TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.RaggedTensorToVariant` with arguments specifying an invalid ragged tensor results in a null pointer dereference. The implementation of `RaggedTensorToVariant` operations(https://github.com/tensorflow/tensorflow/blob/904b3926ed1c6c70380d5313d282d248a776baa1/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L39-L40) does not validate that the ragged tensor argument is non-empty. Since `batched_ragged` contains no elements, `batched_ragged.splits` is a null vector, thus `batched_ragged.splits(0)` will result in dereferencing `nullptr`. 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.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.SparseFillEmptyRows`. This is because of missing validation(https://github.com/tensorflow/tensorflow/blob/fdc82089d206e281c628a93771336bf87863d5e8/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L230-L231) that was covered under a `TODO`. If the `dense_shape` tensor is empty, then `dense_shape_t.vec<>()` would cause a null pointer dereference in the implementation of the op. 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.

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.SdcaOptimizer` triggers undefined behavior due to dereferencing a null pointer. The implementation(https://github.com/tensorflow/tensorflow/blob/60a45c8b6192a4699f2e2709a2645a751d435cc3/tensorflow/core/kernels/sdca_internal.cc) does not validate that the user supplied arguments satisfy all constraints expected by the op(https://www.tensorflow.org/api_docs/python/tf/raw_ops/SdcaOptimizer). 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.

TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. 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.

TensorFlow is an end-to-end open source platform for machine learning. Calling TF operations with tensors of non-numeric types when the operations expect numeric tensors result in null pointer dereferences. The conversion from Python array to C++ array(https://github.com/tensorflow/tensorflow/blob/ff70c47a396ef1e3cb73c90513da4f5cb71bebba/tensorflow/python/lib/core/ndarray_tensor.cc#L113-L169) is vulnerable to a type confusion. 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.

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPool3DGradGrad` exhibits undefined behavior by dereferencing null pointers backing attacker-supplied empty tensors. The implementation(https://github.com/tensorflow/tensorflow/blob/72fe792967e7fd25234342068806707bbc116618/tensorflow/core/kernels/pooling_ops_3d.cc#L679-L703) fails to validate that the 3 tensor inputs are not empty. If any of them is empty, then accessing the elements in the tensor results in dereferencing a null pointer. 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 the cpuidle driver in all Android releases(Android for MSM, Firefox OS for MSM, QRD Android) from CAF using the Linux kernel, the list_for_each macro was not used correctly which could lead to an untrusted pointer dereference.

A vulnerability in mfc driver prior to SMR Oct-2021 Release 1 allows memory corruption via NULL-pointer dereference.

NULL pointer dereference vulnerability in ION driver prior to SMR Sep-2021 Release 1 allows attackers to cause memory corruption.

NULL pointer dereference vulnerability in NPU driver prior to SMR Sep-2021 Release 1 allows attackers to cause memory corruption.

In soter service, there is a possible missing permission check. This could lead to local denial of service with no additional execution privileges.

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.

In cd_SsParseMsg of cd_SsCodec.c, there is a possible crash 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 kernelAndroid ID: A-244448906References: N/A

there is a possible Null Pointer Dereference (modem crash) 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.

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

In multiple locations, there is a possible permissions bypass due to a missing null check. This could lead to local escalation of privilege with no additional execution privileges needed. User interaction is not needed for exploitation.

A nullptr dereference in WebAssembly in Google Chrome prior to 66.0.3359.117 allowed a remote attacker to potentially perform out of bounds memory access via a crafted HTML page.

The updateMessageStatus function in Android 5.1.1 and earlier allows local users to cause a denial of service (NULL pointer exception and process crash).

In Core Kernel in all Android releases from CAF using the Linux kernel, a Null Pointer Dereference vulnerability could potentially exist.

In TrustZone in all Android releases from CAF using the Linux kernel, an Untrusted Pointer Dereference vulnerability could potentially exist.

In all Android releases from CAF using the Linux kernel, an untrusted pointer dereference vulnerability exists in WideVine DRM.

In all Qualcomm products with Android releases from CAF using the Linux kernel, disabling asserts can potentially cause a NULL pointer dereference during an out-of-memory condition.

In ss_SendCallBarringPwdRequiredIndMsg of ss_CallBarring.c, there is a possible null pointer deref 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.

In Qualcomm Android for MSM, Firefox OS for MSM, and QRD Android with all Android releases from CAF using the Linux kernel before security patch level 2018-04-05, untrusted pointer dereference in apr_cb_func can lead to an arbitrary code execution.

there is a possible way to crash the modem 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.

TensorFlow is an open source platform for machine learning. When `mlir::tfg::TFOp::nameAttr` receives null type list attributes, it crashes. We have patched the issue in GitHub commits 3a754740d5414e362512ee981eefba41561a63a6 and a0f0b9a21c9270930457095092f558fbad4c03e5. 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 gives a null dereference. We have patched the issue in GitHub commit 1cf45b831eeb0cab8655c9c7c5d06ec6f45fc41b. 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::GraphDefImporter::ConvertNodeDef` tries to convert NodeDefs without an op name, it crashes. We have patched the issue in GitHub commit a0f0b9a21c9270930457095092f558fbad4c03e5. 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 `LowerBound` or `UpperBound` is given an empty`sorted_inputs` input, it results in a `nullptr` dereference, leading to a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bce3717eaef4f769019fd18e990464ca4a2efeea. 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 end-to-end open source platform for machine learning. The implementation of TrySimplify(https://github.com/tensorflow/tensorflow/blob/c22d88d6ff33031aa113e48aa3fc9aa74ed79595/tensorflow/core/grappler/optimizers/arithmetic_optimizer.cc#L390-L401) has undefined behavior due to dereferencing a null pointer in corner cases that result in optimizing a node with no inputs. 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.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a dereference of a null pointer in `tf.raw_ops.StringNGrams`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L67-L74) does not fully validate the `data_splits` argument. This would result in `ngrams_data`(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L106-L110) to be a null pointer when the output would be computed to have 0 or negative size. Later writes to the output tensor would then cause a null pointer dereference. 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.

