TensorFlow is an end-to-end open source platform for machine learning. When restoring tensors via raw APIs, if the tensor name is not provided, TensorFlow can be tricked into dereferencing a null pointer. Alternatively, attackers can read memory outside the bounds of heap allocated data by providing some tensor names but not enough for a successful restoration. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/save_restore_tensor.cc#L158-L159) retrieves the tensor list corresponding to the `tensor_name` user controlled input and immediately retrieves the tensor at the restoration index (controlled via `preferred_shard` argument). This occurs without validating that the provided list has enough values. If the list is empty this results in dereferencing a null pointer (undefined behavior). If, however, the list has some elements, if the restoration index is outside the bounds this results in heap OOB read. We have patched the issue in GitHub commit 9e82dce6e6bd1f36a57e08fa85af213e2b2f2622. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

TensorFlow is an end-to-end open source platform for machine learning. Sending invalid argument for `row_partition_types` of `tf.raw_ops.RaggedTensorToTensor` API results in a null pointer dereference and undefined behavior. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L328) accesses the first element of a user supplied list of values without validating that the provided list is not empty. We have patched the issue in GitHub commit 301ae88b331d37a2a16159b65b255f4f9eb39314. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all binary cwise operations that don't require broadcasting (e.g., gradients of binary cwise operations). The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/cwise_ops_common.h#L264) assumes that the two inputs have exactly the same number of elements but does not check that. Hence, when the eigen functor executes it triggers heap OOB reads and undefined behavior due to binding to nullptr. We have patched the issue in GitHub commit 93f428fd1768df147171ed674fee1fc5ab8309ec. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

A null pointer dereference flaw was found in the hugetlbfs_fill_super function in the Linux kernel hugetlbfs (HugeTLB pages) functionality. This issue may allow a local user to crash the system or potentially escalate their privileges on the system.

Possible null pointer dereference due to lack of WDOG structure validation during registration in Snapdragon Auto, Snapdragon Connectivity, Snapdragon Industrial IOT, Snapdragon Mobile

A null pointer dereference flaw was found in the nft_inner.c functionality of netfilter in the Linux kernel. This issue could allow a local user to crash the system or escalate their privileges on the system.

TensorFlow is an end-to-end open source platform for machine learning. The fix for CVE-2020-15209(https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15209) missed the case when the target shape of `Reshape` operator is given by the elements of a 1-D tensor. As such, the fix for the vulnerability(https://github.com/tensorflow/tensorflow/blob/9c1dc920d8ffb4893d6c9d27d1f039607b326743/tensorflow/lite/core/subgraph.cc#L1062-L1074) allowed passing a null-buffer-backed tensor with a 1D shape. 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.

Possible null pointer dereference in thread cache operation handler due to lack of validation of user provided input in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Voice & Music, Snapdragon Wearables, Snapdragon Wired Infrastructure and Networking

Possible null pointer dereference due to lack of TLB validation for user provided address in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Voice & Music, Snapdragon Wired Infrastructure and Networking

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.

Possible null pointer dereference in trap handler due to lack of thread ID validation before dereferencing it in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Voice & Music, Snapdragon Wearables, Snapdragon Wired Infrastructure and Networking

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference by providing an invalid `permutation` to `tf.raw_ops.SparseMatrixSparseCholesky`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/kernels/sparse/sparse_cholesky_op.cc#L85-L86) fails to properly validate the input arguments. Although `ValidateInputs` is called and there are checks in the body of this function, the code proceeds to the next line in `ValidateInputs` since `OP_REQUIRES`(https://github.com/tensorflow/tensorflow/blob/080f1d9e257589f78b3ffb75debf584168aa6062/tensorflow/core/framework/op_requires.h#L41-L48) is a macro that only exits the current function. Thus, the first validation condition that fails in `ValidateInputs` will cause an early return from that function. However, the caller will continue execution from the next line. The fix is to either explicitly check `context->status()` or to convert `ValidateInputs` to return a `Status`. 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. 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.

Possible null pointer dereference in thread profile trap handler due to lack of thread ID validation before dereferencing it in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Voice & Music, Snapdragon Wearables, Snapdragon Wired Infrastructure and Networking

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.

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. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, `ctx->session_state()` is nullptr and the call of the member function is 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.

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `MatrixDiag*` operations(https://github.com/tensorflow/tensorflow/blob/4c4f420e68f1cfaf8f4b6e8e3eb857e9e4c3ff33/tensorflow/core/kernels/linalg/matrix_diag_op.cc#L195-L197) does not validate that the tensor arguments are non-empty. 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.

A NULL pointer dereference vulnerability was found in netlink_dump. This issue can occur when the Netlink socket receives the message(sendmsg) for the XFRM_MSG_GETSA, XFRM_MSG_GETPOLICY type message, and the DUMP flag is set and can cause a denial of service or possibly another unspecified impact. Due to the nature of the flaw, privilege escalation cannot be fully ruled out, although it is unlikely.

