What is GHSA-q8gv-q7wr-9jf8?

GHSA-q8gv-q7wr-9jf8 is a security advisory published by GitHub Security Advisories with Medium severity. Segfault in Tensorflow

Which CVE IDs does GHSA-q8gv-q7wr-9jf8 cover?

GHSA-q8gv-q7wr-9jf8 covers the following CVE IDs: CVE-2020-15204. Each CVE has its own detail page on EchelonGraph Pulse with the synthesized EG score.

What is the CVSS v3 score of GHSA-q8gv-q7wr-9jf8?

GHSA-q8gv-q7wr-9jf8 has a CVSS v3 base score of 5.3, published by GitHub Security Advisories.

Which products are affected by GHSA-q8gv-q7wr-9jf8?

GHSA-q8gv-q7wr-9jf8 affects 15 products, including: pip/tensorflow:\u003c 1.15.4; pip/tensorflow:\u003e= 2.0.0, \u003c 2.0.3; pip/tensorflow:\u003e= 2.1.0, \u003c 2.1.2; pip/tensorflow:= 2.2.0; pip/tensorflow:= 2.3.0; and others — see the full list on the advisory page.

GHSA-q8gv-q7wr-9jf8MediumCVSS 5.3

Segfault in Tensorflow

Vendor

GitHub Security Advisories

Published

September 25, 2020

Last Modified

October 28, 2024

🔗 CVE IDs covered (1)

CVE-2020-15204 →

📋 Description

Impact

In eager mode, TensorFlow does not set the session state. Hence, calling tf.raw_ops.GetSessionHandle or tf.raw_ops.GetSessionHandleV2 results in a null pointer dereference: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/session_ops.cc#L45

In the above snippet, in eager mode, ctx->session_state() returns nullptr. Since code immediately dereferences this, we get a segmentation fault.

Patches

We have patched the issue in 9a133d73ae4b4664d22bd1aa6d654fec13c52ee1 and will release patch releases for all versions between 1.15 and 2.3.

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.

🎯 Affected products15

pip/tensorflow:< 1.15.4
pip/tensorflow:>= 2.0.0, < 2.0.3
pip/tensorflow:>= 2.1.0, < 2.1.2
pip/tensorflow:= 2.2.0
pip/tensorflow:= 2.3.0
pip/tensorflow-cpu:< 1.15.4
pip/tensorflow-cpu:>= 2.0.0, < 2.0.3
pip/tensorflow-cpu:>= 2.1.0, < 2.1.2
pip/tensorflow-cpu:= 2.2.0
pip/tensorflow-cpu:= 2.3.0
pip/tensorflow-gpu:< 1.15.4
pip/tensorflow-gpu:>= 2.0.0, < 2.0.3
pip/tensorflow-gpu:>= 2.1.0, < 2.1.2
pip/tensorflow-gpu:= 2.2.0
pip/tensorflow-gpu:= 2.3.0