Division by 0 in `QuantizedAdd`
Description
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in tf.raw_ops.QuantizedBatchNormWithGlobalNormalization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L289-L295) computes a modulo operation without validating that the divisor is not zero. Since vector_num_elements is determined based on input shapes(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L522-L544), a user can trigger scenarios where this quantity is 0. 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.
| Package | Affected versions | Patched versions |
|---|---|---|
tensorflowPyPI | < 2.1.4 | 2.1.4 |
tensorflowPyPI | >= 2.2.0, < 2.2.3 | 2.2.3 |
tensorflowPyPI | >= 2.3.0, < 2.3.3 | 2.3.3 |
tensorflowPyPI | >= 2.4.0, < 2.4.2 | 2.4.2 |
tensorflow-cpuPyPI | < 2.1.4 | 2.1.4 |
tensorflow-cpuPyPI | >= 2.2.0, < 2.2.3 | 2.2.3 |
tensorflow-cpuPyPI | >= 2.3.0, < 2.3.3 | 2.3.3 |
tensorflow-cpuPyPI | >= 2.4.0, < 2.4.2 | 2.4.2 |
tensorflow-gpuPyPI | < 2.1.4 | 2.1.4 |
tensorflow-gpuPyPI | >= 2.2.0, < 2.2.3 | 2.2.3 |
tensorflow-gpuPyPI | >= 2.3.0, < 2.3.3 | 2.3.3 |
tensorflow-gpuPyPI | >= 2.4.0, < 2.4.2 | 2.4.2 |
Affected products
1- Range: < 2.1.4
Patches
1744009c9e5ccValidate work in `QuantizedAdd`, ensure at least one element.
1 file changed · +2 −0
tensorflow/core/kernels/quantized_add_op.cc+2 −0 modified@@ -538,6 +538,8 @@ class QuantizedAddOp : public OpKernel { tensor_min = min_x; tensor_max = max_x; } + OP_REQUIRES(context, vector_num_elements > 0, + errors::InvalidArgument("Must have some elements to add")); VectorTensorAddition<T, Toutput>( vector_data, vector_min, vector_max, vector_num_elements, tensor_data, tensor_min, tensor_max, tensor_num_elements, min_z_value, max_z_value,
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- github.com/advisories/GHSA-x83m-p7pv-ch8vghsaADVISORY
- nvd.nist.gov/vuln/detail/CVE-2021-29549ghsaADVISORY
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-477.yamlghsaWEB
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-675.yamlghsaWEB
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-186.yamlghsaWEB
- github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16ghsax_refsource_MISCWEB
- github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8vghsax_refsource_CONFIRMWEB
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