In cdev_get of char_dev.c, there is a possible use-after-free due to a race condition. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10Android ID: A-153467744
In onCreate of SettingsBaseActivity.java, there is a possible unauthorized setting modification due to a permissions bypass. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is needed for exploitation.Product: AndroidVersions: Android-8.1 Android-9 Android-10 Android-8.0Android ID: A-137015265
In SurfaceFlinger, it is possible to override UI confirmation screen protected by the TEE. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-143128911
In System Settings, there is a possible permissions bypass due to a cached Linux user ID. This could lead to a local permissions bypass with no additional execution privileges needed. User interaction is needed for exploitation. Product: AndroidVersions: Android-10Android ID: A-36899497
In the Android kernel in the video driver there is a use after free due to a race condition. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.
In the Android kernel in the mnh driver there is a race condition due to insufficient locking. This could lead to a use-after-free which could lead to escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation.
In the Android kernel in the FingerTipS touchscreen driver there is a possible memory corruption due to a race condition. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation.
In NFC, there is a possible out of bounds write due to a missing bounds check. This could lead to a to local escalation of privilege with no additional execution privileges needed. User interaction is needed for exploitation. Product: AndroidVersions: Android-10Android ID: A-117985575
Due to a race condition while processing the power stats debug file to read status, a double free condition 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.
Due to a race condition in a bus driver, a double free in msm_bus_floor_vote_context() can potentially occur in all Android releases from CAF (Android for MSM, Firefox OS for MSM, QRD Android) using the Linux Kernel.
In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, in the SPCom kernel driver, a race condition exists when creating a channel.
In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, race condition in diag_dbgfs_read_dcistats(), while accessing diag_dbgfs_dci_data_index, causes potential heap overflow.
In TBD of TBD, there is a possible user after free vulnerability due to a race condition. This could lead to local escalation of privilege with System execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-176918884References: N/A
In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, due to a race condition in a firmware loading routine, a buffer overflow could potentially occur if multiple user space threads try to update the WLAN firmware file through sysfs.
In Android for MSM, Firefox OS for MSM, QRD Android, with all Android releases from CAF using the Linux kernel, in a video driver, a race condition exists which can potentially lead to a buffer overflow.
In HalCamera::requestNewFrame of HalCamera.cpp, there is a possible use-after-free due to a race condition. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11Android ID: A-169282240
In MockLocationAppPreferenceController.java, it is possible to mock the GPS location of the device due to a permissions bypass. This could lead to local escalation of privilege with User execution privileges needed. User interaction is needed for exploitation.Product: AndroidVersions: Android-10Android ID: A-145136060
In CamX code, there is a possible use after free due to a race condition. This could lead to local escalation of privilege with System execution privileges required. User interaction is not needed for exploitation.Product: AndroidVersions: Android kernelAndroid ID: A-123999783
In BroadcastController.java of registerReceiverWithFeatureTraced, there is a possible way to receive broadcasts meant for the "android" package 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.
In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the `splits` tensor has the minimum required number of elements. Code uses this quantity to initialize a different data structure. Since `BatchedMap` is equivalent to a vector, it needs to have at least one element to not be `nullptr`. If user passes a `splits` tensor that is empty or has exactly one element, we get a `SIGABRT` signal raised by the operating system. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
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 collectOps of AppOpsService.java, there is a possible way to cause permanent DoS due to improper input validation. This could lead to local denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.
Incorrect security UI in MacOS services integration in Google Chrome on OS X prior to 76.0.3809.87 allowed a local attacker to execute arbitrary code via a crafted HTML page.
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.DeleteSessionTensor` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Insufficient validation of untrusted input in Permissions in Google Chrome prior to 148.0.7778.96 allowed an attacker on the local network segment to leak cross-origin data via malicious network traffic. (Chromium security severity: Medium)
Insufficient validation of untrusted input in SiteIsolation in Google Chrome prior to 148.0.7778.96 allowed a remote attacker who had compromised the renderer process to bypass site isolation via a crafted HTML page. (Chromium security severity: Low)
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `SparseFillEmptyRowsGrad` implementation has incomplete validation of the shapes of its arguments. Although `reverse_index_map_t` and `grad_values_t` are accessed in a similar pattern, only `reverse_index_map_t` is validated to be of proper shape. Hence, malicious users can pass a bad `grad_values_t` to trigger an assertion failure in `vec`, causing denial of service in serving installations. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1."
