TensorFlow is an end-to-end open source platform for machine learning. A specially crafted TFLite model could trigger an OOB read on heap in the TFLite implementation of `Split_V`(https://github.com/tensorflow/tensorflow/blob/c59c37e7b2d563967da813fa50fe20b21f4da683/tensorflow/lite/kernels/split_v.cc#L99). If `axis_value` is not a value between 0 and `NumDimensions(input)`, then the `SizeOfDimension` function(https://github.com/tensorflow/tensorflow/blob/102b211d892f3abc14f845a72047809b39cc65ab/tensorflow/lite/kernels/kernel_util.h#L148-L150) will access data outside the bounds of the tensor shape array. 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.

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, while processing start bss request from upper layer, out of bounds read occurs if ssid length is greater than maximum.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, Buffer overread may occur due to non-null terminated strings while processing vsprintf in camera jpeg driver.

NVIDIA SHIELD TV, all versions prior to 8.2.2, contains a vulnerability in the NVDEC component, in which an attacker can read from or write to a memory location that is outside the intended boundary of the buffer, which may lead to denial of service or escalation of privileges.

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, a buffer over-read can occur In the WMA NDP event handler functions due to lack of validation of input value event_info which is received from FW.

In kisd, there is a possible out of bounds read 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. Product: Android; Versions: Android-11; Patch ID: ALPS05449968.

In ccci, there is a possible out of bounds read due to a missing bounds check. This could lead to local information disclosure with System execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS06108658; Issue ID: ALPS06108658.

In getAppSize of InstalldNativeService.cpp, there is a possible out of bounds read 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.Product: AndroidVersions: Android-12LAndroid ID: A-220733817

In phNxpNciHal_send_ext_cmd of phNxpNciHal_ext.cc, there is a possible out of bounds write due to a missing bounds check. This could lead to local escalation of privilege in the NFC server with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11Android ID: A-153731369

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, improper input validation for vdev_map in wma_tbttoffset_update_event_handler(), which is received from firmware, leads to potential buffer overwrite and out of bounds memory read.

In Android releases from CAF using the linux kernel (Android for MSM, Firefox OS for MSM, QRD Android) before security patch level 2018-06-05, while processing a StrHwPlatform with length smaller than EFICHIPINFO_MAX_ID_LENGTH, an array out of bounds access may occur.

In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, improper input validation for vdev_id in wma_unified_bcntx_status_event_handler() which is received from firmware leads to potential out of bounds memory read.

An issue was discovered on Samsung mobile devices with P(9.0) (Exynos chipsets) software. Kernel Wi-Fi drivers allow out-of-bounds Read or Write operations (e.g., a buffer overflow). The Samsung IDs are SVE-2019-16125, SVE-2019-16134, SVE-2019-16158, SVE-2019-16159, SVE-2019-16319, SVE-2019-16320, SVE-2019-16337, SVE-2019-16464, SVE-2019-16465, SVE-2019-16467 (March 2020).

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, while processing a gpt update, an out of bounds memory access may potentially occur.

TensorFlow is an open source platform for machine learning. In affected versions the code for sparse matrix multiplication is vulnerable to undefined behavior via binding a reference to `nullptr`. This occurs whenever the dimensions of `a` or `b` are 0 or less. In the case on one of these is 0, an empty output tensor should be allocated (to conserve the invariant that output tensors are always allocated when the operation is successful) but nothing should be written to it (that is, we should return early from the kernel implementation). Otherwise, attempts to write to this empty tensor would result in heap OOB access. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 an attacker can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to `tf.raw_ops.ResourceScatterUpdate`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L919-L923) has an incomplete validation of the relationship between the shapes of `indices` and `updates`: instead of checking that the shape of `indices` is a prefix of the shape of `updates` (so that broadcasting can happen), code only checks that the number of elements in these two tensors are in a divisibility relationship. We have patched the issue in GitHub commit 01cff3f986259d661103412a20745928c727326f. 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.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all binary cwise operations that don't require broadcasting (e.g., gradients of binary cwise operations). The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/cwise_ops_common.h#L264) assumes that the two inputs have exactly the same number of elements but does not check that. Hence, when the eigen functor executes it triggers heap OOB reads and undefined behavior due to binding to nullptr. We have patched the issue in GitHub commit 93f428fd1768df147171ed674fee1fc5ab8309ec. 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 skb_headlen of /include/linux/skbuff.h, there is a possible out of bounds read due to memory corruption. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-153881554

TensorFlow is an end-to-end open source platform for machine learning. When restoring tensors via raw APIs, if the tensor name is not provided, TensorFlow can be tricked into dereferencing a null pointer. Alternatively, attackers can read memory outside the bounds of heap allocated data by providing some tensor names but not enough for a successful restoration. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/save_restore_tensor.cc#L158-L159) retrieves the tensor list corresponding to the `tensor_name` user controlled input and immediately retrieves the tensor at the restoration index (controlled via `preferred_shard` argument). This occurs without validating that the provided list has enough values. If the list is empty this results in dereferencing a null pointer (undefined behavior). If, however, the list has some elements, if the restoration index is outside the bounds this results in heap OOB read. We have patched the issue in GitHub commit 9e82dce6e6bd1f36a57e08fa85af213e2b2f2622. 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 it is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However, if the input tensor is a `RaggedTensor` and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not the case. The last row of `t` contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_from_variant_op.cc#L177-L190) does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. 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 nci_proc_rf_management_ntf of nci_hrcv.cc, there is a possible out of bounds read 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.Product: AndroidVersions: Android-11Android ID: A-164440989

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.

