FKIE_CVE-2021-37656

Vulnerability from fkie_nvd - Published: 2021-08-12 21:15 - Updated: 2024-11-21 06:15
Severity ?
7.1 (High) - CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H
7.8 (High) - CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Summary
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.RaggedTensorToSparse`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/ragged_tensor_to_sparse_kernel.cc#L30) has an incomplete validation of the splits values: it does not check that they are in increasing order. We have patched the issue in GitHub commit 1071f554dbd09f7e101324d366eec5f4fe5a3ece. 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.
References
security-advisories@github.comhttps://github.com/tensorflow/tensorflow/commit/1071f554dbd09f7e101324d366eec5f4fe5a3ecePatch, Third Party Advisory
security-advisories@github.comhttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-4xfp-4pfp-89wgThird Party Advisory
af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/commit/1071f554dbd09f7e101324d366eec5f4fe5a3ecePatch, Third Party Advisory
af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4xfp-4pfp-89wgThird Party Advisory
Impacted products
Vendor Product Version
google tensorflow *
google tensorflow *
google tensorflow 2.5.0
google tensorflow 2.6.0
google tensorflow 2.6.0
google tensorflow 2.6.0
To clipboard 

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      "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.RaggedTensorToSparse`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/ragged_tensor_to_sparse_kernel.cc#L30) has an incomplete validation of the splits values: it does not check that they are in increasing order. We have patched the issue in GitHub commit 1071f554dbd09f7e101324d366eec5f4fe5a3ece. 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."
    },
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      "lang": "es",
      "value": "TensorFlow es una plataforma de c\u00f3digo abierto de extremo a extremo para el aprendizaje autom\u00e1tico. En las versiones afectadas un atacante puede causar un comportamiento indefinido por medio de la vinculaci\u00f3n de una referencia a un puntero null en \"tf.raw_ops.RaggedTensorToSparse\". La [implementaci\u00f3n](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/ragged_tensor_to_sparse_kernel.cc#L30) presenta una comprobaci\u00f3n incompleta de los valores de separaci\u00f3n: no comprueba que est\u00e9n en orden creciente. Hemos parcheado el problema en el commit 1071f554dbd09f7e101324d366eec5f4fe5a3ece de GitHub. La correcci\u00f3n ser\u00e1 incluida en TensorFlow versi\u00f3n 2.6.0. Tambi\u00e9n seleccionaremos 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 en el rango de soporte."
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  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
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  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
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  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



Detection rules are retrieved from Rulezet.