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.
EPSS: 0.008 (53.8th percentile) — read the EPSS interpretation.
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.
Affected products
- Google Tensorflow — versions 2.2.0, 2.3.0
- Tensorflow — versions = 2.2.0, = 2.3.0
- Opensuse Leap — versions 15.2
Weakness classification (CWE)
References
- security-advisories@github.com (Third Party Advisory, x_refsource_MISC)
- security-advisories@github.com (x_refsource_CONFIRM, Exploit, Third Party Advisory)
- security-advisories@github.com (Patch, Third Party Advisory, x_refsource_MISC)
- security-advisories@github.com (vendor-advisory, Mailing List, Third Party Advisory, x_refsource_SUSE)
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.