CVE-2020-15193Use of Uninitialized Resource in Intel Optimization FOR Tensorflow

Severity
7.1HIGHNVD
EPSS
0.2%
top 55.94%
CISA KEV
Not in KEV
Exploit
No known exploits
Timeline
PublishedSep 25

Description

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` fail

CVSS vector

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:LExploitability: 2.8 | Impact: 4.2

Affected Packages4 packages

PyPIintel/optimization_for_tensorflow2.2.02.2.1+4
NVDgoogle/tensorflow2.2.0, 2.3.0+1
CVEListV5tensorflow/tensorflow= 2.2.0, = 2.3.0+1
NVDopensuse/leap15.2

Patches

🔴Vulnerability Details

4
CVEList
Memory corruption in Tensorflow2020-09-25
OSV
Memory corruption in Tensorflow2020-09-25
OSV
CVE-2020-15193: In Tensorflow before versions 22020-09-25
GHSA
Memory corruption in Tensorflow2020-09-25

📋Vendor Advisories

1
Debian
CVE-2020-15193: tensorflow - In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of `dlpack.to_...2020
CVE-2020-15193 — Use of Uninitialized Resource in Intel | cvebase