2021-37667 | Google TensorFlow tf.raw_ops.UnicodeEncode uninitialized pointer
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A vulnerability was found in Google TensorFlow up to 2.3.3/2.4.2/2.5.0 (Artificial Intelligence Software) and classified as critical. Using CWE to declare the problem leads to CWE-824. Impacted is confidentiality, integrity, and availability. CVE summarizes:
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.UnicodeEncode`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unicode_ops.cc#L533-L539) reads the first dimension of the `input_splits` tensor before validating that this tensor is not empty. We have patched the issue in GitHub commit 2e0ee46f1a47675152d3d865797a18358881d7a6. The fix will be included in TensorFlow 2.6.0. 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.
The weakness was published 08/13/2021. The advisory is available at github.com. This vulnerability is handled as CVE-2021-37667 since 07/29/2021. The exploitation is known to be easy. The attack may be launched remotely. No form of authentication is required for exploitation. Successful exploitation requires user interaction by the victim. Technical details are known, but there is no available exploit. The structure of the vulnerability defines a possible price range of USD $5k-$25k at the moment (estimation calculated on 08/17/2021).
Upgrading to version 2.3.4, 2.4.3, 2.5.1 or 2.6.0 eliminates this vulnerability. Applying a patch is able to eliminate this problem. The bugfix is ready for download at github.com. The best possible mitigation is suggested to be upgrading to the latest version.
VulDB Meta Base Score: 6.3
VulDB Meta Temp Score: 6.0
Status: Not defined
0-Day Time: 🔒
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