CVE-2021-29612 - 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. An attacker can trigger a heap buffer overflow in Eigen implementation of tf.raw_ops.BandedTriangularSolve. The implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L269-L278) calls ValidateInputTensors for input validation but fails to validate that the two tensors are not empty. Furthermore, since OP_REQUIRES macro only stops execution of current function after setting ctx->status() to a non-OK value, callers of helper functions that use OP_REQUIRES must check value of ctx->status() before continuing. This doesn't happen in this op's implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L219), hence the validation that is present is also not effective. 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-2021-29612
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-2xgj-xhgf-ggjv
Release Date: 2021-05-14
Fix Resolution: tensorflow - 2.5.0, tensorflow-cpu - 2.5.0, tensorflow-gpu - 2.5.0
CVE-2021-29612 - 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. An attacker can trigger a heap buffer overflow in Eigen implementation of
tf.raw_ops.BandedTriangularSolve. The implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L269-L278) callsValidateInputTensorsfor input validation but fails to validate that the two tensors are not empty. Furthermore, sinceOP_REQUIRESmacro only stops execution of current function after settingctx->status()to a non-OK value, callers of helper functions that useOP_REQUIRESmust check value ofctx->status()before continuing. This doesn't happen in this op's implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L219), hence the validation that is present is also not effective. 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-2021-29612
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-2xgj-xhgf-ggjv
Release Date: 2021-05-14
Fix Resolution: tensorflow - 2.5.0, tensorflow-cpu - 2.5.0, tensorflow-gpu - 2.5.0