2.1 Low
CVSS2
Attack Vector
LOCAL
Attack Complexity
LOW
Authentication
NONE
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
PARTIAL
AV:L/AC:L/Au:N/C:N/I:N/A:P
5.5 Medium
CVSS3
Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
HIGH
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
5.7 Medium
AI Score
Confidence
High
0.0004 Low
EPSS
Percentile
12.7%
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of tf.raw_ops.QuantizeAndDequantizeV4Grad
is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The implementation uses the axis
value as the size argument to absl::InlinedVector
constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range.
[
{
"product": "tensorflow",
"vendor": "tensorflow",
"versions": [
{
"status": "affected",
"version": ">= 2.5.0, < 2.5.1"
},
{
"status": "affected",
"version": "< 2.4.3"
}
]
}
]
2.1 Low
CVSS2
Attack Vector
LOCAL
Attack Complexity
LOW
Authentication
NONE
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
PARTIAL
AV:L/AC:L/Au:N/C:N/I:N/A:P
5.5 Medium
CVSS3
Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
HIGH
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
5.7 Medium
AI Score
Confidence
High
0.0004 Low
EPSS
Percentile
12.7%