CWE-787

Multiple buffer overflows in the limited configuration shell (/sbin/gs_config) on Grandstream HT801 devices before 1.0.29 allow remote authenticated users to execute arbitrary code as root via a crafted manage_if setting, thus bypassing the intended restrictions of this shell and taking full control of the device. There are default weak credentials that can be used to authenticate.

Any CA issuer in the RPKI can trick OctoRPKI prior to 1.3.0 into emitting an invalid VRP “MaxLength” value, causing RTR sessions to terminate. An attacker can use this to disable RPKI Origin Validation in a victim network (for example AS 13335 – Cloudflare) prior to launching a BGP hijack which during normal operations would be rejected as “RPKI invalid”. Additionally, in certain deployments RTR session flapping in and of itself also could cause BGP routing churn, causing availability issues.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc#L93-L102) assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types. We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

libmysofa is vulnerable to Heap-based Buffer Overflow

MediaTek microchips, as used in NETGEAR devices through 2021-11-11 and other devices, mishandle the WPS (Wi-Fi Protected Setup) protocol. (Affected Chipsets MT7603E, MT7610, MT7612, MT7613, MT7615, MT7620, MT7622, MT7628, MT7629, MT7915; Affected Software Versions 7.4.0.0; Out-of-bounds write).