Division by zero in TFLite's implementation of `DepthwiseConv`
Description
TensorFlow is an end-to-end open source platform for machine learning. The implementation of the DepthwiseConv TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/1a8e885b864c818198a5b2c0cbbeca5a1e833bc8/tensorflow/lite/kernels/depthwise_conv.cc#L287-L288). An attacker can craft a model such that input's fourth dimension would be 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
1cbda3c6b2dbbPrevent divisions by 0
1 file changed · +3 −2
tensorflow/lite/kernels/depthwise_conv.cc+3 −2 modified@@ -285,8 +285,8 @@ TfLiteStatus ComputeDepthMultiplier(TfLiteContext* context, int16* depth_multiplier) { int num_filter_channels = SizeOfDimension(filter, 3); int num_input_channels = SizeOfDimension(input, 3); + TF_LITE_ENSURE(context, num_input_channels != 0); TF_LITE_ENSURE_EQ(context, num_filter_channels % num_input_channels, 0); - *depth_multiplier = num_filter_channels / num_input_channels; return kTfLiteOk; } @@ -455,8 +455,9 @@ TfLiteStatus EvalHybridPerChannel(TfLiteContext* context, TfLiteNode* node, float output_activation_min, output_activation_max; CalculateActivationRange(params->activation, &output_activation_min, &output_activation_max); - const int input_size = NumElements(input) / SizeOfDimension(input, 0); const int batch_size = SizeOfDimension(input, 0); + TF_LITE_ENSURE(context, batch_size != 0); + const int input_size = NumElements(input) / batch_size; TfLiteTensor* input_quantized; TF_LITE_ENSURE_OK(context, GetTemporarySafe(context, node, data->input_quantized_index,
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
8- github.com/advisories/GHSA-rf3h-xgv5-2q39ghsaADVISORY
- nvd.nist.gov/vuln/detail/CVE-2021-29602ghsaADVISORY
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-530.yamlghsaWEB
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-728.yamlghsaWEB
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-239.yamlghsaWEB
- github.com/tensorflow/tensorflow/blob/1a8e885b864c818198a5b2c0cbbeca5a1e833bc8/tensorflow/lite/kernels/depthwise_conv.ccghsaWEB
- github.com/tensorflow/tensorflow/commit/cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0ghsax_refsource_MISCWEB
- github.com/tensorflow/tensorflow/security/advisories/GHSA-rf3h-xgv5-2q39ghsax_refsource_CONFIRMWEB
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