NULL Pointer Dereference in GitHub repository gpac/gpac prior to 2.2.2.

NVIDIA Windows GPU Display Driver, all versions, contains a vulnerability in the kernel mode layer (nvlddmkm.sys) handler for DxgkDdiEscape, in which a NULL pointer is dereferenced, leading to denial of service or potential escalation of privileges.

A flaw null pointer dereference in the Linux kernel cgroupv2 subsystem in versions before 5.7.10 was found in the way when reboot the system. A local user could use this flaw to crash the system or escalate their privileges on the system.

In the Linux kernel, the following vulnerability has been resolved: ALSA: hda: Fix UAF of leds class devs at unbinding The LED class devices that are created by HD-audio codec drivers are registered via devm_led_classdev_register() and associated with the HD-audio codec device. Unfortunately, it turned out that the devres release doesn't work for this case; namely, since the codec resource release happens before the devm call chain, it triggers a NULL dereference or a UAF for a stale set_brightness_delay callback. For fixing the bug, this patch changes the LED class device register and unregister in a manual manner without devres, keeping the instances in hda_gen_spec.

A null pointer dereference issue was discovered in function gui_x11_create_blank_mouse in gui_x11.c in vim 8.1.2269 thru 9.0.0339 allows attackers to cause denial of service or other unspecified impacts.

A null pointer dereference issue was discovered in functions op_get_data and op_open1 in opusfile.c in xiph opusfile 0.9 thru 0.12 allows attackers to cause denial of service or other unspecified impacts.

kernel/trace/trace_syscalls.c in the Linux kernel through 3.17.2 does not properly handle private syscall numbers during use of the ftrace subsystem, which allows local users to gain privileges or cause a denial of service (invalid pointer dereference) via a crafted application.

x86 shadow paging arbitrary pointer dereference In environments where host assisted address translation is necessary but Hardware Assisted Paging (HAP) is unavailable, Xen will run guests in so called shadow mode. Due to too lax a check in one of the hypervisor routines used for shadow page handling it is possible for a guest with a PCI device passed through to cause the hypervisor to access an arbitrary pointer partially under guest control.

In onNullBinding of TileLifecycleManager.java, there is a possible way to launch an activity from the background 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.

In the Linux kernel, the following vulnerability has been resolved: smb: client: fix NULL ptr deref in crypto_aead_setkey() Neither SMB3.0 or SMB3.02 supports encryption negotiate context, so when SMB2_GLOBAL_CAP_ENCRYPTION flag is set in the negotiate response, the client uses AES-128-CCM as the default cipher. See MS-SMB2 3.3.5.4. Commit b0abcd65ec54 ("smb: client: fix UAF in async decryption") added a @server->cipher_type check to conditionally call smb3_crypto_aead_allocate(), but that check would always be false as @server->cipher_type is unset for SMB3.02. Fix the following KASAN splat by setting @server->cipher_type for SMB3.02 as well. mount.cifs //srv/share /mnt -o vers=3.02,seal,... BUG: KASAN: null-ptr-deref in crypto_aead_setkey+0x2c/0x130 Read of size 8 at addr 0000000000000020 by task mount.cifs/1095 CPU: 1 UID: 0 PID: 1095 Comm: mount.cifs Not tainted 6.12.0 #1 Hardware name: QEMU Standard PC (Q35 + ICH9, 2009), BIOS 1.16.3-3.fc41 04/01/2014 Call Trace: <TASK> dump_stack_lvl+0x5d/0x80 ? crypto_aead_setkey+0x2c/0x130 kasan_report+0xda/0x110 ? crypto_aead_setkey+0x2c/0x130 crypto_aead_setkey+0x2c/0x130 crypt_message+0x258/0xec0 [cifs] ? __asan_memset+0x23/0x50 ? __pfx_crypt_message+0x10/0x10 [cifs] ? mark_lock+0xb0/0x6a0 ? hlock_class+0x32/0xb0 ? mark_lock+0xb0/0x6a0 smb3_init_transform_rq+0x352/0x3f0 [cifs] ? lock_acquire.part.0+0xf4/0x2a0 smb_send_rqst+0x144/0x230 [cifs] ? __pfx_smb_send_rqst+0x10/0x10 [cifs] ? hlock_class+0x32/0xb0 ? smb2_setup_request+0x225/0x3a0 [cifs] ? __pfx_cifs_compound_last_callback+0x10/0x10 [cifs] compound_send_recv+0x59b/0x1140 [cifs] ? __pfx_compound_send_recv+0x10/0x10 [cifs] ? __create_object+0x5e/0x90 ? hlock_class+0x32/0xb0 ? do_raw_spin_unlock+0x9a/0xf0 cifs_send_recv+0x23/0x30 [cifs] SMB2_tcon+0x3ec/0xb30 [cifs] ? __pfx_SMB2_tcon+0x10/0x10 [cifs] ? lock_acquire.part.0+0xf4/0x2a0 ? __pfx_lock_release+0x10/0x10 ? do_raw_spin_trylock+0xc6/0x120 ? lock_acquire+0x3f/0x90 ? _get_xid+0x16/0xd0 [cifs] ? __pfx_SMB2_tcon+0x10/0x10 [cifs] ? cifs_get_smb_ses+0xcdd/0x10a0 [cifs] cifs_get_smb_ses+0xcdd/0x10a0 [cifs] ? __pfx_cifs_get_smb_ses+0x10/0x10 [cifs] ? cifs_get_tcp_session+0xaa0/0xca0 [cifs] cifs_mount_get_session+0x8a/0x210 [cifs] dfs_mount_share+0x1b0/0x11d0 [cifs] ? __pfx___lock_acquire+0x10/0x10 ? __pfx_dfs_mount_share+0x10/0x10 [cifs] ? lock_acquire.part.0+0xf4/0x2a0 ? find_held_lock+0x8a/0xa0 ? hlock_class+0x32/0xb0 ? lock_release+0x203/0x5d0 cifs_mount+0xb3/0x3d0 [cifs] ? do_raw_spin_trylock+0xc6/0x120 ? __pfx_cifs_mount+0x10/0x10 [cifs] ? lock_acquire+0x3f/0x90 ? find_nls+0x16/0xa0 ? smb3_update_mnt_flags+0x372/0x3b0 [cifs] cifs_smb3_do_mount+0x1e2/0xc80 [cifs] ? __pfx_vfs_parse_fs_string+0x10/0x10 ? __pfx_cifs_smb3_do_mount+0x10/0x10 [cifs] smb3_get_tree+0x1bf/0x330 [cifs] vfs_get_tree+0x4a/0x160 path_mount+0x3c1/0xfb0 ? kasan_quarantine_put+0xc7/0x1d0 ? __pfx_path_mount+0x10/0x10 ? kmem_cache_free+0x118/0x3e0 ? user_path_at+0x74/0xa0 __x64_sys_mount+0x1a6/0x1e0 ? __pfx___x64_sys_mount+0x10/0x10 ? mark_held_locks+0x1a/0x90 do_syscall_64+0xbb/0x1d0 entry_SYSCALL_64_after_hwframe+0x77/0x7f

