neomutt: Out of bounds read in IMAP parser

Mutt 1.11.0 through 2.0.x before 2.0.7 (and NeoMutt 2019-10-25 through 2021-05-04) has a $imap_qresync issue in which imap/util.c has an out-of-bounds read in situations where an IMAP sequence set ends with a comma. NOTE: the $imap_qresync setting for QRESYNC is not enabled by default.

postgresql: Buffer overrun from integer overflow in array subscripting calculations

A flaw was found in postgresql in versions before 13.3, before 12.7, before 11.12, before 10.17 and before 9.6.22. While modifying certain SQL array values, missing bounds checks let authenticated database users write arbitrary bytes to a wide area of server memory. The highest threat from this vulnerability is to data confidentiality and integrity as well as system availability.

The kernel in Amazon Web Services FreeRTOS before 10.4.3 has insufficient bounds checking during management of heap memory.

Windows Hyper-V Denial of Service Vulnerability

Windows Hyper-V Denial of Service Vulnerability

In ASQ in Stormshield Network Security (SNS) 1.0.0 through 2.7.8, 2.8.0 through 2.16.0, 3.0.0 through 3.7.20, 3.8.0 through 3.11.8, and 4.0.1 through 4.2.2, mishandling of memory management can lead to remote code execution.

This vulnerability allows remote attackers to execute arbitrary code on affected installations of OpenText Brava! Desktop 16.6.3.84. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of DXF files. The issue results from the lack of proper validation of user-supplied data, which can result in a memory corruption condition. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-13307.

This vulnerability allows remote attackers to execute arbitrary code on affected installations of OpenText Brava! Desktop 16.6.3.84. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of DXF files. The issue results from the lack of proper validation of user-supplied data, which can result in a memory corruption condition. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-13304.

This vulnerability allows remote attackers to execute arbitrary code on affected installations of Foxit Reader 10.1.1.37576. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the handling of U3D objects in PDF files. The issue results from the lack of proper validation of user-supplied data, which can result in a write past the end of an allocated data structure. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-13011.

The gf_hinter_track_new function in GPAC 1.0.1 allows attackers to read memory via a crafted file in the MP4Box command.

Out of bounds memory access in WebAudio in Google Chrome prior to 91.0.4472.77 allowed a remote attacker to perform out of bounds memory access via a crafted HTML page.

A flaw was found in PoDoFo 0.9.7. A stack-based buffer overflow in PdfEncryptMD5Base::ComputeOwnerKey function in PdfEncrypt.cpp is possible because of a improper check of the keyLength value.

An issue was discovered in the outer_cgi crate before 0.2.1 for Rust. A user-provided Read instance receives an uninitialized memory buffer from KeyValueReader.

Possible out of bound memory access due to improper boundary check while creating HSYNC fence in Snapdragon Auto, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Wearables

Possible buffer overflow due to lack of range check while processing a DIAG command for COEX management in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables

Mozilla: Memory corruption as a result of incorrect style treatment

Firefox incorrectly treated an inline list-item element as a block element, resulting in an out of bounds read or memory corruption, and a potentially exploitable crash. This vulnerability affects Thunderbird < 78.13, Thunderbird < 91, Firefox ESR < 78.13, and Firefox < 91.

Heap buffer overflow in `MaxPoolGrad`

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/ab1e644b48c82cb71493f4362b4dd38f4577a1cf/tensorflow/core/kernels/maxpooling_op.cc#L194-L203) fails to validate that indices used to access elements of input/output arrays are valid. Whereas accesses to `input_backprop_flat` are guarded by `FastBoundsCheck`, the indexing in `out_backprop_flat` can result in OOB access. 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.

Heap buffer overflow in `FractionalAvgPoolGrad`

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalAvgPoolGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/dcba796a28364d6d7f003f6fe733d82726dda713/tensorflow/core/kernels/fractional_avg_pool_op.cc#L216) fails to validate that the pooling sequence arguments have enough elements as required by the `out_backprop` tensor shape. 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.

Heap buffer overflow in `AvgPool3DGrad`

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.AvgPool3DGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/d80ffba9702dc19d1fac74fc4b766b3fa1ee976b/tensorflow/core/kernels/pooling_ops_3d.cc#L376-L450) assumes that the `orig_input_shape` and `grad` tensors have similar first and last dimensions but does not check that this assumption is validated. 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.

Heap buffer overflow in `MaxPool3DGradGrad`

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPool3DGradGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L694-L696) does not check that the initialization of `Pool3dParameters` completes successfully. Since the constructor(https://github.com/tensorflow/tensorflow/blob/596c05a159b6fbb9e39ca10b3f7753b7244fa1e9/tensorflow/core/kernels/pooling_ops_3d.cc#L48-L88) uses `OP_REQUIRES` to validate conditions, the first assertion that fails interrupts the initialization of `params`, making it contain invalid data. In turn, this might cause a heap buffer overflow, depending on default initialized values. 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.

Overflow/denial of service in `tf.raw_ops.ReverseSequence`

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.ReverseSequence` allows for stack overflow and/or `CHECK`-fail based denial of service. The implementation(https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that `seq_dim` and `batch_dim` arguments are valid. Negative values for `seq_dim` can result in stack overflow or `CHECK`-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of `batch_dim`. 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.