CVE-2021-37679 (High) detected in tensorflow_gpu-2.0.3-cp37-cp37m-manylinux2010_x86_64.whl, tensorflow-2.2.1-cp37-cp37m-manylinux2010_x86_64.whl

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CVE-2021-37679 - High Severity Vulnerability

Vulnerable Libraries - tensorflow_gpu-2.0.3-cp37-cp37m-manylinux2010_x86_64.whl, tensorflow-2.2.1-cp37-cp37m-manylinux2010_x86_64.whl

tensorflow_gpu-2.0.3-cp37-cp37m-manylinux2010_x86_64.whl

TensorFlow is an open source machine learning framework for everyone.

Library home page: https://files.pythonhosted.org/packages/a0/41/2f957b293fa90c083f8c02d3f05b47494e3ff8d64410ce7ca30200f13739/tensorflow_gpu-2.0.3-cp37-cp37m-manylinux2010_x86_64.whl

Path to dependency file: /examples/notebooks/tf_2_0/requirements.txt

Path to vulnerable library: /examples/notebooks/tf_2_0/requirements.txt

Dependency Hierarchy:

• ❌ tensorflow_gpu-2.0.3-cp37-cp37m-manylinux2010_x86_64.whl (Vulnerable Library)

tensorflow-2.2.1-cp37-cp37m-manylinux2010_x86_64.whl

TensorFlow is an open source machine learning framework for everyone.

Library home page: https://files.pythonhosted.org/packages/d5/09/4c7f73c263f23a568cd7d3fe56f0daa9a1eaadee603e1e05386b862ffa91/tensorflow-2.2.1-cp37-cp37m-manylinux2010_x86_64.whl

Path to dependency file: /examples/notebooks/tf_2_2/requirements.txt

Path to vulnerable library: /examples/notebooks/tf_2_2/requirements.txt

Dependency Hierarchy:

• ❌ tensorflow-2.2.1-cp37-cp37m-manylinux2010_x86_64.whl (Vulnerable Library)

Found in HEAD commit: 4e3aa8327ca6834d417f1c7de964019ba75cc2d1

Vulnerability Details

TensorFlow is an end-to-end open source platform for machine learning. In affected versions it is possible to nest a tf.map_fn within another tf.map_fn call. However, if the input tensor is a RaggedTensor and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The t and z outputs should be identical, however this is not the case. The last row of t contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a Variant tensor to a RaggedTensor. The implementation does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. 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.

Publish Date: 2021-08-12

URL: CVE-2021-37679

CVSS 3 Score Details (7.8)

Base Score Metrics:

• Exploitability Metrics:
  • Attack Vector: Local
  • Attack Complexity: Low
  • Privileges Required: Low
  • User Interaction: None
  • Scope: Unchanged
• Impact Metrics:
  • Confidentiality Impact: High
  • Integrity Impact: High
  • Availability Impact: High

For more information on CVSS3 Scores, click here.

Suggested Fix

Type: Upgrade version

Origin: GHSA-g8wg-cjwc-xhhp

Release Date: 2021-08-12

Fix Resolution: tensorflow - 2.3.4, 2.4.3, 2.5.1, 2.6.0, tensorflow-cpu - 2.3.4, 2.4.3, 2.5.1, 2.6.0, tensorflow-gpu - 2.3.4, 2.4.3, 2.5.1, 2.6.0