Vulnerability CVE-2021-29607


Published: 2021-05-14

Description:
TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_sparse_binary_op_shared.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), 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. 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.

Type:

CWE-754

CVSS2 => (AV:L/AC:L/Au:N/C:P/I:P/A:P)

CVSS Base Score
Impact Subscore
Exploitability Subscore
4.6/10
6.4/10
3.9/10
Exploit range
Attack complexity
Authentication
Local
Low
No required
Confidentiality impact
Integrity impact
Availability impact
Partial
Partial
Partial
Affected software
Google -> Tensorflow 

 References:
https://github.com/tensorflow/tensorflow/commit/ba6822bd7b7324ba201a28b2f278c29a98edbef2
https://github.com/tensorflow/tensorflow/commit/f6fde895ef9c77d848061c0517f19d0ec2682f3a
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gv26-jpj9-c8gq

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