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Vulnerabilities

With the aim of informing, warning and helping professionals with the latest security vulnerabilities in technology systems, we have made a database available for users interested in this information, which is in Spanish and includes all of the latest documented and recognised vulnerabilities.

This repository, with over 75,000 registers, is based on the information from the NVD (National Vulnerability Database) – by virtue of a partnership agreement – through which INCIBE translates the included information into Spanish.

On occasions this list will show vulnerabilities that have still not been translated, as they are added while the INCIBE team is still carrying out the translation process. The CVE  (Common Vulnerabilities and Exposures) Standard for Information Security Vulnerability Names is used with the aim to support the exchange of information between different tools and databases.

All vulnerabilities collected are linked to different information sources, as well as available patches or solutions provided by manufacturers and developers. It is possible to carry out advanced searches, as there is the option to select different criteria to narrow down the results, some examples being vulnerability types, manufacturers and impact levels, among others.

Through RSS feeds or Newsletters we can be informed daily about the latest vulnerabilities added to the repository. Below there is a list, updated daily, where you can discover the latest vulnerabilities.

CVE-2022-23591
Publication date:
04/02/2022
Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Severity CVSS v4.0: Pending analysis
Last modification:
27/06/2023

CVE-2022-23913
Publication date:
04/02/2022
In Apache ActiveMQ Artemis prior to 2.20.0 or 2.19.1, an attacker could partially disrupt availability (DoS) through uncontrolled resource consumption of memory.
Severity CVSS v4.0: Pending analysis
Last modification:
07/07/2023

CVE-2022-23947
Publication date:
04/02/2022
A stack-based buffer overflow vulnerability exists in the Gerber Viewer gerber and excellon DCodeNumber parsing functionality of KiCad EDA 6.0.1 and master commit de006fc010. A specially-crafted gerber or excellon file can lead to code execution. An attacker can provide a malicious file to trigger this vulnerability.
Severity CVSS v4.0: Pending analysis
Last modification:
07/11/2023

CVE-2022-23946
Publication date:
04/02/2022
A stack-based buffer overflow vulnerability exists in the Gerber Viewer gerber and excellon GCodeNumber parsing functionality of KiCad EDA 6.0.1 and master commit de006fc010. A specially-crafted gerber or excellon file can lead to code execution. An attacker can provide a malicious file to trigger this vulnerability.
Severity CVSS v4.0: Pending analysis
Last modification:
07/11/2023

CVE-2022-23582
Publication date:
04/02/2022
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that `TensorByteSize` would trigger `CHECK` failures. `TensorShape` constructor throws a `CHECK`-fail if shape is partial or has a number of elements that would overflow the size of an `int`. The `PartialTensorShape` constructor instead does not cause a `CHECK`-abort if the shape is partial, which is exactly what this function needs to be able to return `-1`. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Severity CVSS v4.0: Pending analysis
Last modification:
10/02/2022

CVE-2022-23576
Publication date:
04/02/2022
Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateOutputSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in `output_shape.dim()` or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Severity CVSS v4.0: Pending analysis
Last modification:
10/02/2022

CVE-2022-23577
Publication date:
04/02/2022
Tensorflow is an Open Source Machine Learning Framework. The implementation of `GetInitOp` is vulnerable to a crash caused by dereferencing a null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Severity CVSS v4.0: Pending analysis
Last modification:
10/02/2022

CVE-2022-23578
Publication date:
04/02/2022
Tensorflow is an Open Source Machine Learning Framework. If a graph node is invalid, TensorFlow can leak memory in the implementation of `ImmutableExecutorState::Initialize`. Here, we set `item->kernel` to `nullptr` but it is a simple `OpKernel*` pointer so the memory that was previously allocated to it would leak. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Severity CVSS v4.0: Pending analysis
Last modification:
10/02/2022

CVE-2022-23573
Publication date:
04/02/2022
Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Severity CVSS v4.0: Pending analysis
Last modification:
10/02/2022

CVE-2022-23574
Publication date:
04/02/2022
Tensorflow is an Open Source Machine Learning Framework. There is a typo in TensorFlow's `SpecializeType` which results in heap OOB read/write. Due to a typo, `arg` is initialized to the `i`th mutable argument in a loop where the loop index is `j`. Hence it is possible to assign to `arg` from outside the vector of arguments. Since this is a mutable proto value, it allows both read and write to outside of bounds data. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.
Severity CVSS v4.0: Pending analysis
Last modification:
10/02/2022

CVE-2022-23575
Publication date:
04/02/2022
Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateTensorSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Severity CVSS v4.0: Pending analysis
Last modification:
10/02/2022

CVE-2022-23566
Publication date:
04/02/2022
Tensorflow is an Open Source Machine Learning Framework. TensorFlow is vulnerable to a heap OOB write in `Grappler`. The `set_output` function writes to an array at the specified index. Hence, this gives a malicious user a write primitive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Severity CVSS v4.0: Pending analysis
Last modification:
10/02/2022
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