NULL pointer dereference in Google TensorFlow before 1.12.2 could cause a denial of service via an invalid GIF file.

In libhevc, there is a possible out of bounds read due to an integer overflow. This could lead to remote denial of service with no additional execution privileges needed. User interaction is needed for exploitation. Product: AndroidVersions: Android-10Android ID: A-111272481

Out of bounds read in JavaScript in Google Chrome prior to 76.0.3809.100 allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page.

Object lifetime issue in Blink in Google Chrome prior to 72.0.3626.121 allowed a remote attacker to potentially perform out of bounds memory access via a crafted HTML page.

Unspecified vulnerability in Google Chrome before 9.0.597.84 allows user-assisted remote attackers to cause a denial of service (application crash) via vectors involving a "bad volume setting."

TensorFlow is an open source platform for machine learning. If `RaggedTensorToVariant` is given a `rt_nested_splits` list that contains tensors of ranks 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 88f93dfe691563baa4ae1e80ccde2d5c7a143821. 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. `ParameterizedTruncatedNormal` assumes `shape` is of type `int32`. A valid `shape` of type `int64` results in a mismatched type `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 72180be03447a10810edca700cbc9af690dfeb51. 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 `Unbatch` receives a nonscalar input `id`, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit 4419d10d576adefa36b0e0a9425d2569f7c0189f. 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.

The WebSockets implementation in Google Chrome before 6.0.472.53 allows remote attackers to cause a denial of service (NULL pointer dereference and application crash) via unspecified vectors.

libxslt, as used in Google Chrome before 17.0.963.46, allows remote attackers to cause a denial of service (out-of-bounds read) via unspecified vectors.

Use-after-free vulnerability in Google Chrome before 17.0.963.46 allows remote attackers to cause a denial of service or possibly have unspecified other impact via vectors involving Cascading Style Sheets (CSS) token sequences.

Integer underflow in net/base/escape.cc in chrome.dll in Google Chrome 0.2.149.27 allows remote attackers to cause a denial of service (browser crash) via a URI with an invalid handler followed by a "%" (percent) character, which triggers a buffer over-read, as demonstrated using an "about:%" URI.

Google TensorFlow 1.6.x and earlier is affected by: Null Pointer Dereference. The type of exploitation is: context-dependent.

Out of bounds array access in WebRTC in Google Chrome prior to 67.0.3396.62 allowed a remote attacker to potentially perform out of bounds memory access via a crafted HTML page.

Insufficient validation in V8 in Google Chrome prior to 67.0.3396.62 allowed a remote attacker to perform an out of bounds memory read via a crafted HTML page.

Incorrect handling of object lifetimes in WebRTC in Google Chrome prior to 67.0.3396.62 allowed a remote attacker to potentially perform out of bounds memory access via a crafted HTML page.

A heap buffer overflow in GPU in Google Chrome prior to 70.0.3538.67 allowed a remote attacker who had compromised the renderer process to potentially perform a sandbox escape via a crafted HTML page.

An out of bounds read in Swiftshader in Google Chrome prior to 69.0.3497.81 allowed a remote attacker to potentially perform out of bounds memory access via a crafted HTML page.

Google Chrome before 17.0.963.46 does not properly decode audio data, which allows remote attackers to cause a denial of service (out-of-bounds read) via unspecified vectors.

Unbounded memory allocation in Google Guava 11.0 through 24.x before 24.1.1 allows remote attackers to conduct denial of service attacks against servers that depend on this library and deserialize attacker-provided data, because the AtomicDoubleArray class (when serialized with Java serialization) and the CompoundOrdering class (when serialized with GWT serialization) perform eager allocation without appropriate checks on what a client has sent and whether the data size is reasonable.

TensorFlow is an open source platform for machine learning. In affected versions the code behind `tf.function` API can be made to deadlock when two `tf.function` decorated Python functions are mutually recursive. This occurs due to using a non-reentrant `Lock` Python object. Loading any model which contains mutually recursive functions is vulnerable. An attacker can cause denial of service by causing users to load such models and calling a recursive `tf.function`, although this is not a frequent scenario. 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.

