Описание
OOB read in MatrixTriangularSolve
Impact
The implementation of MatrixTriangularSolve fails to terminate kernel execution if one validation condition fails:
Since OP_REQUIRES only sets ctx->status() to a non-OK value and calls return, this allows malicious attackers to trigger an out of bounds read:
As the two input tensors are empty, the OP_REQUIRES in ValidateInputTensors should fire and interrupt execution. However, given the implementation of OP_REQUIRES, after the in0.dims() >= 2 fails, execution moves to the initialization of the bcast object. This initialization is done with invalid data and results in heap OOB read.
Patches
We have patched the issue in GitHub commit 480641e3599775a8895254ffbc0fc45621334f68.
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.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by Ye Zhang and Yakun Zhang of Baidu X-Team.
Ссылки
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vqw6-72r7-fgw7
- https://nvd.nist.gov/vuln/detail/CVE-2021-29551
- https://github.com/tensorflow/tensorflow/commit/480641e3599775a8895254ffbc0fc45621334f68
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-479.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-677.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-188.yaml
Пакеты
tensorflow
< 2.1.4
2.1.4
tensorflow
>= 2.2.0, < 2.2.3
2.2.3
tensorflow
>= 2.3.0, < 2.3.3
2.3.3
tensorflow
>= 2.4.0, < 2.4.2
2.4.2
tensorflow-cpu
< 2.1.4
2.1.4
tensorflow-cpu
>= 2.2.0, < 2.2.3
2.2.3
tensorflow-cpu
>= 2.3.0, < 2.3.3
2.3.3
tensorflow-cpu
>= 2.4.0, < 2.4.2
2.4.2
tensorflow-gpu
< 2.1.4
2.1.4
tensorflow-gpu
>= 2.2.0, < 2.2.3
2.2.3
tensorflow-gpu
>= 2.3.0, < 2.3.3
2.3.3
tensorflow-gpu
>= 2.4.0, < 2.4.2
2.4.2
Связанные уязвимости
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `MatrixTriangularSolve`(https://github.com/tensorflow/tensorflow/blob/8cae746d8449c7dda5298327353d68613f16e798/tensorflow/core/kernels/linalg/matrix_triangular_solve_op_impl.h#L160-L240) fails to terminate kernel execution if one validation condition fails. 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.
TensorFlow is an end-to-end open source platform for machine learning. ...