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Low severityNVD Advisory· Published May 14, 2021· Updated Aug 3, 2024

Division by zero in `Conv3D`

CVE-2021-29517

Description

TensorFlow is an end-to-end open source platform for machine learning. A malicious user could trigger a division by 0 in Conv3D implementation. The implementation(https://github.com/tensorflow/tensorflow/blob/42033603003965bffac51ae171b51801565e002d/tensorflow/core/kernels/conv_ops_3d.cc#L143-L145) does a modulo operation based on user controlled input. Thus, when filter has a 0 as the fifth element, this results in a division by 0. Additionally, if the shape of the two tensors is not valid, an Eigen assertion can be triggered, resulting in a program crash. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Affected packages

Versions sourced from the GitHub Security Advisory.

PackageAffected versionsPatched versions
tensorflowPyPI
< 2.1.42.1.4
tensorflowPyPI
>= 2.2.0, < 2.2.32.2.3
tensorflowPyPI
>= 2.3.0, < 2.3.32.3.3
tensorflowPyPI
>= 2.4.0, < 2.4.22.4.2
tensorflow-cpuPyPI
< 2.1.42.1.4
tensorflow-cpuPyPI
>= 2.2.0, < 2.2.32.2.3
tensorflow-cpuPyPI
>= 2.3.0, < 2.3.32.3.3
tensorflow-cpuPyPI
>= 2.4.0, < 2.4.22.4.2
tensorflow-gpuPyPI
< 2.1.42.1.4
tensorflow-gpuPyPI
>= 2.2.0, < 2.2.32.2.3
tensorflow-gpuPyPI
>= 2.3.0, < 2.3.32.3.3
tensorflow-gpuPyPI
>= 2.4.0, < 2.4.22.4.2

Affected products

1

Patches

1
799f835a3dfa

Fix 2 issues with `Conv3D`.

https://github.com/tensorflow/tensorflowMihai MaruseacApr 19, 2021via ghsa
commit
1 file changed · +7 −0
  • tensorflow/core/kernels/conv_ops_3d.cc+7 −0 modified
    @@ -69,6 +69,11 @@ struct LaunchConvOp<CPUDevice, T> {
                 errors::InvalidArgument("CPU implementation of Conv3D "
                                         "currently only supports dilated rates "
                                         "of 1."));
+    OP_REQUIRES(context, filter.dim_size(3) == input.dim_size(input.dims() - 1),
+                errors::InvalidArgument(
+                    "Number of channels in filter (", filter.dim_size(3),
+                    ") must match last dimension of input (",
+                    input.dim_size(input.dims() - 1), ")"));
     functor::CuboidConvolution<CPUDevice, T>()(
         context->eigen_device<CPUDevice>(), output->tensor<T, 5>(),
         input.tensor<T, 5>(), filter.tensor<T, 5>(), strides[2], strides[1],
@@ -142,6 +147,8 @@ class Conv3DOp : public BinaryOp<T> {
     const int64 filter_depth = filter.dim_size(3);
     const int64 out_depth = filter.dim_size(4);
 
+    OP_REQUIRES(context, filter_depth != 0,
+                errors::InvalidArgument("filter_depth must be non-zero"));
     OP_REQUIRES(context, in_depth % filter_depth == 0,
                 errors::InvalidArgument(
                     "Input depth must be evenly divisible by filter depth: ",

Vulnerability mechanics

Generated by null/stub on May 9, 2026. Inputs: CWE entries + fix-commit diffs from this CVE's patches. Citations validated against bundle.

References

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