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.

NVIDIA SHIELD TV, all versions prior to 8.2.2, contains a vulnerability in the NVHost function, which may lead to abnormal reboot due to a null pointer reference, causing data loss.

In btif_in_hf_client_generic_evt of btif_hf_client.cc, there is a possible Bluetooth service crash 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-12Android ID: A-180420059

A flaw was found in Shim when an error happened while creating a new ESL variable. If Shim fails to create the new variable, it tries to print an error message to the user; however, the number of parameters used by the logging function doesn't match the format string used by it, leading to a crash under certain circumstances.

A Null pointer dereference problem was found in ida_free in lib/idr.c in the Linux Kernel. This issue may allow an attacker using this library to cause a denial of service problem due to a missing check at a function return.

In the Linux kernel, the following vulnerability has been resolved: media: vidtv: psi: Add check for kstrdup Add check for the return value of kstrdup() and return the error if it fails in order to avoid NULL pointer dereference.

In the Linux kernel, the following vulnerability has been resolved: mfd: qcom-spmi-pmic: Fix revid implementation The Qualcomm SPMI PMIC revid implementation is broken in multiple ways. First, it assumes that just because the sibling base device has been registered that means that it is also bound to a driver, which may not be the case (e.g. due to probe deferral or asynchronous probe). This could trigger a NULL-pointer dereference when attempting to access the driver data of the unbound device. Second, it accesses driver data of a sibling device directly and without any locking, which means that the driver data may be freed while it is being accessed (e.g. on driver unbind). Third, it leaks a struct device reference to the sibling device which is looked up using the spmi_device_from_of() every time a function (child) device is calling the revid function (e.g. on probe). Fix this mess by reimplementing the revid lookup so that it is done only at probe of the PMIC device; the base device fetches the revid info from the hardware, while any secondary SPMI device fetches the information from the base device and caches it so that it can be accessed safely from its children. If the base device has not been probed yet then probe of a secondary device is deferred.

In the Linux kernel, the following vulnerability has been resolved: drm: bridge: it66121: Fix invalid connector dereference Fix the NULL pointer dereference when no monitor is connected, and the sound card is opened from userspace. Instead return an empty buffer (of zeroes) as the EDID information to the sound framework if there is no connector attached.

In the Linux kernel, the following vulnerability has been resolved: clk: mediatek: clk-mt7629: Add check for mtk_alloc_clk_data Add the check for the return value of mtk_alloc_clk_data() in order to avoid NULL pointer dereference.

In the Linux kernel, the following vulnerability has been resolved: scsi: pm80xx: Do not call scsi_remove_host() in pm8001_alloc() Calling scsi_remove_host() before scsi_add_host() results in a crash: BUG: kernel NULL pointer dereference, address: 0000000000000108 RIP: 0010:device_del+0x63/0x440 Call Trace: device_unregister+0x17/0x60 scsi_remove_host+0xee/0x2a0 pm8001_pci_probe+0x6ef/0x1b90 [pm80xx] local_pci_probe+0x3f/0x90 We cannot call scsi_remove_host() in pm8001_alloc() because scsi_add_host() has not been called yet at that point in time. Function call tree: pm8001_pci_probe() | `- pm8001_pci_alloc() | | | `- pm8001_alloc() | | | `- scsi_remove_host() | `- scsi_add_host()

AIDE is an advanced intrusion detection environment. From versions 0.13 to 0.19.1, there is a null pointer dereference vulnerability in AIDE. An attacker can crash the program during report printing or database listing after setting extended file attributes with an empty attribute value or with a key containing a comma. A local user might exploit this to cause a local denial of service. This issue has been patched in version 0.19.2. A workaround involves removing xattrs group from rules matching files on affected file systems.

An issue was discovered in Xen through 4.14.x. A bounds check common to most operation time functions specific to FIFO event channels depends on the CPU observing consistent state. While the producer side uses appropriately ordered writes, the consumer side isn't protected against re-ordered reads, and may hence end up de-referencing a NULL pointer. Malicious or buggy guest kernels can mount a Denial of Service (DoS) attack affecting the entire system. Only Arm systems may be vulnerable. Whether a system is vulnerable depends on the specific CPU. x86 systems are not vulnerable.

Mesa v23.0.4 was discovered to contain a NULL pointer dereference via the function dri2GetGlxDrawableFromXDrawableId(). This vulnerability is triggered when the X11 server sends an DRI2_BufferSwapComplete event unexpectedly when the application is using DRI3. NOTE: this is disputed because there is no scenario in which the vulnerability was demonstrated.

Tex Live 944e257 has a NULL pointer dereference in texk/web2c/pdftexdir/writet1.c. NOTE: this is disputed because it should be categorized as a usability problem.

OpenEXR provides the specification and reference implementation of the EXR file format, an image storage format for the motion picture industry. In version 3.3.2, when reading a deep scanline image with a large sample count in reduceMemory mode, it is possible to crash a target application with a NULL pointer dereference in a write operation. This is fixed in version 3.3.3.

Memory corruption during buffer allocation due to dereferencing session ctx pointer without checking if pointer is valid in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Mobile

The bundle management subsystem within OpenHarmony-v3.1.4 and prior versions has a null pointer reference vulnerability which local attackers can exploit this vulnerability to cause a DoS attack to the system when installing a malicious HAP package.

A null pointer dereference may potentially occur during RSA key import in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables