CVE-2020-15265

Public Exploit
Segfault in Tensorflow

Description

In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. 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.

Category

5.9
CVSS
Severity: Medium
CVSS 3.1 •
CVSS 2.0 •
EPSS 0.24%
Third-Party Advisory github.com Third-Party Advisory github.com Third-Party Advisory github.com
Affected: tensorflow tensorflow
Published at:
Updated at:

References

Frequently Asked Questions

What is the severity of CVE-2020-15265?
CVE-2020-15265 has been scored as a medium severity vulnerability.
How to fix CVE-2020-15265?
To fix CVE-2020-15265, make sure you are using an up-to-date version of the affected component(s) by checking the vendor release notes. As for now, there are no other specific guidelines available.
Is CVE-2020-15265 being actively exploited in the wild?
It is possible that CVE-2020-15265 is being exploited or will be exploited in a near future based on public information. According to its EPSS score, there is a ~0% probability that this vulnerability will be exploited by malicious actors in the next 30 days.
What software or system is affected by CVE-2020-15265?
CVE-2020-15265 affects tensorflow tensorflow.
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