Vulnerability · Published Oct 21, 2020 · Assigned by GitHub_M

CVE-2020-15266Undefined behavior in Tensorflow

Low 3.7

In plain English

A low-severity memory corruption in tensorflow from tensorflow. There are no confirmed reports of exploitation so far. The chance it is exploited in the next 30 days is estimated at 0.9% (higher than 61% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.

Severity (CVSS 3.1)3.7Low

Exploit odds (30 days)0.9%top 38.9% of all CVEs

Exploited in the wildNo reportsnot in CISA KEV

Attack toolingNoneno public tooling known

Official description

In Tensorflow before version 2.4.0, when the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

Affected packages & fixed versions

Ecosystem	Package	Fixed in	Advisory
PyPI	tensorflow	2.4.0	GHSA-xwhf-g6j5-j5gc
PyPI	tensorflow	2.4.0	PYSEC-2020-139
PyPI	tensorflow-cpu	2.4.0	GHSA-xwhf-g6j5-j5gc
PyPI	tensorflow-cpu	2.4.0	PYSEC-2020-296
PyPI	tensorflow-gpu	2.4.0	GHSA-xwhf-g6j5-j5gc
PyPI	tensorflow-gpu	2.4.0	PYSEC-2020-331

Affected products (as reported)

Vendor	Product	Versions
tensorflow	tensorflow	< 2.4.0

Weakness: CWE-119 · Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:L

References

https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xwhf-g6j5-j5gc x_refsource_CONFIRM
https://github.com/tensorflow/tensorflow/issues/42129 x_refsource_CONFIRM
https://github.com/tensorflow/tensorflow/pull/42143/commits/3ade2efec2e90c6237de32a19680caaa3ebc2845 x_refsource_CONFIRM