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TensorFlow is an open source platform for machine learning. When `tf.quantization.fake_quant_with_min_max_vars_gradient` receives input `min` or `max` that is nonscalar, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
TensorFlow is an open source platform for machine learning. `DenseBincount` assumes its input tensor `weights` to either have the same shape as its input tensor `input` or to be length-0. A different `weights` shape will trigger a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bf4c14353c2328636a18bfad1e151052c81d5f43. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
When matrix-nio before 0.20 requests a room key from our devices, it correctly accepts key forwards only if they are a response to a previous request. However, it doesn't check that the device that responded matches the device the key was requested from. This allows a malicious homeserver to insert room keys of questionable validity into the key store in some situations, potentially assisting in an impersonation attack. ### For more information If you have any questions or comments about this advisory, e-mail us at [[email protected]](mailto:[email protected]).
["nth-check is vulnerable to Inefficient Regular Expression Complexity"]
### Impact When `SetSize` receives an input `set_shape` that is not a 1D tensor, it gives a `CHECK` fails that can be used to trigger a denial of service attack. ```python import tensorflow as tf arg_0=1 arg_1=[1,1] arg_2=1 arg_3=True arg_4='' tf.raw_ops.SetSize(set_indices=arg_0, set_values=arg_1, set_shape=arg_2, validate_indices=arg_3, name=arg_4) ``` ### Patches We have patched the issue in GitHub commit [cf70b79d2662c0d3c6af74583641e345fc939467](https://github.com/tensorflow/tensorflow/commit/cf70b79d2662c0d3c6af74583641e345fc939467). The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ##...
IBM AIX 7.1, 7.2, 7.3, and VIOS 3.1could allow a local user with elevated privileges to exploit a vulnerability in the lpd daemon to cause a denial of service. IBM X-Force ID: 238641.
TensorFlow is an open source platform for machine learning. If `LRNGrad` is given an `output_image` input tensor that is not 4-D, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bd90b3efab4ec958b228cd7cfe9125be1c0cf255. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
An issue was discovered in the Linux kernel before 6.3.9. ksmbd does not validate the SMB request protocol ID, leading to an out-of-bounds read.
IBM UrbanCode Deploy (UCD) 6.2.7.15, 7.0.5.10, 7.1.2.6, and 7.2.2.1 could disclose sensitive database information to a local user in plain text. IBM X-Force ID: 221008.
IBM QRadar SIEM 7.3, 7.4, and 7.5 does not preform proper certificate validation for some inter-host communications. IBM X-Force ID: 202015.