CWE-369
Divide By Zero
The product divides a value by zero.
CVE-2021-29549 (GCVE-0-2021-29549)
Vulnerability from cvelistv5 – Published: 2021-05-14 19:10 – Updated: 2024-08-03 22:11
VLAI
Title
Division by 0 in `QuantizedAdd`
Summary
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.
Severity
CWE
- CWE-369 - Divide By Zero
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/tensorflow/tensorflow/security… | x_refsource_CONFIRM |
| https://github.com/tensorflow/tensorflow/commit/7… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| tensorflow | tensorflow |
Affected:
< 2.1.4
Affected: >= 2.2.0, < 2.2.3 Affected: >= 2.3.0, < 2.3.3 Affected: >= 2.4.0, < 2.4.2 |
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CVE-2021-29550 (GCVE-0-2021-29550)
Vulnerability from cvelistv5 – Published: 2021-05-14 19:10 – Updated: 2024-08-03 22:11
VLAI
Title
Division by 0 in `FractionalAvgPool`
Summary
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.FractionalAvgPool`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user controls the values of `input_size[i]` and `pooling_ratio_[i]` (via the `value.shape()` and `pooling_ratio` arguments). If the value in `input_size[i]` is smaller than the `pooling_ratio_[i]`, then the floor operation results in `output_size[i]` being 0. The `DCHECK_GT` line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to `GeneratePoolingSequence`(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108). There, the first computation is a division in a modulo operation. Since `output_length` can be 0, this results in runtime crashing. 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.
Severity
CWE
- CWE-369 - Divide By Zero
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/tensorflow/tensorflow/security… | x_refsource_CONFIRM |
| https://github.com/tensorflow/tensorflow/commit/5… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| tensorflow | tensorflow |
Affected:
< 2.1.4
Affected: >= 2.2.0, < 2.2.3 Affected: >= 2.3.0, < 2.3.3 Affected: >= 2.4.0, < 2.4.2 |
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CVE-2021-29554 (GCVE-0-2021-29554)
Vulnerability from cvelistv5 – Published: 2021-05-14 19:10 – Updated: 2024-08-03 22:11
VLAI
Title
Division by 0 in `DenseCountSparseOutput`
Summary
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division. Since `data` is given by the `values` argument, `num_batch_elements` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected.
Severity
CWE
- CWE-369 - Divide By Zero
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/tensorflow/tensorflow/security… | x_refsource_CONFIRM |
| https://github.com/tensorflow/tensorflow/commit/d… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| tensorflow | tensorflow |
Affected:
< 2.3.3
Affected: >= 2.4.0, < 2.4.2 |
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CVE-2021-29555 (GCVE-0-2021-29555)
Vulnerability from cvelistv5 – Published: 2021-05-14 19:17 – Updated: 2024-08-03 22:11
VLAI
Title
Division by 0 in `FusedBatchNorm`
Summary
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.FusedBatchNorm`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/828f346274841fa7505f7020e88ca36c22e557ab/tensorflow/core/kernels/fused_batch_norm_op.cc#L295-L297) performs a division based on the last dimension of the `x` tensor. Since this is controlled by the user, an attacker can trigger a denial of service. 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.
Severity
CWE
- CWE-369 - Divide By Zero
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/tensorflow/tensorflow/security… | x_refsource_CONFIRM |
| https://github.com/tensorflow/tensorflow/commit/1… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| tensorflow | tensorflow |
Affected:
< 2.1.4
Affected: >= 2.2.0, < 2.2.3 Affected: >= 2.3.0, < 2.3.3 Affected: >= 2.4.0, < 2.4.2 |
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CVE-2021-29556 (GCVE-0-2021-29556)
Vulnerability from cvelistv5 – Published: 2021-05-14 19:17 – Updated: 2024-08-03 22:11
VLAI
Title
Division by 0 in `Reverse`
Summary
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.Reverse`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/36229ea9e9451dac14a8b1f4711c435a1d84a594/tensorflow/core/kernels/reverse_op.cc#L75-L76) performs a division based on the first dimension of the tensor argument. 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.
Severity
CWE
- CWE-369 - Divide By Zero
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/tensorflow/tensorflow/security… | x_refsource_CONFIRM |
| https://github.com/tensorflow/tensorflow/commit/4… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| tensorflow | tensorflow |
Affected:
< 2.1.4
Affected: >= 2.2.0, < 2.2.3 Affected: >= 2.3.0, < 2.3.3 Affected: >= 2.4.0, < 2.4.2 |
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CVE-2021-29557 (GCVE-0-2021-29557)
Vulnerability from cvelistv5 – Published: 2021-05-14 19:17 – Updated: 2024-08-03 22:11
VLAI
Title
Division by 0 in `SparseMatMul`
Summary
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.SparseMatMul`. The division by 0 occurs deep in Eigen code because the `b` tensor is empty. 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.
