CVE-2020-15197
published 2020-09-25CVE-2020-15197: In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In…
medium6.3CVSS 3.1
AVNACHPRLUINSCCNINAH
In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. 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 | — | — |
OSV
CVE-2020-15197: In Tensorflow before version 2
osv·2020-09-25
CVE-2020-15197 CVE-2020-15197: In Tensorflow before version 2
In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
GHSA
Denial of Service in Tensorflow
ghsa·2020-09-25
CVE-2020-15197 [MEDIUM] CWE-20 Denial of Service in Tensorflow
Denial of Service in Tensorflow
### Impact
The `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L185
However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor.
### Patches
We have patched the issue in 3cbb917b4714766030b28eba9fb4
OSV
Denial of Service in Tensorflow
osv·2020-09-25
CVE-2020-15197 [MEDIUM] Denial of Service in Tensorflow
Denial of Service in Tensorflow
### Impact
The `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L185
However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor.
### Patches
We have patched the issue in 3cbb917b4714766030b28eba9fb4
Debian
CVE-2020-15197: tensorflow - In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation...
vendor_debian·2020·CVSS 6.3
CVE-2020-15197 [MEDIUM] CVE-2020-15197: tensorflow - In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation...
In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Scope: local
forky: resolved
sid: resolved
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-qc53-44cj-vfvxhttps://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qc53-44cj-vfvx
2020-09-25
Published