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

Heap out of bounds read in `RequantizationRange`

CVE-2021-29569

Description

TensorFlow is an end-to-end open source platform for machine learning. The implementation of tf.raw_ops.MaxPoolGradWithArgmax can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the input_min and input_max tensors have at least one element, as it accesses the first element in two arrays. If the tensors are empty, .flat<T>() is an empty object, backed by an empty array. Hence, accesing even the 0th element is a read outside the bounds. 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
ef0c008ee84b

Fix out of bound read in requantization_range_op.cc

https://github.com/tensorflow/tensorflowLaura PakMay 5, 2021via ghsa
commit
1 file changed · +4 −0
  • tensorflow/core/kernels/requantization_range_op.cc+4 −0 modified
    @@ -46,6 +46,10 @@ class RequantizationRangeOp : public OpKernel {
 
   void Compute(OpKernelContext* ctx) override {
     const Tensor& input = ctx->input(0);
+    OP_REQUIRES(ctx, ctx->input(1).NumElements() > 0,
+                errors::InvalidArgument("Input min must not be empty."));
+    OP_REQUIRES(ctx, ctx->input(2).NumElements() > 0,
+                errors::InvalidArgument("Input max must not be empty."));
     const float input_min_float = ctx->input(1).flat<float>()(0);
     const float input_max_float = ctx->input(2).flat<float>()(0);
     Tensor* output_min = nullptr;

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

7

News mentions

0

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