BIT-tensorflow-2022-35967

    Dashboard / Vulnerabilities / BIT-tensorflow-2022-35967

    BIT-tensorflow-2022-35967

    Published: 6 Mar 2024Last Modified: 8 Sept 2026

    Summary: Segfault in `QuantizedAdd` in TensorFlow

    Details: TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. 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/49b3824d83af706df0ad07e4e677d88659756d89, https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6h3-348g-6h5x, https://nvd.nist.gov/vuln/detail/CVE-2022-35967

    Affected packages

    Package

    Name: tensorflow

    Purl: pkg:bitnami/tensorflow

    Affected ranges

    Type: SEMVER

    Events:

    Introduced- 2.7.0
    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-2022-35967 | CVE-DB