7.1
CVSSv3

CVE-2021-37641

Published: 12/08/2021 Updated: 18/08/2021
CVSS v2 Base Score: 3.6 | Impact Score: 4.9 | Exploitability Score: 3.9
CVSS v3 Base Score: 7.1 | Impact Score: 5.2 | Exploitability Score: 1.8
VMScore: 320
Vector: AV:L/AC:L/Au:N/C:P/I:N/A:P

Vulnerability Summary

TensorFlow is an end-to-end open source platform for machine learning. In affected versions if the arguments to `tf.raw_ops.RaggedGather` don't determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers. The [implementation](github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/ragged_gather_op.cc#L70) directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (i.e., it is not a scalar). Furthermore, the implementation does not check that the list given by `params_nested_splits` is not an empty list of tensors. We have patched the issue in GitHub commit a2b743f6017d7b97af1fe49087ae15f0ac634373. 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.

Vulnerability Trend

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google tensorflow

google tensorflow 2.5.0

google tensorflow 2.6.0

Vendor Advisories

In TensorFlow before version 260 if the arguments to tfraw_opsRaggedGather don't determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers The implementation directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (ie, it is not a scalar) Fur ...