CVE-2021-29607 - 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. Incomplete validation in SparseAdd results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_sparse_binary_op_shared.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of *_indices matches the size of corresponding *_shape. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Publish Date: 2021-05-14
URL: CVE-2021-29607
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-gv26-jpj9-c8gq
Release Date: 2021-05-14
Fix Resolution: tensorflow - 2.5.0, tensorflow-cpu - 2.5.0, tensorflow-gpu - 2.5.0
CVE-2021-29607 - High Severity Vulnerability
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-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:
Found in HEAD commit: 4e3aa8327ca6834d417f1c7de964019ba75cc2d1
TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in
SparseAddresults in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_sparse_binary_op_shared.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of*_indicesmatches the size of corresponding*_shape. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.Publish Date: 2021-05-14
URL: CVE-2021-29607
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.Type: Upgrade version
Origin: GHSA-gv26-jpj9-c8gq
Release Date: 2021-05-14
Fix Resolution: tensorflow - 2.5.0, tensorflow-cpu - 2.5.0, tensorflow-gpu - 2.5.0