CVE-2020-15190: Segfault in Tensorflow
Impact The tf.rawops.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/commonruntime/eager/kernelanddevice.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.
Other sources
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the tf.rawops.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. 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 The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Affected Software
Remediation
Event History
Frequently Asked Questions
What is the severity of CVE-2020-15190?
CVE-2020-15190 is classified as a medium severity vulnerability.
How do I fix CVE-2020-15190?
To remediate CVE-2020-15190, upgrade TensorFlow to version 2.3.1 or later.
Which versions of TensorFlow are affected by CVE-2020-15190?
CVE-2020-15190 affects TensorFlow versions 2.3.0, 2.2.0, 2.1.0, 2.0.0, and all versions up to 1.15.4.
Is CVE-2020-15190 related to TensorFlow GPU versions?
Yes, CVE-2020-15190 impacts both TensorFlow GPU and CPU versions, specifically versions below 2.3.1.
What operation is implicated in CVE-2020-15190?
The vulnerability in CVE-2020-15190 involves the tf.raw_ops.Switch operation in TensorFlow.