The Linux kernel before 2.6.25.10 does not properly perform tty operations, which allows local users to cause a denial of service (system crash) or possibly gain privileges via vectors involving NULL pointer dereference of function pointers in (1) hamradio/6pack.c, (2) hamradio/mkiss.c, (3) irda/irtty-sir.c, (4) ppp_async.c, (5) ppp_synctty.c, (6) slip.c, (7) wan/x25_asy.c, and (8) wireless/strip.c in drivers/net/.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger undefined behavior by binding to null pointer in `tf.raw_ops.ParameterizedTruncatedNormal`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3f6fe4dfef6f57e768260b48166c27d148f3015f/tensorflow/core/kernels/parameterized_truncated_normal_op.cc#L630) does not validate input arguments before accessing the first element of `shape`. If `shape` argument is empty, then `shape_tensor.flat<T>()` is an empty array. 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.

The graphic acceleration functions in VMware Tools 9.x and 10.x before 10.0.9 on OS X allow local users to gain privileges or cause a denial of service (NULL pointer dereference) via unspecified vectors, a different vulnerability than CVE-2016-7079.

The graphic acceleration functions in VMware Tools 9.x and 10.x before 10.0.9 on OS X allow local users to gain privileges or cause a denial of service (NULL pointer dereference) via unspecified vectors, a different vulnerability than CVE-2016-7080.

An issue was discovered in certain Apple products. macOS before 10.12.1 is affected. The issue involves the "AppleSMC" component. It allows local users to gain privileges or cause a denial of service (NULL pointer dereference) via unspecified vectors.

The trace_writeback_dirty_page implementation in include/trace/events/writeback.h in the Linux kernel before 4.4 improperly interacts with mm/migrate.c, which allows local users to cause a denial of service (NULL pointer dereference and system crash) or possibly have unspecified other impact by triggering a certain page move.

win32k.sys in the kernel-mode drivers in Microsoft Windows XP SP2 and SP3, Windows Server 2003 SP2, Windows Vista SP1 and SP2, Windows Server 2008 Gold, SP2, R2, and R2 SP1, and Windows 7 Gold and SP1 allows local users to gain privileges via a crafted application that triggers a NULL pointer dereference, a different vulnerability than other "Vulnerability Type 2" CVEs listed in MS11-034, aka "Win32k Null Pointer De-reference Vulnerability."

Null pointer dereference in Windows Client-Side Caching (CSC) Service allows an authorized attacker to elevate privileges locally.

Null pointer dereference in the Intel(R) VROC software before version 7.7.6.1003 may allow an authenticated user to potentially enable escalation of privilege via local access.

Null pointer dereference in Windows Ancillary Function Driver for WinSock allows an authorized attacker to elevate privileges locally.

Null pointer dereference in Windows Ancillary Function Driver for WinSock allows an authorized attacker to elevate privileges locally.

The ATI Rage 128 (aka r128) driver in the Linux kernel before 2.6.31-git11 does not properly verify Concurrent Command Engine (CCE) state initialization, which allows local users to cause a denial of service (NULL pointer dereference and system crash) or possibly gain privileges via unspecified ioctl calls.

The msm_ipc_router_close function in net/ipc_router/ipc_router_socket.c in the ipc_router component for the Linux kernel 3.x, as used in Qualcomm Innovation Center (QuIC) Android contributions for MSM devices and other products, allow attackers to cause a denial of service (NULL pointer dereference) or possibly have unspecified other impact by triggering failure of an accept system call for an AF_MSM_IPC socket.

Null pointer dereference in Windows TCP/IP allows an authorized attacker to elevate privileges locally.

in OpenHarmony v5.0.2 and prior versions allow a local attacker arbitrary code execution in pre-installed apps through through NULL pointer dereference.. This vulnerability can be exploited only in restricted scenarios.

In the Linux kernel, the following vulnerability has been resolved: scsi: target: Fix WRITE_SAME No Data Buffer crash In newer version of the SBC specs, we have a NDOB bit that indicates there is no data buffer that gets written out. If this bit is set using commands like "sg_write_same --ndob" we will crash in target_core_iblock/file's execute_write_same handlers when we go to access the se_cmd->t_data_sg because its NULL. This patch adds a check for the NDOB bit in the common WRITE SAME code because we don't support it. And, it adds a check for zero SG elements in each handler in case the initiator tries to send a normal WRITE SAME with no data buffer.

