#VU49329 Use of uninitialized resource in TensorFlow - CVE-2020-26271
Published: December 11, 2020 / Updated: January 7, 2021
TensorFlow
TensorFlow
Description
The vulnerability allows a local user to gain access to sensitive information.
The vulnerability exists due to usage of uninitialized resources. Under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input slot of the dst node (given by input_index). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library.
Remediation
External links
- https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.2
- https://github.com/tensorflow/tensorflow/releases/tag/v2.2.2
- https://github.com/tensorflow/tensorflow/releases/tag/v2.1.3
- https://github.com/tensorflow/tensorflow/releases/tag/v2.0.4
- https://github.com/tensorflow/tensorflow/releases/tag/v1.15.5