Advisoriesby IbisReference binding to null in `ParameterizedTruncatedNormal`
Impact
An attacker can trigger undefined behavior by binding to null pointer in tf.raw_ops.ParameterizedTruncatedNormal:
```python
import tensorflow as tf
shape = tf.constant([], shape=[0], dtype=tf.int32)
means = tf.constant((1), dtype=tf.float32)
stdevs = tf.constant((1), dtype=tf.float32)
minvals = tf.constant((1), dtype=tf.float32)
maxvals = tf.constant((1), dtype=tf.float32)
tf.raw_ops.ParameterizedTruncatedNormal(
shape=shape, means=means, stdevs=stdevs, minvals=minvals, maxvals=maxvals)
`
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/3f6fe4dfef6f57e768260b48166c27d148f3015f/tensorflow/core/kernels/parameterized_truncated_normal_op.cc#L630) does not validate input arguments before accessing the first element of shape:
```cc
int32 num_batches = shape_tensor.flat<int32>()(0);
`
If shape argument is empty, then shape_tensor.flat<T>() is an empty array.
Patches
We have patched the issue in GitHub commit [5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8](https://github.com/tensorflow/tensorflow/commit/5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8).
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.
For more information
Please consult [our security...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.1.4 | 2.1.4 |
| >= 2.2.0, < 2.2.3 | 2.2.3 | |
| >= 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 trigger undefined behavior by binding to null pointer in `tf.raw_ops.ParameterizedTruncatedNormal`: ```python import tensorflow as tf shape = tf.constant([], shape=[0], dtype=tf.int32) means = tf.constant((1), dtype=tf.float32) stdevs = tf.constant((1), dtype=tf.float32) minvals = tf.constant((1), dtype=tf.float32) maxvals = tf.constant((1), dtype=tf.float32) tf.raw_ops.ParameterizedTruncatedNormal( shape=shape, means=means, stdevs=stdevs, minvals=minvals, maxvals=maxvals) ``` This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/3f6fe4dfef6f57e768260b48166c27d148f3015f/tensorflow/core/kernels/parameterized_truncated_normal_op.cc#L630) does not validate input arguments before accessing the first element of `shape`: ```cc int32 num_batches = shape_tensor.flat<int32>()(0); ``` If `shape` argument is empty, then `shape_tensor.flat<T>()` is an empty array. ### Patches We have patched the issue in GitHub commit [5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8](https://github.com/tensorflow/tensorflow/commit/5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8). 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. ### 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 Ying Wang and Yakun Zhang 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-476, CWE-824
- Also known as
- BIT-tensorflow-2021-29568, CVE-2021-29568, PYSEC-2021-205, PYSEC-2021-496, PYSEC-2021-694
- github.com/tensorflow/tensorflow/security/advisories/GHSA-4p4p-www8-8fv9
- nvd.nist.gov/vuln/detail/CVE-2021-29568
- github.com/tensorflow/tensorflow/commit/5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-496.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-694.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-205.yaml
- github.com/tensorflow/tensorflow
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