In the Linux kernel, the following vulnerability has been resolved: hwmon: (w83791d) Fix NULL pointer dereference by removing unnecessary structure field If driver read val value sufficient for (val & 0x08) && (!(val & 0x80)) && ((val & 0x7) == ((val >> 4) & 0x7)) from device then Null pointer dereference occurs. (It is possible if tmp = 0b0xyz1xyz, where same literals mean same numbers) Also lm75[] does not serve a purpose anymore after switching to devm_i2c_new_dummy_device() in w83791d_detect_subclients(). The patch fixes possible NULL pointer dereference by removing lm75[]. Found by Linux Driver Verification project (linuxtesting.org). [groeck: Dropped unnecessary continuation lines, fixed multi-line alignment]

Win32k Elevation of Privilege Vulnerability

kernel/bpf/verifier.c in the Linux kernel through 5.15.14 allows local users to gain privileges because of the availability of pointer arithmetic via certain *_OR_NULL pointer types.

In the Linux kernel, the following vulnerability has been resolved: gtp: fix use-after-free and null-ptr-deref in gtp_newlink() The gtp_link_ops operations structure for the subsystem must be registered after registering the gtp_net_ops pernet operations structure. Syzkaller hit 'general protection fault in gtp_genl_dump_pdp' bug: [ 1010.702740] gtp: GTP module unloaded [ 1010.715877] general protection fault, probably for non-canonical address 0xdffffc0000000001: 0000 [#1] SMP KASAN NOPTI [ 1010.715888] KASAN: null-ptr-deref in range [0x0000000000000008-0x000000000000000f] [ 1010.715895] CPU: 1 PID: 128616 Comm: a.out Not tainted 6.8.0-rc6-std-def-alt1 #1 [ 1010.715899] Hardware name: QEMU Standard PC (Q35 + ICH9, 2009), BIOS 1.16.0-alt1 04/01/2014 [ 1010.715908] RIP: 0010:gtp_newlink+0x4d7/0x9c0 [gtp] [ 1010.715915] Code: 80 3c 02 00 0f 85 41 04 00 00 48 8b bb d8 05 00 00 e8 ed f6 ff ff 48 89 c2 48 89 c5 48 b8 00 00 00 00 00 fc ff df 48 c1 ea 03 <80> 3c 02 00 0f 85 4f 04 00 00 4c 89 e2 4c 8b 6d 00 48 b8 00 00 00 [ 1010.715920] RSP: 0018:ffff888020fbf180 EFLAGS: 00010203 [ 1010.715929] RAX: dffffc0000000000 RBX: ffff88800399c000 RCX: 0000000000000000 [ 1010.715933] RDX: 0000000000000001 RSI: ffffffff84805280 RDI: 0000000000000282 [ 1010.715938] RBP: 000000000000000d R08: 0000000000000001 R09: 0000000000000000 [ 1010.715942] R10: 0000000000000001 R11: 0000000000000001 R12: ffff88800399cc80 [ 1010.715947] R13: 0000000000000000 R14: 0000000000000000 R15: 0000000000000400 [ 1010.715953] FS: 00007fd1509ab5c0(0000) GS:ffff88805b300000(0000) knlGS:0000000000000000 [ 1010.715958] CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 [ 1010.715962] CR2: 0000000000000000 CR3: 000000001c07a000 CR4: 0000000000750ee0 [ 1010.715968] PKRU: 55555554 [ 1010.715972] Call Trace: [ 1010.715985] ? __die_body.cold+0x1a/0x1f [ 1010.715995] ? die_addr+0x43/0x70 [ 1010.716002] ? exc_general_protection+0x199/0x2f0 [ 1010.716016] ? asm_exc_general_protection+0x1e/0x30 [ 1010.716026] ? gtp_newlink+0x4d7/0x9c0 [gtp] [ 1010.716034] ? gtp_net_exit+0x150/0x150 [gtp] [ 1010.716042] __rtnl_newlink+0x1063/0x1700 [ 1010.716051] ? rtnl_setlink+0x3c0/0x3c0 [ 1010.716063] ? is_bpf_text_address+0xc0/0x1f0 [ 1010.716070] ? kernel_text_address.part.0+0xbb/0xd0 [ 1010.716076] ? __kernel_text_address+0x56/0xa0 [ 1010.716084] ? unwind_get_return_address+0x5a/0xa0 [ 1010.716091] ? create_prof_cpu_mask+0x30/0x30 [ 1010.716098] ? arch_stack_walk+0x9e/0xf0 [ 1010.716106] ? stack_trace_save+0x91/0xd0 [ 1010.716113] ? stack_trace_consume_entry+0x170/0x170 [ 1010.716121] ? __lock_acquire+0x15c5/0x5380 [ 1010.716139] ? mark_held_locks+0x9e/0xe0 [ 1010.716148] ? kmem_cache_alloc_trace+0x35f/0x3c0 [ 1010.716155] ? __rtnl_newlink+0x1700/0x1700 [ 1010.716160] rtnl_newlink+0x69/0xa0 [ 1010.716166] rtnetlink_rcv_msg+0x43b/0xc50 [ 1010.716172] ? rtnl_fdb_dump+0x9f0/0x9f0 [ 1010.716179] ? lock_acquire+0x1fe/0x560 [ 1010.716188] ? netlink_deliver_tap+0x12f/0xd50 [ 1010.716196] netlink_rcv_skb+0x14d/0x440 [ 1010.716202] ? rtnl_fdb_dump+0x9f0/0x9f0 [ 1010.716208] ? netlink_ack+0xab0/0xab0 [ 1010.716213] ? netlink_deliver_tap+0x202/0xd50 [ 1010.716220] ? netlink_deliver_tap+0x218/0xd50 [ 1010.716226] ? __virt_addr_valid+0x30b/0x590 [ 1010.716233] netlink_unicast+0x54b/0x800 [ 1010.716240] ? netlink_attachskb+0x870/0x870 [ 1010.716248] ? __check_object_size+0x2de/0x3b0 [ 1010.716254] netlink_sendmsg+0x938/0xe40 [ 1010.716261] ? netlink_unicast+0x800/0x800 [ 1010.716269] ? __import_iovec+0x292/0x510 [ 1010.716276] ? netlink_unicast+0x800/0x800 [ 1010.716284] __sock_sendmsg+0x159/0x190 [ 1010.716290] ____sys_sendmsg+0x712/0x880 [ 1010.716297] ? sock_write_iter+0x3d0/0x3d0 [ 1010.716304] ? __ia32_sys_recvmmsg+0x270/0x270 [ 1010.716309] ? lock_acquire+0x1fe/0x560 [ 1010.716315] ? drain_array_locked+0x90/0x90 [ 1010.716324] ___sys_sendmsg+0xf8/0x170 [ 1010.716331] ? sendmsg_copy_msghdr+0x170/0x170 [ 1010.716337] ? lockdep_init_map ---truncated---

