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Out-of-bounds Read

CVE-2020-26271

Severity Low
Score 3.3/10

Summary

TensorFlow before 1.15.5, 2.0.0 through 2.0.3, 2.1.0 through 2.1.2, 2.2.0 through 2.2.1, and 2.3.0 through 2.3.1, under certain cases, allows to access unitialized memory. 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. This also affects tensorflow-cpu and tensorflow-gpu packages. It's fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.

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