TensorFlow is an open source platform for machine learning. If `QuantizedMatMul` is given nonscalar input for: `min_a`, `max_a`, `min_b`, or `max_b` It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. If `EmptyTensorList` receives an input `element_shape` with more than one dimension, it gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. When `CollectiveGather` receives an scalar input `input`, it gives a `CHECK` fails that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c1f491817dec39a26be3c574e86a88c30f3c4770. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. When `tf.quantization.fake_quant_with_min_max_vars_gradient` receives input `min` or `max` that is nonscalar, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. When `tensorflow::full_type::SubstituteFromAttrs` receives a `FullTypeDef& t` that is not exactly three args, it triggers a `CHECK`-fail instead of returning a status. We have patched the issue in GitHub commit 6104f0d4091c260ce9352f9155f7e9b725eab012. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. If `LRNGrad` is given an `output_image` input tensor that is not 4-D, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bd90b3efab4ec958b228cd7cfe9125be1c0cf255. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

In ril, there is a possible system crash due to an incorrect bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS07257259; Issue ID: ALPS07257259.

A parsing issue with binary data in protobuf-java core and lite versions prior to 3.21.7, 3.20.3, 3.19.6 and 3.16.3 can lead to a denial of service attack. Inputs containing multiple instances of non-repeated embedded messages with repeated or unknown fields causes objects to be converted back-n-forth between mutable and immutable forms, resulting in potentially long garbage collection pauses. We recommend updating to the versions mentioned above.

In bindArtworkAndColors of MediaControlPanel.java, there is a possible way to crash the phone due to improper input validation. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-13Android ID: A-239368697

In Message and toBundle of Notification.java, there is a possible UI slowdown or crash due to improper input validation. This could lead to remote denial of service if a malicious contact file is received, with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-10 Android-11 Android-8.0 Android-8.1 Android-9Android ID: A-147358092

In Bluetooth, there is possible controlled termination due to a missing bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Product: AndroidVersions: Android-10Android ID: A-112923309

In Bluetooth, there is possible controlled termination due to a missing bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Product: AndroidVersions: Android-10Android ID: A-116357965

In Bluetooth, there is possible controlled termination due to a missing bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Product: AndroidVersions: Android-10Android ID: A-115747410

In Bluetooth, there is possible controlled termination due to a missing bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Product: AndroidVersions: Android-10Android ID: A-115747155

In Bluetooth, there is possible controlled termination due to a missing bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Product: AndroidVersions: Android-10Android ID: A-115745406

In Bluetooth, there is possible controlled termination due to a missing bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Product: AndroidVersions: Android-10Android ID: A-116351796

In Bluetooth, there is possible controlled termination due to a missing bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Product: AndroidVersions: Android-10Android ID: A-115375248

In wlan firmware, there is a possible firmware assertion due to improper input handling. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS07932637; Issue ID: ALPS07932637.