Insufficient policy enforcement in Blink in Google Chrome prior to 73.0.3683.75 allowed a remote attacker to bypass content security policy via a crafted HTML page.
Improper input validation in Settings prior to SMR-May-2022 Release 1 allows attackers to launch arbitrary activity with system privilege. The patch adds proper validation logic to check the caller.
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, by controlling the `fill` argument of tf.strings.as_string, a malicious attacker is able to trigger a format string vulnerability due to the way the internal format use in a `printf` call is constructed. This may result in segmentation fault. The issue is patched in commit 33be22c65d86256e6826666662e40dbdfe70ee83, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Inappropriate implementation in JavaScript in Google Chrome prior to 76.0.3809.87 allowed a remote attacker to obtain potentially sensitive information from process memory via a crafted HTML page.
In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `tf.raw_ops.Switch` operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is `nullptr`, hence we are binding a reference to `nullptr`. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
The is_ashmem_file function in drivers/staging/android/ashmem.c in a certain Qualcomm Innovation Center (QuIC) Android patch for the Linux kernel 3.x mishandles pointer validation within the KGSL Linux Graphics Module, which allows attackers to bypass intended access restrictions by using the /ashmem string as the dentry name.
Insufficient policy enforcement in storage in Google Chrome prior to 76.0.3809.87 allowed a remote attacker who had compromised the renderer process to bypass site isolation via a crafted HTML page.
Incorrect inheritance of a new document's policy in Content Security Policy in Google Chrome prior to 73.0.3683.75 allowed a remote attacker to bypass content security policy via a crafted HTML page.
Insufficient data validation in CORS in Google Chrome prior to 76.0.3809.87 allowed an attacker who convinced a user to install a malicious extension to bypass content security policy via a crafted Chrome Extension.
Insufficient data validation in AppCache in Google Chrome prior to 76.0.3809.87 allowed a remote attacker who had compromised the renderer process to bypass site isolation via a crafted HTML page.
Insufficient policy enforcement in extensions in Google Chrome prior to 73.0.3683.75 allowed a remote attacker to initiate the extensions installation user interface via a crafted HTML page.
Improper validation of removing package name in Galaxy Themes prior to SMR May-2022 Release 1 allows attackers to uninstall arbitrary packages without permission. The patch adds proper validation logic for removing package name.
NVIDIA Shield TV Experience prior to v8.0.1, NVIDIA Tegra software contains a vulnerability in the bootloader, where it does not validate the fields of the boot image, which may lead to code execution, denial of service, escalation of privileges, and information disclosure.
In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Improper validation vulnerability in RemoteViews prior to SMR Jun-2022 Release 1 allows attackers to launch certain activities.
An issue was discovered on Samsung mobile devices with Q(10.0) software. Attackers can trigger an out-of-bounds access and device reset via a 4K wallpaper image because ImageProcessHelper mishandles boundary checks. The Samsung ID is SVE-2020-18056 (July 2020).
Missing URI encoding of untrusted input in DevTools in Google Chrome prior to 72.0.3626.81 allowed a remote attacker to perform a Dangling Markup Injection attack via a crafted HTML page.
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.TensorSummaryV2` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Insufficient validation of untrusted input in Cookies in Google Chrome prior to 148.0.7778.96 allowed a remote attacker to perform privilege escalation via a crafted HTML page. (Chromium security severity: Medium)
decoder/ih264d_parse_pslice.c in mediaserver in Android 6.x before 2016-07-01 does not properly select concealment frames, which allows remote attackers to cause a denial of service (device hang or reboot) via a crafted media file, aka internal bug 28470138.
Insufficient restrictions on what can be done with Apple Events in Google Chrome on macOS prior to 72.0.3626.81 allowed a local attacker to execute JavaScript via Apple Events.
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.StagePeek` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `index` is a scalar but there is no validation for this before accessing its value. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.