In the Linux kernel, the following vulnerability has been resolved: drm/dp_mst: Ensure mst_primary pointer is valid in drm_dp_mst_handle_up_req() While receiving an MST up request message from one thread in drm_dp_mst_handle_up_req(), the MST topology could be removed from another thread via drm_dp_mst_topology_mgr_set_mst(false), freeing mst_primary and setting drm_dp_mst_topology_mgr::mst_primary to NULL. This could lead to a NULL deref/use-after-free of mst_primary in drm_dp_mst_handle_up_req(). Avoid the above by holding a reference for mst_primary in drm_dp_mst_handle_up_req() while it's used. v2: Fix kfreeing the request if getting an mst_primary reference fails.

In the Linux kernel, the following vulnerability has been resolved: iommu/vt-d: Remove cache tags before disabling ATS The current implementation removes cache tags after disabling ATS, leading to potential memory leaks and kernel crashes. Specifically, CACHE_TAG_DEVTLB type cache tags may still remain in the list even after the domain is freed, causing a use-after-free condition. This issue really shows up when multiple VFs from different PFs passed through to a single user-space process via vfio-pci. In such cases, the kernel may crash with kernel messages like: BUG: kernel NULL pointer dereference, address: 0000000000000014 PGD 19036a067 P4D 1940a3067 PUD 136c9b067 PMD 0 Oops: Oops: 0000 [#1] PREEMPT SMP NOPTI CPU: 74 UID: 0 PID: 3183 Comm: testCli Not tainted 6.11.9 #2 RIP: 0010:cache_tag_flush_range+0x9b/0x250 Call Trace: <TASK> ? __die+0x1f/0x60 ? page_fault_oops+0x163/0x590 ? exc_page_fault+0x72/0x190 ? asm_exc_page_fault+0x22/0x30 ? cache_tag_flush_range+0x9b/0x250 ? cache_tag_flush_range+0x5d/0x250 intel_iommu_tlb_sync+0x29/0x40 intel_iommu_unmap_pages+0xfe/0x160 __iommu_unmap+0xd8/0x1a0 vfio_unmap_unpin+0x182/0x340 [vfio_iommu_type1] vfio_remove_dma+0x2a/0xb0 [vfio_iommu_type1] vfio_iommu_type1_ioctl+0xafa/0x18e0 [vfio_iommu_type1] Move cache_tag_unassign_domain() before iommu_disable_pci_caps() to fix it.