TensorFlow is an open source platform for machine learning. The implementation of tf.reshape op in TensorFlow is vulnerable to a denial of service via CHECK-failure (assertion failure) caused by overflowing the number of elements in a tensor. This issue has been patched in GitHub commit 61f0f9b94df8c0411f0ad0ecc2fec2d3f3c33555. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. When `SetSize` receives an input `set_shape` that is not a 1D tensor, it gives a `CHECK` fails that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit cf70b79d2662c0d3c6af74583641e345fc939467. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. When `DrawBoundingBoxes` receives an input `boxes` that is not of dtype `float`, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit da0d65cdc1270038e72157ba35bf74b85d9bda11. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. When `tf.random.gamma` receives large input shape and rates, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit 552bfced6ce4809db5f3ca305f60ff80dd40c5a3. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. The `UnbatchGradOp` function takes an argument `id` that is assumed to be a scalar. A nonscalar `id` can trigger a `CHECK` failure and crash the program. It also requires its argument `batch_index` to contain three times the number of elements as indicated in its `batch_index.dim_size(0)`. An incorrect `batch_index` can trigger a `CHECK` failure and crash the program. We have patched the issue in GitHub commit 5f945fc6409a3c1e90d6970c9292f805f6e6ddf2. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. When `tf.linalg.matrix_rank` receives an empty input `a`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c55b476aa0e0bd4ee99d0f3ad18d9d706cd1260a. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. The implementation of `AvgPool3DGradOp` does not fully validate the input `orig_input_shape`. This results in an overflow that results in a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 9178ac9d6389bdc54638ab913ea0e419234d14eb. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. If `Save` or `SaveSlices` is run over tensors of an unsupported `dtype`, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 5dd7b86b84a864b834c6fa3d7f9f51c87efa99d4. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. If `SparseBincount` is given inputs for `indices`, `values`, and `dense_shape` that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. When `TensorListFromTensor` receives an `element_shape` of a rank greater than one, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit 3db59a042a38f4338aa207922fa2f476e000a6ee. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. The implementation of SobolSampleOp is vulnerable to a denial of service via CHECK-failure (assertion failure) caused by assuming `input(0)`, `input(1)`, and `input(2)` to be scalar. This issue has been patched in GitHub commit c65c67f88ad770662e8f191269a907bf2b94b1bf. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. The implementation of `Conv2DBackpropInput` requires `input_sizes` to be 4-dimensional. Otherwise, it gives a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 50156d547b9a1da0144d7babe665cf690305b33c. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. When `TensorListScatter` and `TensorListScatterV2` receive an `element_shape` of a rank greater than one, they give a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit bb03fdf4aae944ab2e4b35c7daa051068a8b7f61. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. When `AudioSummaryV2` receives an input `sample_rate` with more than one element, it gives a `CHECK` fails that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bf6b45244992e2ee543c258e519489659c99fb7f. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

TensorFlow is an open source platform for machine learning. The implementation of `FractionalAvgPoolGrad` does not fully validate the input `orig_input_tensor_shape`. This results in an overflow that results in a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 03a659d7be9a1154fdf5eeac221e5950fec07dad. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

In isWordBreakAfter of LayoutUtils.cpp, there is a possible way to slow or crash a TextView due to improper input validation. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Product: Android; Versions: Android-9, Android-10, Android-11, Android-8.0, Android-8.1; Android ID: A-170968514.

TensorFlow is an open source platform for machine learning. `DenseBincount` assumes its input tensor `weights` to either have the same shape as its input tensor `input` or to be length-0. A different `weights` shape will trigger a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bf4c14353c2328636a18bfad1e151052c81d5f43. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Improper access control for some Intel Unison software may allow an unauthenticated user to potentially enable denial of service via network access.

Remote prevention of access to cellular service with no user interaction (for example, crashing the cellular radio service with a malformed packet)

In on_create_record_event of btif_sdp_server.cc, there is a possible out of bounds read due to a missing null check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-13Android ID: A-263545186

In doInBackground of NotificationContentInflater.java, there is a possible temporary denial or service due to long running operations. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-11 Android-12 Android-12L Android-13Android ID: A-252766417

In LogResponse of Dns.cpp, there is a possible out of bounds read due to a missing bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-13Android ID: A-261079188

In wlan firmware, there is possible system crash due to an uncaught exception. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS07664720; Issue ID: ALPS07664720.

Product: AndroidVersions: Android kernelAndroid ID: A-229255400References: N/A

In wlan firmware, there is possible system crash due to an integer overflow. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS07664735; Issue ID: ALPS07664735.

In wlan firmware, there is possible system crash due to an integer overflow. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS07664731; Issue ID: ALPS07664731.

In wlan firmware, there is possible system crash due to an integer overflow. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS07664741; Issue ID: ALPS07664741.

In wlan firmware, there is possible system crash due to an uncaught exception. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS07664711; Issue ID: ALPS07664711.

Calling of non-existent provider in MobileWips application prior to SMR Feb-2021 Release 1 allows unauthorized actions including denial of service attack by hijacking the provider.

An issue in protobuf-java allowed the interleaving of com.google.protobuf.UnknownFieldSet fields in such a way that would be processed out of order. A small malicious payload can occupy the parser for several minutes by creating large numbers of short-lived objects that cause frequent, repeated pauses. We recommend upgrading libraries beyond the vulnerable versions.

In Telephony, there is a possible out of bounds read due to a missing bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation. Patch ID: ALPS09289881; Issue ID: MSV-2023.