CVSS2
Attack Vector
NETWORK
Attack Complexity
LOW
Authentication
SINGLE
Confidentiality Impact
PARTIAL
Integrity Impact
PARTIAL
Availability Impact
PARTIAL
AV:N/AC:L/Au:S/C:P/I:P/A:P
CVSS3
Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
HIGH
Integrity Impact
HIGH
Availability Impact
HIGH
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
EPSS
Percentile
72.3%
The implementation of shape inference for Dequantize
is vulnerable to an integer overflow weakness:
import tensorflow as tf
input = tf.constant([1,1],dtype=tf.qint32)
@tf.function
def test():
y = tf.raw_ops.Dequantize(
input=input,
min_range=[1.0],
max_range=[10.0],
mode='MIN_COMBINED',
narrow_range=False,
axis=2**31-1,
dtype=tf.bfloat16)
return y
test()
The axis
argument can be -1
(the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes axis + 1
, an attacker can trigger an integer overflow:
int axis = -1;
Status s = c->GetAttr("axis", &axis);
// ...
if (axis < -1) {
return errors::InvalidArgument("axis should be at least -1, got ",
axis);
}
// ...
if (axis != -1) {
ShapeHandle input;
TF_RETURN_IF_ERROR(c->WithRankAtLeast(c->input(0), axis + 1, &input));
// ...
}
We have patched the issue in GitHub commit b64638ec5ccaa77b7c1eb90958e3d85ce381f91b.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
This vulnerability has been reported by Yu Tian of Qihoo 360 AIVul Team.
Vendor | Product | Version | CPE |
---|---|---|---|
tensorflow | gpu | 2.7.0 | cpe:2.3:a:tensorflow:gpu:2.7.0:*:*:*:*:*:*:* |
tensorflow | gpu | * | cpe:2.3:a:tensorflow:gpu:*:*:*:*:*:*:*:* |
tensorflow | cpu | 2.7.0 | cpe:2.3:a:tensorflow:cpu:2.7.0:*:*:*:*:*:*:* |
tensorflow | cpu | * | cpe:2.3:a:tensorflow:cpu:*:*:*:*:*:*:*:* |
tensorflow | tensorflow | 2.7.0 | cpe:2.3:a:tensorflow:tensorflow:2.7.0:*:*:*:*:*:*:* |
tensorflow | tensorflow | * | cpe:2.3:a:tensorflow:tensorflow:*:*:*:*:*:*:*:* |
github.com/advisories/GHSA-c6fh-56w7-fvjw
github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L3001-L3034
github.com/tensorflow/tensorflow/commit/b64638ec5ccaa77b7c1eb90958e3d85ce381f91b
github.com/tensorflow/tensorflow/security/advisories/GHSA-c6fh-56w7-fvjw
nvd.nist.gov/vuln/detail/CVE-2022-21727
CVSS2
Attack Vector
NETWORK
Attack Complexity
LOW
Authentication
SINGLE
Confidentiality Impact
PARTIAL
Integrity Impact
PARTIAL
Availability Impact
PARTIAL
AV:N/AC:L/Au:S/C:P/I:P/A:P
CVSS3
Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
HIGH
Integrity Impact
HIGH
Availability Impact
HIGH
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
EPSS
Percentile
72.3%