4.6
CVSSv2

CVE-2021-41219

Published: 05/11/2021 Updated: 09/11/2021
CVSS v2 Base Score: 4.6 | Impact Score: 6.4 | Exploitability Score: 3.9
CVSS v3 Base Score: 7.8 | Impact Score: 5.9 | Exploitability Score: 1.8
VMScore: 409
Vector: AV:L/AC:L/Au:N/C:P/I:P/A:P

Vulnerability Summary

TensorFlow is an open source platform for machine learning. In affected versions the code for sparse matrix multiplication is vulnerable to undefined behavior via binding a reference to `nullptr`. This occurs whenever the dimensions of `a` or `b` are 0 or less. In the case on one of these is 0, an empty output tensor should be allocated (to conserve the invariant that output tensors are always allocated when the operation is successful) but nothing should be written to it (that is, we should return early from the kernel implementation). Otherwise, attempts to write to this empty tensor would result in heap OOB access. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Vulnerability Trend

Vulnerable Product Search on Vulmon Subscribe to Product

google tensorflow

google tensorflow 2.6.0

Vendor Advisories

In TensorFlow before version 261, the code for sparse matrix multiplication is vulnerable to undefined behavior via binding a reference to nullptr This occurs whenever the dimensions of a or b are 0 or less In the case on one of these is 0, an empty output tensor should be allocated (to conserve the invariant that output tensors are always allo ...