CVE-2021-29546
published 2021-05-14CVE-2021-29546: TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in…
PriorityP336high7.8CVSS 3.1
AVLACLPRLUINSUCHIHAH
EPSS
0.20%
10.2th percentile
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not 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.
Affected
18 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| debian | tensorflow | — | — |
| tensorflow | < 2.1.4 | 2.1.4 | |
| tensorflow | >= 2.2.0 < 2.2.3 | 2.2.3 | |
| tensorflow | >= 2.3.0 < 2.3.3 | 2.3.3 | |
| tensorflow | >= 2.4.0 < 2.4.2 | 2.4.2 | |
| intel | optimization_for_tensorflow | >= 0 < 2.1.4 | 2.1.4 |
| intel | optimization_for_tensorflow | >= 0 < 67784700869470d65d5f2ef20aeb5e97c31673cb | 67784700869470d65d5f2ef20aeb5e97c31673cb |
| intel | optimization_for_tensorflow | >= 0 < 2.2.0rc0 | 2.2.0rc0 |
| intel | optimization_for_tensorflow | >= 2.2.0 < 2.2.3 | 2.2.3 |
| intel | optimization_for_tensorflow | >= 2.2.0 < 2.3.0rc0 | 2.3.0rc0 |
| intel | optimization_for_tensorflow | >= 2.3.0 < 2.3.3 | 2.3.3 |
| intel | optimization_for_tensorflow | >= 2.3.0 < 2.3.4 | 2.3.4 |
| intel | optimization_for_tensorflow | >= 2.4.0 < 2.4.2 | 2.4.2 |
| intel | optimization_for_tensorflow | >= 2.4.0 < 2.4.3 | 2.4.3 |
| tensorflow | tensorflow | < 2.1.4 | 2.1.4 |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
CVSS provenance
nvdv3.17.8HIGHCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
nvdv2.04.6MEDIUMAV:L/AC:L/Au:N/C:P/I:P/A:P
vendor_debian2.5LOW
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Debian
CVE-2021-29546: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. An attack...
vendor_debian·2021·CVSS 2.5
CVE-2021-29546 [LOW] CVE-2021-29546: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. An attack...
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not 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.
Scope: local
forky: resolved
sid: resolved
GHSA
Division by 0 in `QuantizedBiasAdd`
ghsa·2021-05-21
CVE-2021-29546 [LOW] CWE-369 Division by 0 in `QuantizedBiasAdd`
Division by 0 in `QuantizedBiasAdd`
### Impact
An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`:
```python
import tensorflow as tf
input_tensor = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.quint8)
bias = tf.constant([], shape=[0], dtype=tf.quint8)
min_input = tf.constant(-10.0, dtype=tf.float32)
max_input = tf.constant(-10.0, dtype=tf.float32)
min_bias = tf.constant(-10.0, dtype=tf.float32)
max_bias = tf.constant(-10.0, dtype=tf.float32)
tf.raw_ops.QuantizedBiasAdd(input=input_tensor, bias=bias, min_input=min_input,
max_input=max_input, min_bias=min_bias,
max_bias=max_bias, out_type=tf.qint32)
```
This is because the [implementation of the Eigen kernel](https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcd
OSV
Division by 0 in `QuantizedBiasAdd`
osv·2021-05-21
CVE-2021-29546 [LOW] Division by 0 in `QuantizedBiasAdd`
Division by 0 in `QuantizedBiasAdd`
### Impact
An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`:
```python
import tensorflow as tf
input_tensor = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.quint8)
bias = tf.constant([], shape=[0], dtype=tf.quint8)
min_input = tf.constant(-10.0, dtype=tf.float32)
max_input = tf.constant(-10.0, dtype=tf.float32)
min_bias = tf.constant(-10.0, dtype=tf.float32)
max_bias = tf.constant(-10.0, dtype=tf.float32)
tf.raw_ops.QuantizedBiasAdd(input=input_tensor, bias=bias, min_input=min_input,
max_input=max_input, min_bias=min_bias,
max_bias=max_bias, out_type=tf.qint32)
```
This is because the [implementation of the Eigen kernel](https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcd
OSV
CVE-2021-29546: TensorFlow is an end-to-end open source platform for machine learning
osv·2021-05-14
CVE-2021-29546 CVE-2021-29546: TensorFlow is an end-to-end open source platform for machine learning
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not 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.
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cbhttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-m34j-p8rj-wjxqhttps://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cbhttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-m34j-p8rj-wjxq
2021-05-14
Published