM", "confidentialityImpact": "NONE", "integrityImpact": "LOW", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L", "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-q263-fvxm-m5mw", "refsource": "CONFIRM", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw"}, {"name": "https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b", "refsource": "MISC", "url": "https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b"}]}, "source": {"advisory": "GHSA-q263-fvxm-m5mw", "discovery": "UNKNOWN"}}}, "adp": [{"providerMetadata": {"orgId": "af854a3a-2127-422b-91ae-364da2661108", "shortName": "CVE", "dateUpdated": "2024-08-04T15:56:04.342Z"}, "title": "CVE Program Container", "references": [{"tags": ["x_refsource_CONFIRM", "x_transferred"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw"}, {"tags": ["x_refsource_MISC", "x_transferred"], "url": "https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b"}]}]}, "cveMetadata": {"assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa", "assignerShortName": "GitHub_M", "cveId": "CVE-2020-26271", "datePublished": "2020-12-10T22:10:14.000Z", "dateReserved": "2020-10-01T00:00:00.000Z", "dateUpdated": "2024-08-04T15:56:04.342Z", "state": "PUBLISHED"}, "dataType": "CVE_RECORD", "dataVersion": "5.1"}

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{"affected": [{"affectedData": [{"product": "tensorflow", "vendor": "tensorflow", "versions": [{"status": "affected", "version": "< 1.15.5"}, {"status": "affected", "version": ">= 2.0.0, < 2.0.4"}, {"status": "affected", "version": ">= 2.1.0, < 2.1.3"}, {"status": "affected", "version": ">= 2.2.0, < 2.2.2"}, {"status": "affected", "version": ">= 2.3.0, < 2.3.2"}]}], "source": "security-advisories@github.com"}], "configurations": [{"nodes": [{"cpeMatch": [{"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "matchCriteriaId": "CA3A54AC-E0F8-4741-8A80-04EEF746B14B", "versionEndExcluding": "1.15.5", "vulnerable": true}, {"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "matchCriteriaId": "989E4548-7823-436F-A9FE-04158ED41C48", "versionEndExcluding": "2.0.4", "versionStartIncluding": "2.0.0", "vulnerable": true}, {"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "matchCriteriaId": "46417CA8-E666-4E12-B2A8-BB0E97D49BF4", "versionEndExcluding": "2.1.3", "versionStartIncluding": "2.1.0", "vulnerable": true}, {"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "matchCriteriaId": "57B24744-0D81-41E9-9ED0-7296368DEF00", "versionEndExcluding": "2.2.2", "versionStartIncluding": "2.2.0", "vulnerable": true}, {"criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*", "matchCriteriaId": "DBEA56AF-3495-4883-9721-0FA9F08E7F6D", "versionEndExcluding": "2.3.2", "versionStartIncluding": "2.3.0", "vulnerable": true}], "negate": false, "operator": "OR"}]}], "cveTags": [], "descriptions": [{"lang": "en", "value": "In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input slot of the dst node (given by input_index). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0."}, {"lang": "es", "value": "En las versiones afectadas de TensorFlow en determinados casos, cargar un modelo guardado puede resultar en el acceso a la memoria no inicializada mientras se construye el gr\u00e1fico de computaci\u00f3n.&#xa0;La funci\u00f3n MakeEdge crea un per\u00edmetro entre un tensor de salida del nodo src (dado por output_index) y la ranura de entrada del nodo dst (dado por input_index).&#xa0;Esto solo es posible si los tipos de tensores en ambos lados coinciden, por lo que la funci\u00f3n comienza obteniendo los valores de DataType correspondientes y compar\u00e1ndolos para la igualdad.&#xa0;Sin embargo, no se comprueba que los \u00edndices apunten al interior de las matrices en las que indexan.&#xa0;Por lo tanto, esto puede resultar en un acceso a datos fuera de l\u00edmites de los correspondientes arreglos asignados a la pila.&#xa0;En la mayor\u00eda de los escenarios, esto puede manifestarse como un acceso a los datos no inicializados,&#xa0;pero si el \u00edndice apunta lejos de los l\u00edmites de las matrices, esto se puede usar para filtrar direcciones de la biblioteca.&#xa0;Esto es corregido en las versiones 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 y 2.4.0."}], "id": "CVE-2020-26271", "lastModified": "2026-06-17T03:07:58.140", "metrics": {"cvssMetricV2": [{"acInsufInfo": false, "baseSeverity": "LOW", "cvssData": {"accessComplexity": "LOW", "accessVector": "LOCAL", "authentication": "NONE", "availabilityImpact": "NONE", "baseScore": 2.1, "confidentialityImpact": "PARTIAL", "integrityImpact": "NONE", "vectorString": "AV:L/AC:L/Au:N/C:P/I:N/A:N", "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": "LOW", "baseScore": 4.4, "baseSeverity": "MEDIUM", "confidentialityImpact": "NONE", "integrityImpact": "LOW", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L", "version": "3.1"}, "exploitabilityScore": 1.8, "impactScore": 2.5, "source": "security-advisories@github.com", "type": "Secondary"}, {"cvssData": {"attackComplexity": "LOW", "attackVector": "LOCAL", "availabilityImpact": "NONE", "baseScore": 3.3, "baseSeverity": "LOW", "confidentialityImpact": "LOW", "integrityImpact": "NONE", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N", "version": "3.1"}, "exploitabilityScore": 1.8, "impactScore": 1.4, "source": "nvd@nist.gov", "type": "Primary"}]}, "published": "2020-12-10T22:15:12.077", "references": [{"source": "security-advisories@github.com", "tags": ["Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b"}, {"source": "security-advisories@github.com", "tags": ["Exploit", "Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw"}, {"source": "af854a3a-2127-422b-91ae-364da2661108", "tags": ["Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b"}, {"source": "af854a3a-2127-422b-91ae-364da2661108", "tags": ["Exploit", "Patch", "Third Party Advisory"], "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw"}], "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-125"}, {"lang": "en", "value": "CWE-908"}], "source": "nvd@nist.gov", "type": "Primary"}]}

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