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Out-of-bounds Read


Severity Medium
Score 5.5/10


Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered. The fix will be included in TensorFlow 2.8.0 and and TensorFlow 2.7.1.

  • LOW
  • NONE
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  • LOW
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  • 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.


Advisory Timeline

  • Published