LOW · 3.7

CVE-2020-15266

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. Attem...

Vulnerability 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.

CVSS Score

3.7

LOW

CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:L
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality
NONE
Integrity
NONE
Availability
LOW

Affected Products

VendorProductVersions
GoogleTensorflow< 2.4.0

Related Weaknesses (CWE)

References

FAQ

What is CVE-2020-15266?

CVE-2020-15266 is a vulnerability with a CVSS score of 3.7 (LOW). 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. Attem...

How severe is CVE-2020-15266?

CVE-2020-15266 has been rated LOW with a CVSS base score of 3.7/10. Review the CVSS metrics above for detailed severity breakdown.

Is there a patch for CVE-2020-15266?

Check the references section above for vendor advisories and patch information. Affected products include: Google Tensorflow.