Vulmon
Recent Vulnerabilities
Research Posts
Trends
Blog
About
Contact
Vulmon Alerts
By Relevance
By Risk Score
By Publish Date
google tensorflow 2.3.0 vulnerabilities and exploits
(subscribe to this query)
5
CVSSv2
CVE-2020-15191
In Tensorflow prior to 2.2.1 and 2.3.1, if a user passes an invalid argument to `dlpack.to_dlpack` the expected validations will cause variables to bind to `nullptr` while setting a `status` variable to the error condition. However, this `status` argument is not properly checked....
Google Tensorflow 2.2.0
Google Tensorflow 2.3.0
Opensuse Leap 15.2
4
CVSSv2
CVE-2020-15192
In Tensorflow prior to 2.2.1 and 2.3.1, if a user passes a list of strings to `dlpack.to_dlpack` there is a memory leak following an expected validation failure. The issue occurs because the `status` argument during validation failures is not properly checked. Since each of the a...
Google Tensorflow 2.2.0
Google Tensorflow 2.3.0
Opensuse Leap 15.2
5.5
CVSSv2
CVE-2020-15193
In Tensorflow prior to 2.2.1 and 2.3.1, the implementation of `dlpack.to_dlpack` can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users ...
Google Tensorflow 2.2.0
Google Tensorflow 2.3.0
Opensuse Leap 15.2
3.5
CVSSv2
CVE-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 particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes it...
Google Tensorflow 2.3.0
6.5
CVSSv2
CVE-2020-15196
In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified. In the spa...
Google Tensorflow 2.3.0
4.3
CVSSv2
CVE-2020-15199
In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the `splits` tensor has the minimum required number of elements. Code uses this quantity to initiali...
Google Tensorflow 2.3.0
4.3
CVSSv2
CVE-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 particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tenso...
Google Tensorflow 2.3.0
6.8
CVSSv2
CVE-2020-15201
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` tenso...
Google Tensorflow 2.3.0
5
CVSSv2
CVE-2020-15206
In Tensorflow prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using ...
Google Tensorflow
Opensuse Leap 15.2
CVSSv2
CVSSv2
CVSSv3
VMScore
Recommendations:
race condition
CVE-2024-4249
CVE-2024-4244
CVE-2023-20198
TCP
CVE-2022-48648
CVE-2022-48636
CVE-2024-21345
SQL
Vulnerability Notification Service
You don’t have to wait for vulnerability scanning results
Get Started