CVE-2021-29532
published 2021-05-14CVE-2021-29532: TensorFlow is an end-to-end open source platform for machine learning. An attacker can force accesses outside the bounds of heap allocated arrays by passing in…
PriorityP429high7.1CVSS 3.1
AVLACLPRLUINSUCHINAH
EPSS
0.20%
9.9th percentile
TensorFlow is an end-to-end open source platform for machine learning. An attacker can force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to `tf.raw_ops.RaggedCross`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efea03b38fb8d3b81762237dc85e579cc5fc6e87/tensorflow/core/kernels/ragged_cross_op.cc#L456-L487) lacks validation for the user supplied arguments. Each of the above branches call a helper function after accessing array elements via a `*_list[next_*]` pattern, followed by incrementing the `next_*` index. However, as there is no validation that the `next_*` values are in the valid range for the corresponding `*_list` arrays, this results in heap OOB reads. 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 < 44b7f486c0143f68b56c34e2d01e146ee445134a | 44b7f486c0143f68b56c34e2d01e146ee445134a |
| 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
nvdv3.17.1HIGHCVSS: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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Debian
CVE-2021-29532: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. An attack...
vendor_debian·2021·CVSS 2.5
CVE-2021-29532 [LOW] CVE-2021-29532: 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 force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to `tf.raw_ops.RaggedCross`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efea03b38fb8d3b81762237dc85e579cc5fc6e87/tensorflow/core/kernels/ragged_cross_op.cc#L456-L487) lacks validation for the user supplied arguments. Each of the above branches call a helper function after accessing array elements via a `*_list[next_*]` pattern, followed by incrementing the `next_*` index. However, as there is no validation that the `next_*` values are in the valid range for the corresponding `*_list` arrays, this results in heap OOB reads. The fix will be included in TensorFlow 2.5.0. We wi
GHSA
Heap out of bounds read in `RaggedCross`
ghsa·2021-05-21
CVE-2021-29532 [LOW] CWE-125 Heap out of bounds read in `RaggedCross`
Heap out of bounds read in `RaggedCross`
### Impact
An attacker can force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to `tf.raw_ops.RaggedCross`:
```python
import tensorflow as tf
ragged_values = []
ragged_row_splits = []
sparse_indices = []
sparse_values = []
sparse_shape = []
dense_inputs_elem = tf.constant([], shape=[92, 0], dtype=tf.int64)
dense_inputs = [dense_inputs_elem]
input_order = "R"
hashed_output = False
num_buckets = 0
hash_key = 0
tf.raw_ops.RaggedCross(ragged_values=ragged_values,
ragged_row_splits=ragged_row_splits,
sparse_indices=sparse_indices,
sparse_values=sparse_values,
sparse_shape=sparse_shape,
dense_inputs=dense_inputs,
input_order=input_order,
hashed_output=hashed_output,
num_buckets=num_buckets,
hash_key=hash_ke
OSV
Heap out of bounds read in `RaggedCross`
osv·2021-05-21
CVE-2021-29532 [LOW] Heap out of bounds read in `RaggedCross`
Heap out of bounds read in `RaggedCross`
### Impact
An attacker can force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to `tf.raw_ops.RaggedCross`:
```python
import tensorflow as tf
ragged_values = []
ragged_row_splits = []
sparse_indices = []
sparse_values = []
sparse_shape = []
dense_inputs_elem = tf.constant([], shape=[92, 0], dtype=tf.int64)
dense_inputs = [dense_inputs_elem]
input_order = "R"
hashed_output = False
num_buckets = 0
hash_key = 0
tf.raw_ops.RaggedCross(ragged_values=ragged_values,
ragged_row_splits=ragged_row_splits,
sparse_indices=sparse_indices,
sparse_values=sparse_values,
sparse_shape=sparse_shape,
dense_inputs=dense_inputs,
input_order=input_order,
hashed_output=hashed_output,
num_buckets=num_buckets,
hash_key=hash_ke
OSV
CVE-2021-29532: TensorFlow is an end-to-end open source platform for machine learning
osv·2021-05-14
CVE-2021-29532 CVE-2021-29532: 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 force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to `tf.raw_ops.RaggedCross`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efea03b38fb8d3b81762237dc85e579cc5fc6e87/tensorflow/core/kernels/ragged_cross_op.cc#L456-L487) lacks validation for the user supplied arguments. Each of the above branches call a helper function after accessing array elements via a `*_list[next_*]` pattern, followed by incrementing the `next_*` index. However, as there is no validation that the `next_*` values are in the valid range for the corresponding `*_list` arrays, this results in heap OOB reads. The fix will be included in TensorFlow 2.5.0. We wi
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/44b7f486c0143f68b56c34e2d01e146ee445134ahttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-j47f-4232-hvv8https://github.com/tensorflow/tensorflow/commit/44b7f486c0143f68b56c34e2d01e146ee445134ahttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-j47f-4232-hvv8
2021-05-14
Published