PT-2021-18360 · Google · Tensorflow
Yakun Zhang
+1
·
Published
2021-05-14
·
Updated
2024-03-06
·
CVE-2021-29609
CVSS v3.1
7.8
High
| Vector | AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H |
Name of the Vulnerable Software and Affected Versions
TensorFlow versions prior to 2.5.0
TensorFlow versions 2.1.4 through 2.4.2
Description
Incomplete validation in
SparseAdd results in allowing attackers to exploit undefined behavior, such as dereferencing null pointers and writing outside of bounds of heap allocated data. The implementation has a large set of validation for the two sparse tensor inputs, but does not validate that the tensors are not empty or that the second dimension of * indices matches the size of corresponding * shape. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation.Recommendations
For TensorFlow versions prior to 2.1.4, there is no information about a newer version that contains a fix for this vulnerability.
For TensorFlow versions 2.1.4 through 2.4.2, update to version 2.5.0 or later to resolve the issue.
As a temporary workaround, consider disabling the
SparseAdd function until a patch is available.
Restrict access to the vulnerable SparseAdd module to minimize the risk of exploitation.
Avoid using the * indices and * shape variables in the affected API endpoint until the issue is resolved.Exploit
Memory Corruption
Improper Initialization
NULL Pointer Dereference
Found an issue in the description? Have something to add? Feel free to write us 👾
Related Identifiers
Affected Products
Tensorflow