CVE-2021-29590: Heap OOB read in TFLite's implementation of `Minimum` or `Maximum`
Impact 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 indexes in both tensors with the same index but does not validate that the index is within bounds:
cc auto maxminfunc = & { outputdata[SubscriptToIndex(outputdesc, indexes)] = op(input1data[SubscriptToIndex(desc1, indexes)], input2data[SubscriptToIndex(desc2, indexes)]); };
Patches We have patched the issue in GitHub commit 953f28dca13c92839ba389c055587cfe6c723578.
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.
For more information Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
Other sources
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/maximumminimum.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.
Affected Software
Remediation
Event History
Frequently Asked Questions
What is the severity of CVE-2021-29590?
CVE-2021-29590 has been assigned a high severity rating due to the potential for arbitrary memory reads.
How do I fix CVE-2021-29590?
To fix CVE-2021-29590, upgrade TensorFlow to version 2.4.2 or later for tensorflow-gpu, tensorflow-cpu, or tensorflow.
What versions are affected by CVE-2021-29590?
CVE-2021-29590 affects TensorFlow versions 2.1.4 up to 2.4.1, including all versions of 2.2.x and 2.3.x.
What causes CVE-2021-29590?
CVE-2021-29590 is caused by improper handling of empty input tensor arguments in the Minimum and Maximum TFLite operators.
Can CVE-2021-29590 lead to data exposure?
Yes, CVE-2021-29590 can lead to data exposure through the reading of out-of-bounds memory.