CVE-2020-15202
published 2020-09-25CVE-2020-15202: In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two…
critical9CVSS 3.1
AVNACHPRNUINSCCHIHAH
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments. However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Affected
19 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| debian | tensorflow | — | — |
| tensorflow | < 1.15.4 | 1.15.4 | |
| tensorflow | >= 2.0.0 < 2.0.3 | 2.0.3 | |
| tensorflow | >= 2.1.0 < 2.1.2 | 2.1.2 | |
| tensorflow | >= 2.2.0 < 2.2.1 | 2.2.1 | |
| tensorflow | >= 2.3.0 < 2.3.1 | 2.3.1 | |
| intel | optimization_for_tensorflow | < ca8c013b5e97b1373b3bb1c97ea655e69f31a575 | ca8c013b5e97b1373b3bb1c97ea655e69f31a575 |
| intel | optimization_for_tensorflow | >= 0 < 1.15.4 | 1.15.4 |
| intel | optimization_for_tensorflow | >= 0 < 27b417360cbd671ef55915e4bb6bb06af8b8a832 | 27b417360cbd671ef55915e4bb6bb06af8b8a832 |
| intel | optimization_for_tensorflow | >= 2.0.0 < 2.0.3 | 2.0.3 |
| intel | optimization_for_tensorflow | >= 2.1.0 < 2.1.2 | 2.1.2 |
| intel | optimization_for_tensorflow | >= 2.2.0 < 2.2.1 | 2.2.1 |
| intel | optimization_for_tensorflow | >= 2.3.0 < 2.3.1 | 2.3.1 |
| opensuse | leap | — | — |
| tensorflow | tensorflow | < 1.15.4 | 1.15.4 |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
OSV
Integer truncation in Shard API usage
osv·2020-09-25
CVE-2020-15202 [HIGH] Integer truncation in Shard API usage
Integer truncation in Shard API usage
### Impact
The `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/util/work_sharder.h#L59-L60
However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L204-L205
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L317-L318
In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on
OSV
CVE-2020-15202: In Tensorflow before versions 1
osv·2020-09-25
CVE-2020-15202 CVE-2020-15202: In Tensorflow before versions 1
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments. However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
GHSA
Integer truncation in Shard API usage
ghsa·2020-09-25
CVE-2020-15202 [HIGH] CWE-197 Integer truncation in Shard API usage
Integer truncation in Shard API usage
### Impact
The `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/util/work_sharder.h#L59-L60
However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L204-L205
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/random_op.cc#L317-L318
In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on
Debian
CVE-2020-15202: tensorflow - In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard`...
vendor_debian·2020·CVSS 9.0
CVE-2020-15202 [CRITICAL] CVE-2020-15202: tensorflow - In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard`...
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments. However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Scope: local
forky: resolve
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.htmlhttps://github.com/tensorflow/tensorflow/commit/27b417360cbd671ef55915e4bb6bb06af8b8a832https://github.com/tensorflow/tensorflow/commit/ca8c013b5e97b1373b3bb1c97ea655e69f31a575https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6fg-mjxg-hqq4http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.htmlhttps://github.com/tensorflow/tensorflow/commit/27b417360cbd671ef55915e4bb6bb06af8b8a832https://github.com/tensorflow/tensorflow/commit/ca8c013b5e97b1373b3bb1c97ea655e69f31a575https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6fg-mjxg-hqq4
2020-09-25
Published