CVE-2021-37677
published 2021-08-12CVE-2021-37677: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a…
PriorityP420medium5.5CVSS 3.1
AVLACLPRLUINSUCNINAH
EPSS
0.15%
4.4th percentile
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Affected
13 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| debian | tensorflow | — | — |
| tensorflow | — | — | |
| tensorflow | — | — | |
| tensorflow | >= 2.3.0 < 2.3.4 | 2.3.4 | |
| tensorflow | >= 2.4.0 < 2.4.3 | 2.4.3 | |
| intel | optimization_for_tensorflow | >= 0 < da857cfa0fde8f79ad0afdbc94e88b5d4bbec764 | da857cfa0fde8f79ad0afdbc94e88b5d4bbec764 |
| intel | optimization_for_tensorflow | >= 0 < 2.3.4 | 2.3.4 |
| intel | optimization_for_tensorflow | >= 2.3.0 < 2.3.4 | 2.3.4 |
| intel | optimization_for_tensorflow | >= 2.4.0 < 2.4.3 | 2.4.3 |
| intel | optimization_for_tensorflow | >= 2.5.0 < 2.5.1 | 2.5.1 |
| tensorflow | tensorflow | < 2.3.4 | 2.3.4 |
| 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_debian5.5LOW
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OSV
Missing validation in shape inference for `Dequantize`
osv·2021-08-25
CVE-2021-37677 [MEDIUM] Missing validation in shape inference for `Dequantize`
Missing validation in shape inference for `Dequantize`
### Impact
The shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments:
```python
import tensorflow as tf
tf.compat.v1.disable_v2_behavior()
tf.raw_ops.Dequantize(
input_tensor = tf.constant(-10.0, dtype=tf.float32),
input_tensor = tf.cast(input_tensor, dtype=tf.quint8),
min_range = tf.constant([], shape=[0], dtype=tf.float32),
max_range = tf.constant([], shape=[0], dtype=tf.float32),
mode = 'MIN_COMBINED',
narrow_range=False,
axis=-10,
dtype=tf.dtypes.float32)
```
The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999
GHSA
Missing validation in shape inference for `Dequantize`
ghsa·2021-08-25
CVE-2021-37677 [MEDIUM] CWE-1284 Missing validation in shape inference for `Dequantize`
Missing validation in shape inference for `Dequantize`
### Impact
The shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments:
```python
import tensorflow as tf
tf.compat.v1.disable_v2_behavior()
tf.raw_ops.Dequantize(
input_tensor = tf.constant(-10.0, dtype=tf.float32),
input_tensor = tf.cast(input_tensor, dtype=tf.quint8),
min_range = tf.constant([], shape=[0], dtype=tf.float32),
max_range = tf.constant([], shape=[0], dtype=tf.float32),
mode = 'MIN_COMBINED',
narrow_range=False,
axis=-10,
dtype=tf.dtypes.float32)
```
The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999
OSV
CVE-2021-37677: TensorFlow is an end-to-end open source platform for machine learning
osv·2021-08-12
CVE-2021-37677 CVE-2021-37677: TensorFlow is an end-to-end open source platform for machine learning
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. The fix will be included in TensorFlow 2
Debian
CVE-2021-37677: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. In affect...
vendor_debian·2021·CVSS 5.5
CVE-2021-37677 [MEDIUM] CVE-2021-37677: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. In affect...
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. The fix will be included in TensorFlow 2
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qfpc-5pjr-mh26https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qfpc-5pjr-mh26
2021-08-12
Published