BIT-tensorflow-2022-23573

    Dashboard / Vulnerabilities / BIT-tensorflow-2022-23573

    BIT-tensorflow-2022-23573

    Published: 6 Mar 2024Last Modified: 8 Sept 2026

    Summary: Uninitialized variable access in Tensorflow

    Details: Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

    References: https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/assign_op.h#L30-L143, https://github.com/tensorflow/tensorflow/commit/ef1d027be116f25e25bb94a60da491c2cf55bd0b, https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q85f-69q7-55h2, https://nvd.nist.gov/vuln/detail/CVE-2022-23573

    Affected packages

    Package

    Name: tensorflow

    Purl: pkg:bitnami/tensorflow

    Affected ranges

    Type: SEMVER

    Events:

    Introduced- 0
    Fixed -2.5.3

    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-2022-23573 | CVE-DB