In reinit of HeifDecoderImpl.cpp, there is a possible crash due to a missing null check. This could lead to remote persistent denial of service in the file picker with no additional execution privileges needed. User interaction is needed for exploitation.Product: AndroidVersions: Android-11 Android-12 Android-12LAndroid ID: A-215002587

FFmpeg in Google Chrome prior to 56.0.2924.76 for Linux, Windows and Mac, failed to perform proper bounds checking, which allowed a remote attacker to potentially exploit heap corruption via a crafted video file.

FFmpeg in Google Chrome prior to 56.0.2924.76 for Linux, Windows and Mac, failed to perform proper bounds checking, which allowed a remote attacker to potentially exploit heap corruption via a crafted video file.

Type confusion in Histogram in Google Chrome prior to 56.0.2924.76 for Linux, Windows and Mac, and 56.0.2924.87 for Android, allowed a remote attacker to potentially exploit a near null dereference via a crafted HTML page.

A use after free in Google Chrome prior to 56.0.2924.76 for Linux, Windows and Mac, and 56.0.2924.87 for Android, allowed a remote attacker to perform an out of bounds memory read via a crafted HTML page.

Integer overflow in international date handling in International Components for Unicode (ICU) for C/C++ before 60.1, as used in V8 in Google Chrome prior to 63.0.3239.84 and other products, allowed a remote attacker to perform an out of bounds memory read via a crafted HTML page.

A stack buffer overflow in NumberingSystem in International Components for Unicode (ICU) for C/C++ before 60.2, as used in V8 in Google Chrome prior to 62.0.3202.75 and other products, allowed a remote attacker to potentially exploit heap corruption via a crafted HTML page.

Google Chrome before 17.0.963.56 does not properly perform a cast of an unspecified variable during handling of columns, which allows remote attackers to cause a denial of service or possibly have unknown other impact via a crafted document.

Google Chrome before 17.0.963.56 does not properly parse H.264 data, which allows remote attackers to cause a denial of service (out-of-bounds read) via unspecified vectors.

Google V8, as used in Google Chrome before 17.0.963.83, allows remote attackers to cause a denial of service via vectors that trigger an invalid read operation.

Google Chrome before 17.0.963.56 allows remote attackers to cause a denial of service (application crash) via an empty X.509 certificate.

Google Chrome before 17.0.963.65 does not properly handle text, which allows remote attackers to cause a denial of service (out-of-bounds read) via a crafted document.

Use after free vulnerability exists in WebKit in Google Chrome before Blink M12 in RenderLayerwhen removing elements with reflections.

An issue exists in third_party/WebKit/Source/WebCore/svg/animation/SVGSMILElement.h in WebKit in Google Chrome before Blink M11 and M12 when trying to access a removed smil element.

An issue exists in WebKit in Google Chrome before Blink M12. when clearing lists in AnimationControllerPrivate that signal when a hardware animation starts.

The NPAPI implementation in Google Chrome before 12.0.742.112 does not properly handle strings, which allows remote attackers to cause a denial of service (out-of-bounds read) via unspecified vectors.

Incorrect handling of timer information in Timer.cpp in WebKit in Google Chrome before Blink M13.

WebKit in Google Chrome before Blink M11 and M12 does not properly handle counter nodes, which allows remote attackers to cause a denial of service (memory corruption).

The WebSockets implementation in Google Chrome before 14.0.835.163 allows remote attackers to cause a denial of service (NULL pointer dereference and application crash) via unspecified vectors.

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. The `RaggedRangOp` function takes an argument `limits` that is eventually used to construct a `TensorShape` as an `int64`. If `limits` is a very large float, it can overflow when converted to an `int64`. This triggers an `InvalidArgument` but also throws an abort signal that crashes the program. We have patched the issue in GitHub commit 37cefa91bee4eace55715eeef43720b958a01192. 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 `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 `Conv2DBackpropInput` receives empty `out_backprop` inputs (e.g. `[3, 1, 0, 1]`), the current CPU/GPU kernels `CHECK` fail (one with dnnl, the other with cudnn). This can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 27a65a43cf763897fecfa5cdb5cc653fc5dd0346. 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 `MaxPool` receives a window size input array `ksize` with dimensions greater than its input tensor `input`, 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 32d7bd3defd134f21a4e344c8dfd40099aaf6b18. 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.

TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, 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 `RandomPoissonV2` 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. The `AvgPoolOp` function takes an argument `ksize` that must be positive but is not checked. A negative `ksize` can trigger a `CHECK` failure and crash the program. 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 to this issue.