BIT-tensorflow-2022-35996

    Dashboard / Vulnerabilities / BIT-tensorflow-2022-35996

    BIT-tensorflow-2022-35996

    Published: 6 Mar 2024Last Modified: 8 Sept 2026

    Summary: Floating point exception in `Conv2D` in TensorFlow

    Details: TensorFlow is an open source platform for machine learning. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

    References: https://github.com/tensorflow/tensorflow/commit/611d80db29dd7b0cfb755772c69d60ae5bca05f9, https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q5jv-m6qw-5g37, https://nvd.nist.gov/vuln/detail/CVE-2022-35996

    Affected packages

    Package

    Name: tensorflow

    Purl: pkg:bitnami/tensorflow

    Affected ranges

    Type: SEMVER

    Events:

    Introduced- 0
    Fixed -2.7.2

    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-2022-35996 | CVE-DB