PYSEC-2021-762

    Dashboard / Vulnerabilities / PYSEC-2021-762

    PYSEC-2021-762

    Published: 12 Aug 2021Last Modified: 6 Dec 2023

    Summary:

    Details: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

    References: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hpv4-7p9c-mvfr, https://github.com/tensorflow/tensorflow/commit/0f931751fb20f565c4e94aa6df58d54a003cdb30

    Affected packages

    Package

    Name: tensorflow-gpu

    Purl: pkg:pypi/tensorflow-gpu

    Affected ranges

    Type: GIT

    Events:

    Introduced- 0
    Fixed -0f931751fb20f565c4e94aa6df58d54a003cdb30

    Affected versions

    2.3.0
    2.3.1
    2.3.2
    2.3.3

    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
    PYSEC-2021-762 | CVE-DB