Heap buffer overflow in Tensorflow
Description
Reviewed
Sep 25, 2020
Published to the GitHub Advisory Database
Sep 25, 2020
Published by the National Vulnerability Database
Sep 25, 2020
Last updated
Feb 1, 2023
Impact
The
SparseCountSparseOutputandRaggedCountSparseOutputimplementations don't validate that theweightstensor has the same shape as the data. The check exists forDenseCountSparseOutput, where both tensors are fully specified:https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L110-L117
In the sparse and ragged count weights are still accessed in parallel with the data:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L199-L201
But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights.
Patches
We have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release.
We recommend users to upgrade to TensorFlow 2.3.1.
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 is a variant of GHSA-p5f8-gfw5-33w4
References