BIT-tensorflow-2020-15193

    Dashboard / Vulnerabilities / BIT-tensorflow-2020-15193

    BIT-tensorflow-2020-15193

    Published: 6 Mar 2024Last Modified: 8 Sept 2026

    Summary: Memory corruption in Tensorflow

    Details: 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.

    Affected packages

    Package

    Name: tensorflow

    Purl: pkg:bitnami/tensorflow

    Affected ranges

    Type: SEMVER

    Events:

    Introduced- 2.2.0
    Fixed -2.2.1

    Affected versions

    Common Vulnerability Scoring System

    Attack Vector
    Network
    Adjacent
    Local
    Physical
    Privileges Required
    None
    Low
    High
    User Interaction
    None
    Required
    Scope
    Unchanged
    Changed
    Confidentiality
    None
    Low
    High
    Integrity
    None
    Low
    High
    Availability
    None
    Low
    High
    BIT-tensorflow-2020-15193 | CVE-DB