Skip to content

Segfault in Tensorflow

Moderate severity GitHub Reviewed Published Sep 24, 2020 in tensorflow/tensorflow • Updated Feb 1, 2023

Package

pip tensorflow (pip)

Affected versions

< 1.15.4
>= 2.0.0, < 2.0.3
>= 2.1.0, < 2.1.2
= 2.2.0
= 2.3.0

Patched versions

1.15.4
2.0.3
2.1.2
2.2.1
2.3.1
pip tensorflow-cpu (pip)
< 1.15.4
>= 2.0.0, < 2.0.3
>= 2.1.0, < 2.1.2
= 2.2.0
= 2.3.0
1.15.4
2.0.3
2.1.2
2.2.1
2.3.1
pip tensorflow-gpu (pip)
< 1.15.4
>= 2.0.0, < 2.0.3
>= 2.1.0, < 2.1.2
= 2.2.0
= 2.3.0
1.15.4
2.0.3
2.1.2
2.2.1
2.3.1

Description

Impact

The tf.raw_ops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor.

However, the eager runtime traverses all tensors in the output:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/common_runtime/eager/kernel_and_device.cc#L308-L313

Since only one of the tensors is defined, the other one is nullptr, hence we are binding a reference to nullptr. This is undefined behavior and reported as an error if compiling with -fsanitize=null. In this case, this results in a segmentation fault

Patches

We have patched the issue in da8558533d925694483d2c136a9220d6d49d843c and will release a patch release for all affected versions.

We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

References

@mihaimaruseac mihaimaruseac published to tensorflow/tensorflow Sep 24, 2020
Reviewed Sep 25, 2020
Published to the GitHub Advisory Database Sep 25, 2020
Published by the National Vulnerability Database Sep 25, 2020
Last updated Feb 1, 2023

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v3 base metrics

Attack vector
Network
Attack complexity
Low
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
Low

CVSS v3 base metrics

Attack vector: More severe the more the remote (logically and physically) an attacker can be in order to exploit the vulnerability.
Attack complexity: More severe for the least complex attacks.
Privileges required: More severe if no privileges are required.
User interaction: More severe when no user interaction is required.
Scope: More severe when a scope change occurs, e.g. one vulnerable component impacts resources in components beyond its security scope.
Confidentiality: More severe when loss of data confidentiality is highest, measuring the level of data access available to an unauthorized user.
Integrity: More severe when loss of data integrity is the highest, measuring the consequence of data modification possible by an unauthorized user.
Availability: More severe when the loss of impacted component availability is highest.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L

EPSS score

0.233%
(61st percentile)

Weaknesses

CVE ID

CVE-2020-15190

GHSA ID

GHSA-4g9f-63rx-5cw4

Source code

Loading Checking history
See something to contribute? Suggest improvements for this vulnerability.