Various out of bounds reads when handling responses in OpenSC before 0.19.0-rc1 could be used by attackers able to supply crafted smartcards to potentially crash the opensc library using programs.

Out-of-bounds read in the Intel(R) Trace Analyzer and Collector before version 2021.5 may allow an authenticated user to potentially enable denial of service via local access.

A specially crafted IOCTL can be issued to the rzpnk.sys driver in Razer Synapse that can cause an out of bounds read operation to occur due to a field within the IOCTL data being used as a length.

hw/display/cirrus_vga_rop.h in QEMU (aka Quick Emulator) allows local guest OS privileged users to cause a denial of service (out-of-bounds read and QEMU process crash) via vectors related to copying VGA data via the cirrus_bitblt_rop_fwd_transp_ and cirrus_bitblt_rop_fwd_ functions.

Out-of-bounds read condition in older versions of some Intel Graphics Driver for Windows code branches allows local users to perform a denial of service attack.

The sdhci_sdma_transfer_multi_blocks function in hw/sd/sdhci.c in QEMU (aka Quick Emulator) allows local guest OS privileged users to cause a denial of service (out-of-bounds heap access and crash) or execute arbitrary code on the QEMU host via vectors involving the data transfer length.

The vrend_draw_vbo function in virglrenderer before 0.6.0 allows local guest OS users to cause a denial of service (out-of-bounds array access and QEMU process crash) via vectors involving vertext_buffer_index.

The cirrus_invalidate_region function in hw/display/cirrus_vga.c in Qemu allows local OS guest privileged users to cause a denial of service (out-of-bounds array access and QEMU process crash) via vectors related to negative pitch.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a segfault and denial of service via accessing data outside of bounds in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc#L176-L189) assumes the inputs are not empty. If any of these inputs is empty, `.flat<T>()` is an empty buffer, so accessing the element at index 0 is accessing data outside of bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

njs through 0.4.3, used in NGINX, has an out-of-bounds read in njs_lvlhsh_level_find in njs_lvlhsh.c.

Possible buffer over-read due to lack of length check while flashing meta images in Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables

HUAWEI P30 Pro smartphones with Versions earlier than 10.1.0.160(C00E160R2P8) have an out of bound read vulnerability. Some functions are lack of verification when they process some messages sent from other module. Attackers can exploit this vulnerability by send malicious message to cause out-of-bound read. This can compromise normal service.