While processing the system path, an out of bounds access can occur in Android releases from CAF using the linux kernel (Android for MSM, Firefox OS for MSM, QRD Android) before security patch level 2018-06-05.

While processing the USB StrSerialDescriptor array, an array index out of bounds can occur in Android releases from CAF using the linux kernel (Android for MSM, Firefox OS for MSM, QRD Android) before security patch level 2018-06-05.

A buffer over-read can occur during a fast initial link setup (FILS) connection in Android releases from CAF using the linux kernel (Android for MSM, Firefox OS for MSM, QRD Android) before security patch level 2018-06-05.

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FusedBatchNorm` is vulnerable to a heap buffer overflow. If the tensors are empty, the same implementation can trigger undefined behavior by dereferencing null pointers. The implementation(https://github.com/tensorflow/tensorflow/blob/57d86e0db5d1365f19adcce848dfc1bf89fdd4c7/tensorflow/core/kernels/fused_batch_norm_op.cc) fails to validate that `scale`, `offset`, `mean` and `variance` (the last two only when required) all have the same number of elements as the number of channels of `x`. This results in heap out of bounds reads when the buffers backing these tensors are indexed past their boundary. If the tensors are empty, the validation mentioned in the above paragraph would also trigger and prevent the undefined behavior. 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.

In android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, possible buffer overflow or information leak in the functions "sme_set_ft_ies" and "csr_roam_issue_ft_preauth_req" due to incorrect initialization of WEXT callbacks and lack of the checks for buffer size.

An attacker can modify the address to point to trusted memory to overwrite arbitrary trusted memory. It is recommended to update past 0.6.2 or git commit https://github.com/google/asylo/commit/53ed5d8fd8118ced1466e509606dd2f473707a5c

The Security Team discovered an integer overflow bug that allows an attacker with code execution to issue memory cache invalidation operations on pages that they don’t own, allowing them to control kernel memory from userspace. We recommend upgrading to kernel version 4.1 or beyond.

In IoT Devices SDK, there is an implementation of calloc() that doesn't have a length check. An attacker could pass in memory objects larger than the buffer and wrap around to have a smaller buffer than required, allowing the attacker access to the other parts of the heap. We recommend upgrading the Google Cloud IoT Device SDK for Embedded C used to 1.0.3 or greater.

In OatFileAssistant::GenerateOatFile of oat_file_assistant.cc, there is a possible file corruption issue due to an insecure default value. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: Android-7.0 Android-7.1.1 Android-7.1.2 Android-8.0 Android-8.1 Android-9. Android ID: A-130821293.

An attacker can change the pointer to untrusted memory to point to trusted memory region which causes copying trusted memory to trusted memory, if the latter is later copied out, it allows for reading of memory regions from the trusted region. It is recommended to update past 0.6.2 or git commit https://github.com/google/asylo/commit/53ed5d8fd8118ced1466e509606dd2f473707a5c

An attacker can modify the pointers in enclave memory to overwrite arbitrary memory addresses within the secure enclave. It is recommended to update past 0.6.3 or git commit https://github.com/google/asylo/commit/a47ef55db2337d29de19c50cd29b0deb2871d31c

An attacker can craft a specific IdaPro *.i64 file that will cause the BinDiff plugin to load an invalid memory offset. This can allow the attacker to control the instruction pointer and execute arbitrary code. It is recommended to upgrade BinDiff 7

Stack-based buffer overflow in decoder/impeg2d_vld.c in mediaserver in Android 6.x before 2016-04-01 allows remote attackers to execute arbitrary code or cause a denial of service (memory corruption) via a crafted media file, aka internal bug 25812590.

Improper validation vulnerability in ucmRetParcelable of KnoxSDK prior to SMR Jul-2022 Release 1 allows attackers to launch certain activities.

An elevation of privilege vulnerability in Qualcomm closed source components. Product: Android. Versions: Android kernel. Android ID: A-36714120.

Uninitialized use in USB in Google Chrome prior to 88.0.4324.96 allowed a local attacker to potentially perform out of bounds memory access via via a USB device.

Integer overflow in IAudioPolicyService.cpp in Android allows local users to gain privileges via a crafted application, aka Android Bug ID 19261727.

In the SetupWizard, there is a possible Factory Reset Protection bypass due to a permissions bypass. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android Versions: Android-7.0 Android-7.1.1 Android-7.1.2 Android-8.0 Android-8.1 Android-9.0 Android ID: A-110034419

In nfc_llcp_build_sdreq_tlv of llcp_commands.c, 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. Product: Android. Versions: Android kernel. Android ID: A-73083945.

In driver_override_store of bus.c, there is a possible out of bounds write due to an incorrect bounds check. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation. Product: Android Versions: Android kernel Android ID: A-74128061 References: Upstream kernel.

In copy_process of fork.c, there is possible memory corruption due to a double free. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android Versions: Android kernel Android ID: A-111081202 References: N/A

On Pixel devices there is a bug causing verified boot to show the same certificate fingerprint despite using different signing keys. This may lead to local escalation of privilege if people are relying on those fingerprints to determine what version of the OS the device is running, with System execution privileges needed. User interaction is not needed for exploitation. Product: Android. Versions: Android kernel. Android ID: A-65543936.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, Out of bound mask range access caused by using possible old value of msg mask table count while copying masks to userspace.

In all android releases (Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, a potential buffer over flow could occur while processing the ndp event due to lack of check on the message length.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, improper access control can lead to device node and executable to be run from /cache/ which presents a potential issue.

In all android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the linux kernel, improper configuration of script may lead to unprivileged access.