GHSA-2r8p-fg3c-wcj4

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    GHSA-2r8p-fg3c-wcj4

    Published: 25 Aug 2021Last Modified: 8 Jul 2026

    Summary: Heap OOB and CHECK fail in `ResourceGather`

    Details: ### Impact An attacker can trigger a crash via a `CHECK`-fail in debug builds of TensorFlow using `tf.raw_ops.ResourceGather` or a read from outside the bounds of heap allocated data in the same API in a release build: ```python import tensorflow as tf tensor = tf.constant(value=[[1,2],[3,4],[5,6]],shape=(3,2),dtype=tf.uint32) v = tf.Variable(tensor) tf.raw_ops.ResourceGather( resource=v.handle, indices=[0], dtype=tf.uint32, batch_dims=10, validate_indices=False) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L660-L668) does not check that the `batch_dims` value that the user supplies is less than the rank of the input tensor. Since the implementation uses several for loops over the dimensions of `tensor`, this results in reading data from outside the bounds of heap allocated buffer backing the tensor: ```cc // batch_dims_ = > params.dims() (10 > 2) for (int i = 0; i < batch_dims_; ++i) { result_shape.AddDim(params.dim_size(i)); } for (int i = batch_dims_; i < indices.dims(); ++i) { result_shape.AddDim(indices.dim_size(i)); } for (int i = batch_dims_ + 1; i < params.dims(); ++i) { result_shape.AddDim(params.dim_size(i)); } ``` In debug mode, `.dim_size(i)` validates that the argument is less than `.dims()` using a `DCHECK`. But the `DCHECK` is a no-op in release builds. ### Patches We have patched the issue in GitHub commit [bc9c546ce7015c57c2f15c168b3d9201de679a1d](https://github.com/tensorflow/tensorflow/commit/bc9c546ce7015c57c2f15c168b3d9201de679a1d). 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. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

    Affected packages

    Package

    Name: tensorflow

    Purl: pkg:pypi/tensorflow

    Affected ranges

    Type: ECOSYSTEM

    Events:

    Introduced- 0
    Fixed -2.3.4

    Affected versions

    0.12.0
    0.12.1

    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
    GHSA-2r8p-fg3c-wcj4 | CVE-DB