Vulnerability in Google Tensorflow

CVE-2020-15193

In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of `dlpack.to_dlpack` can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing in a Python object instead of a tensor. The uninitialized memory address is due to a `reinterpret_cast` Since the `PyObject` is a Python object, not a TensorFlow Tensor, the cast to `EagerTensor` fails. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.

Published · last modified .

CVSS v3 metric

CVSS v3 base score 7.1 (High). Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L.

EPSS exploit prediction

EPSS: 0.008 (55.9th percentile), scored .

Very low probability of exploitation in the next 30 days; routine patching cadence is appropriate. 56th percentile — 55.9% of CVEs in the catalogue have a lower EPSS than this one. How to read EPSS.

EPSS trend (30 days)EPSS over the last 30 days for CVE-2020-15193: held from 0.008 to 0.008.

EPSS over last 30 days · oldest: 0.008 · newest: 0.008 · change: 0.000

Affected products

Weakness classification (CWE)

References

Frequently asked questions

What is CVE-2020-15193?
CVE-2020-15193 is a high-severity vulnerability in Google Tensorflow, classified under Use of Uninitialized Resource. CVSS score: 7.1/10. Published 2020-09-25.
How severe is CVE-2020-15193?
High severity. CVSS v3 base score is 7.1 out of 10.