CVE-2020-15193 Memory corruption in Tensorflow

2020-09-2518:40:51

CWE-908

GitHub_M

www.cve.org

7.1 High

CVSS3

Attack Vector

NETWORK

Attack Complexity

LOW

Privileges Required

LOW

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

NONE

Integrity Impact

HIGH

Availability Impact

LOW

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L

6.9 Medium

AI Score

Confidence

High

0.002 Low

EPSS

Percentile

51.5%

JSON

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.

CNA Affected

[
  {
    "product": "tensorflow",
    "vendor": "tensorflow",
    "versions": [
      {
        "status": "affected",
        "version": "= 2.2.0"
      },
      {
        "status": "affected",
        "version": "= 2.3.0"
      }
    ]
  }
]