CVSS2
Attack Vector
NETWORK
Attack Complexity
MEDIUM
Authentication
NONE
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
PARTIAL
AV:N/AC:M/Au:N/C:N/I:N/A:P
CVSS3
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
NONE
Scope
CHANGED
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
LOW
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:N/A:L
EPSS
Percentile
47.1%
In TensorFlow Lite models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/segment_sum.cc#L39-L44
We have patched the issue in 204945b and will release patch releases for all affected versions.
We recommend users to upgrade to TensorFlow 2.2.1, or 2.3.1.
A potential workaround would be to add a custom Verifier
to limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps.
However, if the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.
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 discovered from a variant analysis of GHSA-p2cq-cprg-frvm.
Vendor | Product | Version | CPE |
---|---|---|---|
* | tensorflow-gpu | 2.3.0 | cpe:2.3:a:*:tensorflow-gpu:2.3.0:*:*:*:*:*:*:* |
* | tensorflow-gpu | 2.2.0 | cpe:2.3:a:*:tensorflow-gpu:2.2.0:*:*:*:*:*:*:* |
* | tensorflow-cpu | 2.3.0 | cpe:2.3:a:*:tensorflow-cpu:2.3.0:*:*:*:*:*:*:* |
* | tensorflow-cpu | 2.2.0 | cpe:2.3:a:*:tensorflow-cpu:2.2.0:*:*:*:*:*:*:* |
tensorflow | tensorflow | 2.3.0 | cpe:2.3:a:tensorflow:tensorflow:2.3.0:*:*:*:*:*:*:* |
tensorflow | tensorflow | 2.2.0 | cpe:2.3:a:tensorflow:tensorflow:2.2.0:*:*:*:*:*:*:* |
github.com/advisories/GHSA-hjmq-236j-8m87
github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/segment_sum.cc#L39-L44
github.com/tensorflow/tensorflow/commit/00c7ed7ce81c2126ebc17dfe7073b5c0efd5ec0a
github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a
github.com/tensorflow/tensorflow/commit/a4030d8ba3692c438997c27be2dd95f3d5f54827
github.com/tensorflow/tensorflow/releases/tag/v2.3.1
github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87
nvd.nist.gov/vuln/detail/CVE-2020-15213
CVSS2
Attack Vector
NETWORK
Attack Complexity
MEDIUM
Authentication
NONE
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
PARTIAL
AV:N/AC:M/Au:N/C:N/I:N/A:P
CVSS3
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
NONE
Scope
CHANGED
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
LOW
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:N/A:L
EPSS
Percentile
47.1%