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Out-of-bounds Read

CVE-2021-29590

High
7.1/10

Summary

TensorFlow is an end-to-end open source platform for machine learning. The implementations of the `Minimum` and `Maximum` TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. 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.

  • LOW
  • LOCAL
  • NONE
  • UNCHANGED
  • NONE
  • LOW
  • HIGH
  • HIGH

CWE-125 - Out-of-Bounds Read

Out-of-bounds read is a vulnerability that allows access to memory beyond the authorized accessible location. Such a vulnerability compromises the confidentiality of the trusted environment in the application and enables an attacker to launch further attacks by leveraging the exposed information.

References

Advisory Timeline

  • Published