In read_paint of ttcolr.c, there is a possible out of bounds read due to a heap buffer overflow. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-13Android ID: A-254803162

In affected versions of TensorFlow the tf.raw_ops.DataFormatVecPermute API does not validate the src_format and dst_format attributes. The code assumes that these two arguments define a permutation of NHWC. This can result in uninitialized memory accesses, read outside of bounds and even crashes. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.

In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input slot of the dst node (given by input_index). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.

In btm_ble_update_inq_result of btm_ble_gap.cc, there is a possible out of bounds read due to a heap buffer overflow. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-13Android ID: A-264880969

In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these. This is patched in version 2.4.0. This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched.

In dumpstateBoard of Dumpstate.cpp, there is a possible out of bounds read 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.Product: AndroidVersions: Android kernelAndroid ID: A-263783650References: N/A

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, if userspace provides a too-large IE length in wlan_hdd_cfg80211_set_ie, a buffer over-read occurs.

In all Qualcomm products with Android releases from CAF using the Linux kernel, the camera application can possibly request frame/command buffer processing with invalid values leading to the driver performing a heap buffer over-read.

In all Android releases from CAF using the Linux kernel, an out of bounds access can potentially occur in a camera function.

In all Android releases from CAF using the Linux kernel, a kernel driver has an off-by-one buffer over-read vulnerability.

In all Qualcomm products with Android releases from CAF using the Linux kernel, array out of bounds access can occur if userspace sends more than 16 multicast addresses.

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `QuantizeV2` can trigger a read outside of bounds of heap allocated array. This occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer. The code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, while processing start bss request from upper layer, out of bounds read occurs if ssid length is greater than maximum.

In video decoder, there is a possible out of bounds read due to improper input validation. This could lead to local denial of service with no additional execution privileges needed

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, while processing diag event after associating to a network out of bounds read occurs if ssid of the network joined is greater than max limit.

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, in wma_ndp_confirm_event_handler and wma_ndp_indication_event_handler, ndp_cfg len and num_ndp_app_info is from fw. If they are not checked, it may cause buffer over-read once the value is too large.

In SignalStrengthAdapter::FillGsmSignalStrength() of protocolmiscadapter.cpp, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with baseband firmware compromise required. User interaction is not needed for exploitation.

In Init of protocolcalladapter.cpp, there is a possible out of bounds read due to a missing bounds check. This could lead to remote information disclosure with System execution privileges needed. User interaction is not needed for exploitation.

In video decoder, there is a possible out of bounds read due to improper input validation. This could lead to local denial of service with no additional execution privileges needed

In ProtocolMiscCarrierConfigSimInfoIndAdapter of protocolmiscadapter.cpp, there is a possible out of bounds read due to a missing bounds check. This could lead to remote information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.

In cd_ParseMsg of cd_codec.c, there is a possible out of bounds read due to a missing bounds check. This could lead to remote information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.

In Init of protocolembmsadapter.cpp, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.

In video decoder, there is a possible out of bounds read due to improper input validation. This could lead to local denial of service with no additional execution privileges needed

In Init of protocolnetadapter.cpp, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.

In video decoder, there is a possible out of bounds read due to improper input validation. This could lead to local denial of service with no additional execution privileges needed

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of sparse reduction operations in TensorFlow can trigger accesses outside of bounds of heap allocated data. The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_reduce_op.cc#L217-L228) fails to validate that each reduction group does not overflow and that each corresponding index does not point to outside the bounds of the input tensor. We have patched the issue in GitHub commit 87158f43f05f2720a374f3e6d22a7aaa3a33f750. 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.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, while parsing Netlink attributes, a buffer overread can occur.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, while processing a vendor command, a buffer over-read can occur.

Out of bounds read in ANGLE allowed a remote attacker to obtain sensitive data via a crafted HTML page.

In parse_gap_data of utils.cc, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with User execution privileges needed. User interaction is not needed for exploitation.

An array out-of-bounds access in all Qualcomm products with Android releases from CAF using the Linux kernel can potentially occur in a camera driver.

NVIDIA libnvrm contains a possible out of bounds read due to a missing bounds check which could lead to local information disclosure. This issue is rated as moderate. Product: Android. Version: N/A. Android: A-65482562. Reference: N-CVE-2017-6288.

In all Android releases from CAF using the Linux kernel, a buffer overread can occur if a particular string is not NULL terminated.

NVIDIA driver contains a possible out-of-bounds read vulnerability due to a leak which may lead to information disclosure. This issue is rated as moderate. Android: A-63851980.

NVIDIA libnvrm contains a possible out of bounds read due to a missing bounds check which could lead to local information disclosure. This issue is rated as moderate.Product: Android. Version: N/A. Android: A-64893264. Reference: N-CVE-2017-6287.

Out of bounds read in audio in Google Chrome prior to 86.0.4240.75 allowed a remote attacker to obtain potentially sensitive information from process memory via a crafted HTML page.

NVIDIA Tegra kernel driver contains a vulnerability in NVIDIA NVDEC, where a user with high privileges might be able to read from or write to a memory location that is outside the intended boundary of the buffer, which may lead to denial of service, Information disclosure, loss of Integrity, or possible escalation of privileges.

In kernel/compat.c in the Linux kernel before 3.17, as used in Google Chrome OS and other products, there is a possible out-of-bounds read. restart_syscall uses uninitialized data when restarting compat_sys_nanosleep. NOTE: this is disputed because the code path is unreachable

Out of bounds read in networking in Google Chrome prior to 87.0.4280.88 allowed a remote attacker who had compromised the renderer process to obtain potentially sensitive information from process memory via a crafted HTML page.

NVIDIA libnvrm contains a possible out of bounds read due to a missing bounds check which could lead to local information disclosure. This issue is rated as moderate. Product: Android. Version: N/A. Android: A-64893156. Reference: N-CVE-2017-6285.

NVIDIA TrustZone Software contains a vulnerability in the Keymaster implementation where the software reads data past the end, or before the beginning, of the intended buffer; and may lead to denial of service or information disclosure. This issue is rated as high.

Insufficient validation of untrusted input in V8 in Google Chrome prior to 59.0.3071.104 for Mac, Windows, and Linux, and 59.0.3071.117 for Android, allowed a remote attacker to perform out of bounds memory access via a crafted HTML page.

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.

Out of bounds memory access in V8 in Google Chrome prior to 116.0.5845.110 allowed a remote attacker to perform an out of bounds memory read via a crafted HTML page. (Chromium security severity: High)

In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified. In the sparse and ragged count weights are still accessed in parallel with the data. But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

An issue was discovered on Samsung mobile devices with M(6.0) and N(7.x) software. There is a buffer over-read in a trustlet. The Samsung ID is SVE-2017-8890 (August 2017).

Out of bounds memory access in CSS in Google Chrome prior to 116.0.5845.110 allowed a remote attacker to perform an out of bounds memory read via a crafted HTML page. (Chromium security severity: High)

TensorFlow is an end-to-end open source platform for machine learning. The implementations of the `Minimum` and `Maximum` TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within 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.

Incorrect handling of complex species in V8 in Google Chrome prior to 57.0.2987.98 for Linux, Windows, and Mac and 57.0.2987.108 for Android allowed a remote attacker to execute arbitrary code via a crafted HTML page.

Out of bounds memory access in Fonts in Google Chrome prior to 116.0.5845.110 allowed a remote attacker to perform an out of bounds memory read via a crafted HTML page. (Chromium security severity: Medium)