In Minikin, there is a possible way to trigger ANR by showing a malicious message due to resource exhaustion. This could lead to remote denial of service with no additional execution privileges needed. User interaction is not needed for exploitation.

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 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 Messaging, there is a possible way to disable the messaging application 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.

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.

In wifi driver, there is a possible system crash 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: ALPS05551397; Issue ID: ALPS05551397.

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: ALPS07664735; Issue ID: ALPS07664735.

Product: AndroidVersions: Android kernelAndroid ID: A-210916981References: N/A

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.

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.

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. Fixed were added in commits f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. The issue is patched in commit adf095206f25471e864a8e63a0f1caef53a0e3a6, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

In Tensorflow before version 2.4.0, when the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

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 before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

A drm driver have oob problem, could cause the system crash or EOPProduct: AndroidVersions: Android SoCAndroid ID: A-233124709

In ElementaryStreamQueue::dequeueAccessUnitMPEG4Video of ESQueue.cpp, there is a possible infinite loop leading to resource exhaustion due to an incorrect bounds check. This could lead to remote denial of service with no additional execution privileges needed. User interaction is needed for exploitation.

Use after free in Ozone in Google Chrome prior to 101.0.4951.41 allowed a remote attacker to potentially exploit heap corruption via running a Wayland test.

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.

TensorFlow is an open source platform for machine learning. If `MirrorPadGrad` is given outsize input `paddings`, TensorFlow will give a heap OOB error. We have patched the issue in GitHub commit 717ca98d8c3bba348ff62281fdf38dcb5ea1ec92. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. If `FractionMaxPoolGrad` is given outsize inputs `row_pooling_sequence` and `col_pooling_sequence`, TensorFlow will crash. We have patched the issue in GitHub commit d71090c3e5ca325bdf4b02eb236cfb3ee823e927. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. If `ThreadUnsafeUnigramCandidateSampler` is given input `filterbank_channel_count` greater than the allowed max size, TensorFlow will crash. We have patched the issue in GitHub commit 39ec7eaf1428e90c37787e5b3fbd68ebd3c48860. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. When `tf.raw_ops.ImageProjectiveTransformV2` is given a large output shape, it overflows. We have patched the issue in GitHub commit 8faa6ea692985dbe6ce10e1a3168e0bd60a723ba. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. Inputs `dense_features` or `example_state_data` not of rank 2 will trigger a `CHECK` fail in `SdcaOptimizer`. We have patched the issue in GitHub commit 80ff197d03db2a70c6a111f97dcdacad1b0babfa. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. An input `sparse_matrix` that is not a matrix with a shape with rank 0 will trigger a `CHECK` fail in `tf.raw_ops.SparseMatrixNNZ`. We have patched the issue in GitHub commit f856d02e5322821aad155dad9b3acab1e9f5d693. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. If `tf.raw_ops.TensorListResize` is given a nonscalar value for input `size`, it results `CHECK` fail which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 888e34b49009a4e734c27ab0c43b0b5102682c56. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. If `tf.raw_ops.TensorListConcat` is given `element_shape=[]`, it results segmentation fault which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit fc33f3dc4c14051a83eec6535b608abe1d355fde. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. If `SparseFillEmptyRowsGrad` is given empty inputs, TensorFlow will crash. We have patched the issue in GitHub commit af4a6a3c8b95022c351edae94560acc61253a1b8. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. An input `token` that is not a UTF-8 bytestring will trigger a `CHECK` fail in `tf.raw_ops.PyFunc`. We have patched the issue in GitHub commit 9f03a9d3bafe902c1e6beb105b2f24172f238645. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. When `tf.raw_ops.ResizeNearestNeighborGrad` is given a large `size` input, it overflows. We have patched the issue in GitHub commit 00c821af032ba9e5f5fa3fe14690c8d28a657624. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. When `tf.raw_ops.FusedResizeAndPadConv2D` is given a large tensor shape, it overflows. We have patched the issue in GitHub commit d66e1d568275e6a2947de97dca7a102a211e01ce. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. When printing a tensor, we get it's data as a `const char*` array (since that's the underlying storage) and then we typecast it to the element type. However, conversions from `char` to `bool` are undefined if the `char` is not `0` or `1`, so sanitizers/fuzzers will crash. The issue has been patched in GitHub commit `1be74370327`. The fix will be included in TensorFlow 2.11.0. We will also cherrypick this commit on TensorFlow 2.10.1, TensorFlow 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. If `BCast::ToShape` is given input larger than an `int32`, it will crash, despite being supposed to handle up to an `int64`. An example can be seen in `tf.experimental.numpy.outer` by passing in large input to the input `b`. We have patched the issue in GitHub commit 8310bf8dd188ff780e7fc53245058215a05bdbe5. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. When running on GPU, `tf.image.generate_bounding_box_proposals` receives a `scores` input that must be of rank 4 but is not checked. We have patched the issue in GitHub commit cf35502463a88ca7185a99daa7031df60b3c1c98. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

TensorFlow is an open source platform for machine learning. If `QuantizeAndDequantizeV3` is given a nonscalar `num_bits` input tensor, 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 f3f9cb38ecfe5a8a703f2c4a8fead434ef291713. 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. 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. 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. 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. When `mlir::tfg::ConvertGenericFunctionToFunctionDef` is given empty function attributes, it crashes. We have patched the issue in GitHub commit ad069af92392efee1418c48ff561fd3070a03d7b. 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. 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. The implementation of `AvgPoolGrad` does not fully validate the input `orig_input_shape`. This results in a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 3a6ac52664c6c095aa2b114e742b0aa17fdce78f. 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 `FakeQuantWithMinMaxVarsPerChannel` is given `min` or `max` tensors of a rank other than one, 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 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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 `RangeSize` receives values that do not fit into an `int64_t`, it crashes. We have patched the issue in GitHub commit 37e64539cd29fcfb814c4451152a60f5d107b0f0. 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 `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. 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.