CVE-2020-15266 Undefined behavior in Tensorflow

What is CVE-2020-15266?

CVE-2020-15266 is a low-severity denial of service vulnerability in Google Tensorflow, published on 21 Oct 2020. An attacker can exploit it over the internet without logging in, with no action from the victim.

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.

Weakness: CWE-119

Which versions are affected by CVE-2020-15266?

10 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product.

Products include Google Tensorflow.

How do I fix CVE-2020-15266?

Upgrade tensorflow to 2.4.0 or later.

Upgrade, then put limits on request size, rate and nesting depth so one client cannot exhaust the service. More about Denial of service.

Is CVE-2020-15266 being exploited?

There is no known exploitation of CVE-2020-15266 in the wild and no public exploit code.

Other vulnerabilities in Google Tensorflow

• CVE-2023-25668 TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation Critical 9.8
• CVE-2018-7575 Integer Overflow or Wraparound in Google TensorFlow Critical 9.8
• CVE-2021-37678 Arbitrary code execution due to YAML deserialization Critical 9.3
• CVE-2021-35958 Path traversal in n/a Critical 9.1
• CVE-2020-15202 Integer truncation in Shard API usage Critical 9.0

All Google Tensorflow vulnerabilities

Sources

• CVE record
• NVD
• OSV
• GitHub advisory
• How this page is made

Also known as BIT-tensorflow-2020-15266, GHSA-xwhf-g6j5-j5gc, PYSEC-2020-139, PYSEC-2020-296, PYSEC-2020-331.