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

`CHECK` fail in `LRNGrad` in TensorFlow

CVE-2022-35985

Description

TensorFlow is an open source platform for machine learning. If LRNGrad is given an output_image input tensor that is not 4-D, it results in a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bd90b3efab4ec958b228cd7cfe9125be1c0cf255. 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.

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, < 2.9.12.9.1
tensorflow-cpuPyPI
< 2.7.22.7.2
tensorflow-cpuPyPI
>= 2.8.0, < 2.8.12.8.1
tensorflow-cpuPyPI
>= 2.9.0, < 2.9.12.9.1
tensorflow-gpuPyPI
< 2.7.22.7.2
tensorflow-gpuPyPI
>= 2.8.0, < 2.8.12.8.1
tensorflow-gpuPyPI
>= 2.9.0, < 2.9.12.9.1

Affected products

1

Patches

1
bd90b3efab4e

Fix security vulnerability with LRNGradOp

https://github.com/tensorflow/tensorflowSagun BajraJul 13, 2022via ghsa
commit
2 files changed · +39 −1
  • tensorflow/core/kernels/lrn_op.cc+2 −1 modified
    @@ -668,7 +668,8 @@ class LRNGradOp : public OpKernel {
         in_image.dim_size(0) == batch && in_image.dim_size(1) == rows &&
             in_image.dim_size(2) == cols && in_image.dim_size(3) == depth &&
             out_image.dim_size(0) == batch && out_image.dim_size(1) == rows &&
-            out_image.dim_size(2) == cols && out_image.dim_size(3) == depth,
+            out_image.dim_size(2) == cols && out_image.dim_size(3) == depth &&
+            out_image.dims() == 4,
         errors::InvalidArgument(
             "input_grads, input_image, and out_image should have the same "
             "shape"));
  • tensorflow/python/kernel_tests/nn_ops/lrn_op_test.py+37 −0 modified
    @@ -20,11 +20,13 @@
 
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import errors_impl
 from tensorflow.python.framework import test_util
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import gradient_checker
 from tensorflow.python.ops import gradients_impl
 from tensorflow.python.ops import nn
+from tensorflow.python.ops import random_ops
 import tensorflow.python.ops.nn_grad  # pylint: disable=unused-import
 from tensorflow.python.platform import test
 
@@ -111,6 +113,41 @@ def testGradientsZeroInput(self):
     self.assertAllClose(r, expected)
     self.assertShapeEqual(expected, grad)
 
+  @test_util.run_in_graph_and_eager_modes
+  def testIncompatibleInputAndOutputImageShapes(self):
+    depth_radius = 1
+    bias = 1.59018219
+    alpha = 0.117728651
+    beta = 0.404427052
+    input_grads = random_ops.random_uniform(
+        shape=[4, 4, 4, 4],
+        minval=-10000,
+        maxval=10000,
+        dtype=dtypes.float32,
+        seed=-2033)
+    input_image = random_ops.random_uniform(
+        shape=[4, 4, 4, 4],
+        minval=-10000,
+        maxval=10000,
+        dtype=dtypes.float32,
+        seed=-2033)
+    invalid_output_image = random_ops.random_uniform(
+        shape=[4, 4, 4, 4, 4, 4],
+        minval=-10000,
+        maxval=10000,
+        dtype=dtypes.float32,
+        seed=-2033)
+    with self.assertRaises((ValueError, errors_impl.InvalidArgumentError)):
+      self.evaluate(
+          nn.lrn_grad(
+              input_grads=input_grads,
+              input_image=input_image,
+              output_image=invalid_output_image,
+              depth_radius=depth_radius,
+              bias=bias,
+              alpha=alpha,
+              beta=beta))
+
   def _RunAndVerifyGradients(self, dtype):
     with self.cached_session():
       # random shape

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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