Impact
There is a typo in TensorFlow's SpecializeType which results in heap OOB read/write:
for (int i = 0; i < op_def.output_arg_size(); i++) {
// ...
for (int j = 0; j < t->args_size(); j++) {
auto* arg = t->mutable_args(i);
// ...
}
} Due to a typo, arg is initialized to the ith mutable argument in a loop where the loop index is j. Hence it is possible to assign to arg from outside the vector of arguments. Since this is a mutable proto value, it allows both read and write to outside of bounds data.
Patches
We have patched the issue in GitHub commit 0657c83d08845cc434175934c642299de2c0f042.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
References
Impact
There is a typo in TensorFlow's
SpecializeTypewhich results in heap OOB read/write:Due to a typo,
argis initialized to theith mutable argument in a loop where the loop index isj. Hence it is possible to assign toargfrom outside the vector of arguments. Since this is a mutable proto value, it allows both read and write to outside of bounds data.Patches
We have patched the issue in GitHub commit 0657c83d08845cc434175934c642299de2c0f042.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
References