CVE-2021-37647 (GCVE-0-2021-37647)

Vulnerability from cvelistv5 – Published: 2021-08-12 18:10 – Updated: 2024-08-04 01:23
VLAI
Title
Null pointer dereference in `SparseTensorSliceDataset` in TensorFlow
Summary
TensorFlow is an end-to-end open source platform for machine learning. When a user does not supply arguments that determine a valid sparse tensor, `tf.raw_ops.SparseTensorSliceDataset` implementation can be made to dereference a null pointer. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L240-L251) has some argument validation but fails to consider the case when either `indices` or `values` are provided for an empty sparse tensor when the other is not. If `indices` is empty, then [code that performs validation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L260-L261) (i.e., checking that the indices are monotonically increasing) results in a null pointer dereference. If `indices` as provided by the user is empty, then `indices` in the C++ code above is backed by an empty `std::vector`, hence calling `indices->dim_size(0)` results in null pointer dereferencing (same as calling `std::vector::at()` on an empty vector). We have patched the issue in GitHub commit 02cc160e29d20631de3859c6653184e3f876b9d7. 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.
Severity
7.7 (High)
CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H
CWE
  • CWE-476 - NULL Pointer Dereference
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.5.0, < 2.5.1
Affected: >= 2.4.0, < 2.4.3
Affected: < 2.3.4
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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. Cuando un usuario no suministra argumentos que determinen un tensor disperso v\u00e1lido, la implementaci\u00f3n \\\"tf.raw_ops.SparseTensorSliceDataset\\\" puede hacerse para derivar un puntero null. La [implementaci\u00f3n](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L240-L251) presenta alguna comprobaci\u00f3n de argumentos, pero no considera el caso en el que o bien \\\"indices\\\" o bien \\\"values\\\" se proporcionan para un tensor disperso vac\u00edo cuando el otro no lo est\u00e1. Si \\\"indices\\\" est\u00e1 vac\u00edo, entonces [c\u00f3digo que lleva a cabo la comprobaci\u00f3n](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L260-L261) (es decir, la comprobaci\u00f3n de que los \u00edndices son monot\u00f3nicamente crecientes) resulta en una desreferencia de puntero null. Si \\\"indices\\\" tal y como lo proporciona el usuario est\u00e1 vac\u00edo, entonces \\\"indices\\\" en el c\u00f3digo C++ anterior est\u00e1 respaldado por un \\\"std::vector\u0027 vac\u00edo, por lo que llamar a \\\"indices-)dim_size(0)\\\" resulta en una desreferencia de puntero null (igual que llamar a \\\"std::vector::at()\\\" en un vector vac\u00edo). Hemos parcheado el problema en el commit de GitHub 02cc160e29d20631de3859c6653184e3f876b9d7. La correcci\u00f3n se incluir\u00e1 en TensorFlow versi\u00f3n 2.6.0. Tambi\u00e9n se incluir\u00e1 este commit en TensorFlow versi\u00f3n 2.5.1, TensorFlow versi\u00f3n 2.4.3 y TensorFlow versi\u00f3n 2.3.4, ya que estos tambi\u00e9n est\u00e1n afectados y todav\u00eda est\u00e1n en el rango de soporte.\"}],\"metrics\":{\"cvssMetricV31\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Secondary\",\"cvssData\":{\"version\":\"3.1\",\"vectorString\":\"CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H\",\"baseScore\":7.7,\"baseSeverity\":\"HIGH\",\"attackVector\":\"LOCAL\",\"attackComplexity\":\"LOW\",\"privilegesRequired\":\"NONE\",\"userInteraction\":\"NONE\",\"scope\":\"UNCHANGED\",\"confidentialityImpact\":\"NONE\",\"integrityImpact\":\"HIGH\",\"availabilityImpact\":\"HIGH\"},\"exploitabilityScore\":2.5,\"impactScore\":5.2},{\"source\":\"nvd@nist.gov\",\"type\":\"Primary\",\"cvssData\":{\"version\":\"3.1\",\"vectorString\":\"CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H\",\"baseScore\":5.5,\"baseSeverity\":\"MEDIUM\",\"attackVector\":\"LOCAL\",\"attackComplexity\":\"LOW\",\"privilegesRequired\":\"LOW\",\"userInteraction\":\"NONE\",\"scope\":\"UNCHANGED\",\"confidentialityImpact\":\"NONE\",\"integrityImpact\":\"NONE\",\"availabilityImpact\":\"HIGH\"},\"exploitabilityScore\":1.8,\"impactScore\":3.6}],\"cvssMetricV2\":[{\"source\":\"nvd@nist.gov\",\"type\":\"Primary\",\"cvssData\":{\"version\":\"2.0\",\"vectorString\":\"AV:L/AC:L/Au:N/C:N/I:N/A:P\",\"baseScore\":2.1,\"accessVector\":\"LOCAL\",\"accessComplexity\":\"LOW\",\"authentication\":\"NONE\",\"confidentialityImpact\":\"NONE\",\"integrityImpact\":\"NONE\",\"availabilityImpact\":\"PARTIAL\"},\"baseSeverity\":\"LOW\",\"exploitabilityScore\":3.9,\"impactScore\":2.9,\"acInsufInfo\":false,\"obtainAllPrivilege\":false,\"obtainUserPrivilege\":false,\"obtainOtherPrivilege\":false,\"userInteractionRequired\":false}]},\"weaknesses\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Primary\",\"description\":[{\"lang\":\"en\",\"value\":\"CWE-476\"}]}],\"configurations\":[{\"nodes\":[{\"operator\":\"OR\",\"negate\":false,\"cpeMatch\":[{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*\",\"versionStartIncluding\":\"2.3.0\",\"versionEndExcluding\":\"2.3.4\",\"matchCriteriaId\":\"0F83C081-51CC-415F-A8C0-0A44C75E2CD6\"},{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*\",\"versionStartIncluding\":\"2.4.0\",\"versionEndExcluding\":\"2.4.3\",\"matchCriteriaId\":\"BD3F2BF8-EBA9-42BF-8F9B-D918B880B15A\"},{\"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\"}]}]}],\"references\":[{\"url\":\"https://github.com/tensorflow/tensorflow/commit/02cc160e29d20631de3859c6653184e3f876b9d7\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c5x2-p679-95wc\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/commit/02cc160e29d20631de3859c6653184e3f876b9d7\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c5x2-p679-95wc\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Third Party Advisory\"]}]}}",
    "redhat_vex": {
      "current_release_date": "2026-03-27T13:45:04+00:00",
      "cve": "CVE-2021-37647",
      "id": "CVE-2021-37647",
      "initial_release_date": "2021-01-01T00:00:00+00:00",
      "product_status:known_not_affected": "1",
      "source": "Red Hat CSAF VEX",
      "status": "final",
      "title": "Null pointer dereference in `SparseTensorSliceDataset` in TensorFlow",
      "url": "https://security.access.redhat.com/data/csaf/v2/vex/2021/cve-2021-37647.json",
      "version": "3"
    }
  }
}