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Out-of-bounds Read

CVE-2021-37672

Medium
5.5/10

Summary

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `tf.raw_ops.SdcaOptimizerV2`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/sdca_internal.cc#L320-L353) does not check that the length of `example_labels` is the same as the number of examples. We have patched the issue in GitHub commit a4e138660270e7599793fa438cd7b2fc2ce215a6. The fix will be included in TensorFlow 2.6.0-rc2. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

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

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