CVE-2021-29549
published 2021-05-14CVE-2021-29549: 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…
PriorityP420medium5.5CVSS 3.1
AVLACLPRLUINSUCNINAH
EPSS
0.19%
8.7th percentile
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.
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 < 744009c9e5cc5d0447f0dc39d055f917e1fd9e16 | 744009c9e5cc5d0447f0dc39d055f917e1fd9e16 |
| 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
nvdv3.15.5MEDIUMCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
nvdv2.02.1LOWAV:L/AC:L/Au:N/C:N/I:N/A:P
vendor_debian2.5LOW
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GHSA
Division by 0 in `QuantizedAdd`
ghsa·2021-05-21
CVE-2021-29549 [LOW] CWE-369 Division by 0 in `QuantizedAdd`
Division by 0 in `QuantizedAdd`
### Impact
An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedAdd`:
```python
import tensorflow as tf
x = tf.constant([68, 228], shape=[2, 1], dtype=tf.quint8)
y = tf.constant([], shape=[2, 0], dtype=tf.quint8)
min_x = tf.constant(10.723421015884028)
max_x = tf.constant(15.19578006631113)
min_y = tf.constant(-5.539003866682977)
max_y = tf.constant(42.18819949559947)
tf.raw_ops.QuantizedAdd(x=x, y=y, min_x=min_x, max_x=max_x, min_y=min_y, max_y=max_y)
```
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 zer
OSV
Division by 0 in `QuantizedAdd`
osv·2021-05-21
CVE-2021-29549 [LOW] Division by 0 in `QuantizedAdd`
Division by 0 in `QuantizedAdd`
### Impact
An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedAdd`:
```python
import tensorflow as tf
x = tf.constant([68, 228], shape=[2, 1], dtype=tf.quint8)
y = tf.constant([], shape=[2, 0], dtype=tf.quint8)
min_x = tf.constant(10.723421015884028)
max_x = tf.constant(15.19578006631113)
min_y = tf.constant(-5.539003866682977)
max_y = tf.constant(42.18819949559947)
tf.raw_ops.QuantizedAdd(x=x, y=y, min_x=min_x, max_x=max_x, min_y=min_y, max_y=max_y)
```
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 zer
OSV
CVE-2021-29549: TensorFlow is an end-to-end open source platform for machine learning
osv·2021-05-14
CVE-2021-29549 CVE-2021-29549: 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 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 co
Debian
CVE-2021-29549: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. An attack...
vendor_debian·2021·CVSS 2.5
CVE-2021-29549 [LOW] CVE-2021-29549: 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 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 co
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8vhttps://github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8v
2021-05-14
Published