In the Linux kernel, the following vulnerability has been resolved: crypto: sun8i-ce - Fix use after free in unprepare sun8i_ce_cipher_unprepare should be called before crypto_finalize_skcipher_request, because client callbacks may immediately free memory, that isn't needed anymore. But it will be used by unprepare after free. Before removing prepare/unprepare callbacks it was handled by crypto engine in crypto_finalize_request. Usually that results in a pointer dereference problem during a in crypto selftest. Unable to handle kernel NULL pointer dereference at virtual address 0000000000000030 Mem abort info: ESR = 0x0000000096000004 EC = 0x25: DABT (current EL), IL = 32 bits SET = 0, FnV = 0 EA = 0, S1PTW = 0 FSC = 0x04: level 0 translation fault Data abort info: ISV = 0, ISS = 0x00000004, ISS2 = 0x00000000 CM = 0, WnR = 0, TnD = 0, TagAccess = 0 GCS = 0, Overlay = 0, DirtyBit = 0, Xs = 0 user pgtable: 4k pages, 48-bit VAs, pgdp=000000004716d000 [0000000000000030] pgd=0000000000000000, p4d=0000000000000000 Internal error: Oops: 0000000096000004 [#1] SMP This problem is detected by KASAN as well. ================================================================== BUG: KASAN: slab-use-after-free in sun8i_ce_cipher_do_one+0x6e8/0xf80 [sun8i_ce] Read of size 8 at addr ffff00000dcdc040 by task 1c15000.crypto-/373 Hardware name: Pine64 PinePhone (1.2) (DT) Call trace: dump_backtrace+0x9c/0x128 show_stack+0x20/0x38 dump_stack_lvl+0x48/0x60 print_report+0xf8/0x5d8 kasan_report+0x90/0xd0 __asan_load8+0x9c/0xc0 sun8i_ce_cipher_do_one+0x6e8/0xf80 [sun8i_ce] crypto_pump_work+0x354/0x620 [crypto_engine] kthread_worker_fn+0x244/0x498 kthread+0x168/0x178 ret_from_fork+0x10/0x20 Allocated by task 379: kasan_save_stack+0x3c/0x68 kasan_set_track+0x2c/0x40 kasan_save_alloc_info+0x24/0x38 __kasan_kmalloc+0xd4/0xd8 __kmalloc+0x74/0x1d0 alg_test_skcipher+0x90/0x1f0 alg_test+0x24c/0x830 cryptomgr_test+0x38/0x60 kthread+0x168/0x178 ret_from_fork+0x10/0x20 Freed by task 379: kasan_save_stack+0x3c/0x68 kasan_set_track+0x2c/0x40 kasan_save_free_info+0x38/0x60 __kasan_slab_free+0x100/0x170 slab_free_freelist_hook+0xd4/0x1e8 __kmem_cache_free+0x15c/0x290 kfree+0x74/0x100 kfree_sensitive+0x80/0xb0 alg_test_skcipher+0x12c/0x1f0 alg_test+0x24c/0x830 cryptomgr_test+0x38/0x60 kthread+0x168/0x178 ret_from_fork+0x10/0x20 The buggy address belongs to the object at ffff00000dcdc000 which belongs to the cache kmalloc-256 of size 256 The buggy address is located 64 bytes inside of freed 256-byte region [ffff00000dcdc000, ffff00000dcdc100)

