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Moderate severityNVD Advisory· Published Sep 16, 2022· Updated Apr 23, 2025

`CHECK` failure in `AvgPoolOp` in Tensorflow

CVE-2022-35941

Description

TensorFlow is an open source platform for machine learning. The AvgPoolOp function takes an argument ksize that must be positive but is not checked. A negative ksize can trigger a CHECK failure and crash the program. We have patched the issue in GitHub commit 3a6ac52664c6c095aa2b114e742b0aa17fdce78f. 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 to this issue.

Affected packages

Versions sourced from the GitHub Security Advisory.

PackageAffected versionsPatched versions
tensorflowPyPI
< 2.7.22.7.2
tensorflowPyPI
>= 2.8.0, < 2.8.12.8.1
tensorflowPyPI
>= 2.9.0, < 2.9.22.9.2
tensorflow-cpuPyPI
< 2.7.22.7.2
tensorflow-cpuPyPI
>= 2.8.0, < 2.8.12.8.1
tensorflow-cpuPyPI
>= 2.9.0, < 2.9.22.9.2
tensorflow-gpuPyPI
< 2.7.22.7.2
tensorflow-gpuPyPI
>= 2.8.0, < 2.8.12.8.1
tensorflow-gpuPyPI
>= 2.9.0, < 2.9.22.9.2

Affected products

1

Patches

1
3a6ac52664c6

Fix security vulnerability with AvgPoolGrad

https://github.com/tensorflow/tensorflowA. Unique TensorFlowerJul 18, 2022via ghsa
commit
2 files changed · +19 −3
  • tensorflow/core/kernels/avgpooling_op.cc+3 −3 modified
    @@ -298,7 +298,7 @@ class AvgPoolingGradOp : public OpKernel {
     TensorShape output_shape;
     auto shape_vec = tensor_in_shape.vec<int32>();
     for (int64_t i = 0; i < tensor_in_shape.NumElements(); ++i) {
-      output_shape.AddDim(shape_vec(i));
+      OP_REQUIRES_OK(context, output_shape.AddDimWithStatus(shape_vec(i)));
     }
     const int64_t in_rows = output_shape.dim_size(1);
     const int64_t in_cols = output_shape.dim_size(2);
@@ -457,7 +457,7 @@ class AvgPoolingGradOp<GPUDevice, T> : public OpKernel {
     TensorShape output_shape;
     auto shape_vec = tensor_in_shape.vec<int32>();
     for (int64_t i = 0; i < tensor_in_shape.NumElements(); ++i) {
-      output_shape.AddDim(shape_vec(i));
+      OP_REQUIRES_OK(context, output_shape.AddDimWithStatus(shape_vec(i)));
     }
 
     if (output_shape.num_elements() == 0) {
@@ -543,7 +543,7 @@ class AvgPoolingGradOpCustomGPUKernel : public OpKernel {
     TensorShape output_shape;
     auto shape_vec = tensor_in_shape.vec<int32>();
     for (int64_t i = 0; i < tensor_in_shape.NumElements(); ++i) {
-      output_shape.AddDim(shape_vec(i));
+      OP_REQUIRES_OK(context, output_shape.AddDimWithStatus(shape_vec(i)));
     }
     if (output_shape.num_elements() == 0) {
       Tensor* output = nullptr;
  • tensorflow/python/kernel_tests/nn_ops/pooling_ops_test.py+16 −0 modified
    @@ -2470,6 +2470,22 @@ def testMaxPoolGradWithArgmaxEagerShapeErrors(self):
               inp, grad, argmax, ksize=[1, 1, 1, 1], strides=[1, 1, 1, 1],
               padding="VALID")
 
+  def testAvgPoolGradInvalidInputShapeRaiseError(self):
+    with self.assertRaises((ValueError, errors_impl.InvalidArgumentError)):
+      with self.cached_session():
+        orig_input_shape = constant_op.constant(
+            -536870912, shape=[4], dtype=dtypes.int32)
+        grad = constant_op.constant(
+            .0890338004362538, shape=[1, 5, 7, 1], dtype=dtypes.float64)
+        t = gen_nn_ops.AvgPoolGrad(
+            orig_input_shape=orig_input_shape,
+            grad=grad,
+            ksize=[1, 2, 2, 1],
+            strides=[1, 2, 2, 1],
+            padding="VALID",
+            data_format="NHWC")
+        self.evaluate(t)
+
 
 def GetMaxPoolFwdTest(input_size, filter_size, strides, padding):

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

6

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