CVE-2021-29569
published 2021-05-14CVE-2021-29569: TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of…
PriorityP428high7.1CVSS 3.1
AVLACLPRLUINSUCHINAH
EPSS
0.20%
9.9th percentile
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the `input_min` and `input_max` tensors have at least one element, as it accesses the first element in two arrays. If the tensors are empty, `.flat()` is an empty object, backed by an empty array. Hence, accesing even the 0th element is a read outside the bounds. 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
14 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 < ef0c008ee84bad91ec6725ddc42091e19a30cf0e | ef0c008ee84bad91ec6725ddc42091e19a30cf0e |
| intel | optimization_for_tensorflow | >= 0 < 2.1.4 | 2.1.4 |
| intel | optimization_for_tensorflow | >= 2.2.0 < 2.2.3 | 2.2.3 |
| intel | optimization_for_tensorflow | >= 2.3.0 < 2.3.3 | 2.3.3 |
| intel | optimization_for_tensorflow | >= 2.4.0 < 2.4.2 | 2.4.2 |
| tensorflow | tensorflow | < 2.1.4 | 2.1.4 |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
CVSS provenance
nvdv3.17.1HIGHCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
nvdv2.03.6LOWAV:L/AC:L/Au:N/C:P/I:N/A:P
vendor_debian2.5LOW
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GHSA
Heap out of bounds read in `RequantizationRange`
ghsa·2021-05-21
CVE-2021-29569 [LOW] CWE-125 Heap out of bounds read in `RequantizationRange`
Heap out of bounds read in `RequantizationRange`
### Impact
The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs:
```python
import tensorflow as tf
input = tf.constant([1], shape=[1], dtype=tf.qint32)
input_max = tf.constant([], dtype=tf.float32)
input_min = tf.constant([], dtype=tf.float32)
tf.raw_ops.RequantizationRange(input=input, input_min=input_min, input_max=input_max)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the `input_min` and `input_max` tensors have at least one element, as it accesses the first element in two arrays:
```cc
co
OSV
Heap out of bounds read in `RequantizationRange`
osv·2021-05-21
CVE-2021-29569 [LOW] Heap out of bounds read in `RequantizationRange`
Heap out of bounds read in `RequantizationRange`
### Impact
The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs:
```python
import tensorflow as tf
input = tf.constant([1], shape=[1], dtype=tf.qint32)
input_max = tf.constant([], dtype=tf.float32)
input_min = tf.constant([], dtype=tf.float32)
tf.raw_ops.RequantizationRange(input=input, input_min=input_min, input_max=input_max)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the `input_min` and `input_max` tensors have at least one element, as it accesses the first element in two arrays:
```cc
co
OSV
CVE-2021-29569: TensorFlow is an end-to-end open source platform for machine learning
osv·2021-05-14
CVE-2021-29569 CVE-2021-29569: TensorFlow is an end-to-end open source platform for machine learning
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the `input_min` and `input_max` tensors have at least one element, as it accesses the first element in two arrays. If the tensors are empty, `.flat()` is an empty object, backed by an empty array. Hence, accesing even the 0th element is a read outside the bounds. 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, Tens
Debian
CVE-2021-29569: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. The imple...
vendor_debian·2021·CVSS 2.5
CVE-2021-29569 [LOW] CVE-2021-29569: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. The imple...
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the `input_min` and `input_max` tensors have at least one element, as it accesses the first element in two arrays. If the tensors are empty, `.flat()` is an empty object, backed by an empty array. Hence, accesing even the 0th element is a read outside the bounds. 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, Tens
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/ef0c008ee84bad91ec6725ddc42091e19a30cf0ehttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-3h8m-483j-7xxmhttps://github.com/tensorflow/tensorflow/commit/ef0c008ee84bad91ec6725ddc42091e19a30cf0ehttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-3h8m-483j-7xxm
2021-05-14
Published