CVE-2020-15200
published 2020-09-25CVE-2020-15200: In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In…
PriorityP429medium5.9CVSS 3.1
AVNACHPRNUINSUCNINAH
EPSS
0.85%
54.4th percentile
In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Affected
6 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| debian | tensorflow | — | — |
| tensorflow | — | — | |
| intel | optimization_for_tensorflow | >= 0 < 3cbb917b4714766030b28eba9fb41bb97ce9ee02 | 3cbb917b4714766030b28eba9fb41bb97ce9ee02 |
| intel | optimization_for_tensorflow | >= 0 < 2.3.1 | 2.3.1 |
| intel | optimization_for_tensorflow | >= 2.3.0 < 2.3.1 | 2.3.1 |
| tensorflow | tensorflow | — | — |
CVSS provenance
nvdv3.15.9MEDIUMCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
nvdv2.04.3MEDIUMAV:N/AC:M/Au:N/C:N/I:N/A:P
vendor_debian5.9LOW
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GHSA
Segfault in Tensorflow
ghsa·2020-09-25
CVE-2020-15200 [HIGH] CWE-122 Segfault in Tensorflow
Segfault in Tensorflow
### Impact
The `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the [following code](https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L248-L265
) sets up conditions to cause a heap buffer overflow:
```cc
auto per_batch_counts = BatchedMap(num_batches);
int batch_idx = 0;
for (int idx = 0; idx = splits_values(batch_idx)) {
batch_idx++;
}
const auto& value = values_values(idx);
if (value >= 0 && (maxlength_ <= 0 || value < maxlength_)) {
per_batch_counts[batch_idx - 1][value] = 1;
}
}
```
A `Batch
OSV
CVE-2020-15200: In Tensorflow before version 2
osv·2020-09-25
CVE-2020-15200 CVE-2020-15200: In Tensorflow before version 2
In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
OSV
Segfault in Tensorflow
osv·2020-09-25
CVE-2020-15200 [HIGH] Segfault in Tensorflow
Segfault in Tensorflow
### Impact
The `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the [following code](https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L248-L265
) sets up conditions to cause a heap buffer overflow:
```cc
auto per_batch_counts = BatchedMap(num_batches);
int batch_idx = 0;
for (int idx = 0; idx = splits_values(batch_idx)) {
batch_idx++;
}
const auto& value = values_values(idx);
if (value >= 0 && (maxlength_ <= 0 || value < maxlength_)) {
per_batch_counts[batch_idx - 1][value] = 1;
}
}
```
A `Batch
Debian
CVE-2020-15200: tensorflow - In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation...
vendor_debian·2020·CVSS 5.9
CVE-2020-15200 [MEDIUM] CVE-2020-15200: tensorflow - In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation...
In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Scope: local
forky: resolved
sid:
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x7rp-74x2-mjf3https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x7rp-74x2-mjf3
2020-09-25
Published