Severity
CWE
- CWE-369 - Divide By Zero
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/tensorflow/tensorflow/security… | x_refsource_CONFIRM |
| https://github.com/tensorflow/tensorflow/commit/7… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| tensorflow | tensorflow |
Affected:
< 2.1.4
Affected: >= 2.2.0, < 2.2.3 Affected: >= 2.3.0, < 2.3.3 Affected: >= 2.4.0, < 2.4.2 |
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CVE-2021-29573 (GCVE-0-2021-29573)
Vulnerability from cvelistv5 – Published: 2021-05-14 19:16 – Updated: 2024-08-03 22:11
VLAI
Title
Division by 0 in `MaxPoolGradWithArgmax`
Summary
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` is vulnerable to a division by 0. The implementation(https://github.com/tensorflow/tensorflow/blob/279bab6efa22752a2827621b7edb56a730233bd8/tensorflow/core/kernels/maxpooling_op.cc#L1033-L1034) fails to validate that the batch dimension of the tensor is non-zero, before dividing by this quantity. 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.
Severity
CWE
- CWE-369 - Divide By Zero
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/tensorflow/tensorflow/security… | x_refsource_CONFIRM |
| https://github.com/tensorflow/tensorflow/commit/3… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| tensorflow | tensorflow |
Affected:
< 2.1.4
Affected: >= 2.2.0, < 2.2.3 Affected: >= 2.3.0, < 2.3.3 Affected: >= 2.4.0, < 2.4.2 |
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CVE-2021-29585 (GCVE-0-2021-29585)
Vulnerability from cvelistv5 – Published: 2021-05-14 19:35 – Updated: 2024-08-03 22:11
VLAI
Title
Division by zero in padding computation in TFLite
Summary
TensorFlow is an end-to-end open source platform for machine learning. The TFLite computation for size of output after padding, `ComputeOutSize`(https://github.com/tensorflow/tensorflow/blob/0c9692ae7b1671c983569e5d3de5565843d500cf/tensorflow/lite/kernels/padding.h#L43-L55), does not check that the `stride` argument is not 0 before doing the division. Users can craft special models such that `ComputeOutSize` is called with `stride` set to 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.
Severity
CWE
- CWE-369 - Divide By Zero
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/tensorflow/tensorflow/security… | x_refsource_CONFIRM |
| https://github.com/tensorflow/tensorflow/commit/4… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| tensorflow | tensorflow |
Affected:
< 2.1.4
Affected: >= 2.2.0, < 2.2.3 Affected: >= 2.3.0, < 2.3.3 Affected: >= 2.4.0, < 2.4.2 |
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CVE-2021-29586 (GCVE-0-2021-29586)
Vulnerability from cvelistv5 – Published: 2021-05-14 19:35 – Updated: 2024-08-03 22:11
VLAI
Title
Division by zero in optimized pooling implementations in TFLite
Summary
TensorFlow is an end-to-end open source platform for machine learning. Optimized pooling implementations in TFLite fail to check that the stride arguments are not 0 before calling `ComputePaddingHeightWidth`(https://github.com/tensorflow/tensorflow/blob/3f24ccd932546416ec906a02ddd183b48a1d2c83/tensorflow/lite/kernels/pooling.cc#L90). Since users can craft special models which will have `params->stride_{height,width}` be zero, this will result in a division by zero. 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.
Severity
CWE
- CWE-369 - Divide By Zero
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/tensorflow/tensorflow/security… | x_refsource_CONFIRM |
| https://github.com/tensorflow/tensorflow/commit/5… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| tensorflow | tensorflow |
Affected:
< 2.1.4
Affected: >= 2.2.0, < 2.2.3 Affected: >= 2.3.0, < 2.3.3 Affected: >= 2.4.0, < 2.4.2 |
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CVE-2021-29587 (GCVE-0-2021-29587)
Vulnerability from cvelistv5 – Published: 2021-05-14 19:22 – Updated: 2024-08-03 22:11
VLAI
Title
Division by zero in TFLite's implementation of `SpaceToDepth`
Summary
TensorFlow is an end-to-end open source platform for machine learning. The `Prepare` step of the `SpaceToDepth` TFLite operator does not check for 0 before division(https://github.com/tensorflow/tensorflow/blob/5f7975d09eac0f10ed8a17dbb6f5964977725adc/tensorflow/lite/kernels/space_to_depth.cc#L63-L67). An attacker can craft a model such that `params->block_size` would be zero. 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.
Severity
CWE
- CWE-369 - Divide By Zero
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/tensorflow/tensorflow/security… | x_refsource_CONFIRM |
| https://github.com/tensorflow/tensorflow/commit/0… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| tensorflow | tensorflow |
Affected:
< 2.1.4
Affected: >= 2.2.0, < 2.2.3 Affected: >= 2.3.0, < 2.3.3 Affected: >= 2.4.0, < 2.4.2 |
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No mitigation information available for this CWE.
No CAPEC attack patterns related to this CWE.