An issue was discovered on Samsung mobile devices with O(8.x), P(9.0), and Q(10.0) software. The Quram image codec library allows attackers to overwrite memory and execute arbitrary code via crafted JPEG data that is mishandled during decoding. The Samsung IDs are SVE-2020-18088, SVE-2020-18225, SVE-2020-18301 (September 2020).

In KeyInstall, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08956986; Issue ID: MSV-1575.

Out-of-bound Write vulnerability in chunk parsing implementation of libsdffextractor prior to SMR Apr-2023 Release 1 allows local attackers to execute arbitrary code.

In atci, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS09082988; Issue ID: MSV-1774.

In da, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08541780; Issue ID: ALPS08541780.

In vdec, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS09028313; Issue ID: MSV-1703.

In da, there is a possible out of bounds write due to improper input validation. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08541632; Issue ID: ALPS08541633.

In ged, there is a possible out of bounds write due to an integer overflow. This could lead to local denial of service with System execution privileges needed. User interaction is not needed for exploitation Patch ID: ALPS07835901; Issue ID: ALPS07835901.

In mp3 decoder, there is a possible out of bounds write due to a race condition. This could lead to remote escalation of privilege with no additional execution privileges needed. User interaction is needed for exploitation. Patch ID: ALPS08441369; Issue ID: ALPS08441369.

In TVAPI, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: DTV03961601; Issue ID: DTV03961601.

In wlan firmware, there is a possible out of bounds write due to improper input validation. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08477406; Issue ID: MSV-1010.

In OPTEE, there is a possible out of bounds write due to an incorrect bounds check. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08522504; Issue ID: ALPS08522504.

In wlan firmware, there is a possible out of bounds write due to improper input validation. This could lead to remote escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08360153 (for MT6XXX chipsets) / WCNCR00363530 (for MT79XX chipsets); Issue ID: MSV-979.

In venc, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08810810 / ALPS08805789; Issue ID: MSV-1502.

Out of bounds memory access in Blink in Google Chrome prior to 122.0.6261.57 allowed a remote attacker to perform out of bounds memory access via a crafted HTML page. (Chromium security severity: High)

In gnss service, there is a possible out of bounds write due to improper input validation. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08719602; Issue ID: MSV-1412.

In flashc, there is a possible out of bounds write due to an uncaught exception. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08541757; Issue ID: ALPS08541764.

In alac decoder, there is a possible out of bounds write due to an incorrect error handling. This could lead to remote escalation of privilege with no additional execution privileges needed. User interaction is needed for exploitation. Patch ID: ALPS08441150; Issue ID: ALPS08441150.

In da, there is a possible out of bounds write due to lack of valudation. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08541632; Issue ID: ALPS08541742.

In wlan service, there is a possible out of bounds write due to improper input validation. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS08572601; Issue ID: MSV-1229.

Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would allow limited reads and writes outside of arrays in TFLite. This exploits missing validation in the conversion from sparse tensors to dense tensors. The fix is 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. Users are advised to upgrade as soon as possible.

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.

Heap buffer overflow in Visuals in Google Chrome prior to 115.0.5790.170 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page. (Chromium security severity: High)

An improper boundary check in eden_runtime hal service prior to SMR Feb-2022 Release 1 allows arbitrary memory write and code execution.

protobuf allows remote authenticated attackers to cause a heap-based buffer overflow.

Heap buffer overflow in WebRTC in Google Chrome prior to 103.0.5060.114 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page.

In a2dp_vendor_opus_decoder_decode_packet of a2dp_vendor_opus_decoder.cc, there is a possible out of bounds write due to a heap buffer overflow. This could lead to paired device escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

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.

In transcodeQ*ToFloat of btif_avrcp_audio_track.cc, there is a possible out of bounds write due to a missing bounds check. This could lead to paired device escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

Use after free in WebXR in Google Chrome on Android prior to 86.0.4240.75 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page.

An improper input validation in SMC_SRPMB_WSM handler of RPMB ldfw prior to SMR Feb-2022 Release 1 allows arbitrary memory write and code execution.

Use after free in media in Google Chrome prior to 86.0.4240.111 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page.

In multiple functions of MtpPacket.cpp, there is a possible out of bounds write due to a heap buffer overflow. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is needed for exploitation.

Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. 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.

Insufficient policy enforcement in ANGLE in Google Chrome prior to 86.0.4240.183 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page.

Inappropriate implementation in V8 in Google Chrome prior to 86.0.4240.183 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page.

Insufficient data validation in media in Google Chrome prior to 85.0.4183.121 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page.

Heap buffer overflow in UI in Google Chrome prior to 87.0.4280.66 allowed a remote attacker who had compromised the renderer process to potentially perform a sandbox escape via a crafted HTML page.

In wcn bsp driver, there is a possible out of bounds write due to a missing bounds check.This could lead to local denial of service with no additional execution privileges

In exif_entry_get_value of exif-entry.c, there is a possible out of bounds write due to an integer overflow. This could lead to remote code execution if a third party app used this library to process remote image data with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-8.1 Android-9 Android-10 Android-11 Android-8.0Android ID: A-159625731

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, to mimic Python's indexing with negative values, TFLite uses `ResolveAxis` to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds. If the `DCHECK` does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption. The issue is patched in commit 2d88f470dea2671b430884260f3626b1fe99830a, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

In TensorFlow Lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, saved models in the flatbuffer format use a double indexing scheme: a model has a set of subgraphs, each subgraph has a set of operators and each operator has a set of input/output tensors. The flatbuffer format uses indices for the tensors, indexing into an array of tensors that is owned by the subgraph. This results in a pattern of double array indexing when trying to get the data of each tensor. However, some operators can have some tensors be optional. To handle this scenario, the flatbuffer model uses a negative `-1` value as index for these tensors. This results in special casing during validation at model loading time. Unfortunately, this means that the `-1` index is a valid tensor index for any operator, including those that don't expect optional inputs and including for output tensors. Thus, this allows writing and reading from outside the bounds of heap allocated arrays, although only at a specific offset from the start of these arrays. This results in both read and write gadgets, albeit very limited in scope. The issue is patched in several commits (46d5b0852, 00302787b7, e11f5558, cd31fd0ce, 1970c21, and fff2c83), and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that only operators which accept optional inputs use the `-1` special value and only for the tensors that they expect to be optional. Since this allow-list type approach is erro-prone, we advise upgrading to the patched code.

In eatt_l2cap_reconfig_completed of eatt_impl.h, there is a possible out of bounds write due to an integer overflow. This could lead to remote code execution with no additional execution privileges needed. User interaction is not needed for exploitation.