CVSS3
Attack Vector
LOCAL
Attack Complexity
HIGH
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
NONE
Integrity Impact
LOW
Availability Impact
HIGH
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:H
EPSS
Percentile
39.4%
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.
[
{
"product": "tensorflow",
"vendor": "tensorflow",
"versions": [
{
"status": "affected",
"version": "< 2.1.4"
},
{
"status": "affected",
"version": ">= 2.2.0, < 2.2.3"
},
{
"status": "affected",
"version": ">= 2.3.0, < 2.3.3"
},
{
"status": "affected",
"version": ">= 2.4.0, < 2.4.2"
}
]
}
]