TensorFlow is an open source platform for machine learning. In affected versions the code for boosted trees in TensorFlow is still missing validation. As a result, attackers can trigger denial of service (via dereferencing `nullptr`s or via `CHECK`-failures) as well as abuse undefined behavior (binding references to `nullptr`s). An attacker can also read and write from heap buffers, depending on the API that gets used and the arguments that are passed to the call. Given that the boosted trees implementation in TensorFlow is unmaintained, it is recommend to no longer use these APIs. We will deprecate TensorFlow's boosted trees APIs in subsequent releases. 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 OpenHarmony v4.0.0 and prior versions allow a local attacker arbitrary code execution in pre-installed apps through use after free or cause DOS through NULL pointer dereference.

A crafted NTFS image can cause a NULL pointer dereference in ntfs_extent_inode_open in NTFS-3G < 2021.8.22.

Null pointer dereference in Microsoft Brokering File System allows an authorized attacker to elevate privileges locally.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the code for `tf.raw_ops.SaveV2` does not properly validate the inputs and an attacker can trigger a null pointer dereference. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/save_restore_v2_ops.cc) uses `ValidateInputs` to check that the input arguments are valid. This validation would have caught the illegal state represented by the reproducer above. However, the validation uses `OP_REQUIRES` which translates to setting the `Status` object of the current `OpKernelContext` to an error status, followed by an empty `return` statement which just terminates the execution of the function it is present in. However, this does not mean that the kernel execution is finalized: instead, execution continues from the next line in `Compute` that follows the call to `ValidateInputs`. This is equivalent to lacking the validation. We have patched the issue in GitHub commit 9728c60e136912a12d99ca56e106b7cce7af5986. 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 the implementation of SVDF in TFLite is [vulnerable to a null pointer error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/svdf.cc#L300-L313). The [`GetVariableInput` function](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L115-L119) can return a null pointer but `GetTensorData` assumes that the argument is always a valid tensor. Furthermore, because `GetVariableInput` calls [`GetMutableInput`](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L82-L90) which might return `nullptr`, the `tensor->is_variable` expression can also trigger a null pointer exception. We have patched the issue in GitHub commit 5b048e87e4e55990dae6b547add4dae59f4e1c76. 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 craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. This is caused by the MLIR optimization of `L2NormalizeReduceAxis` operator. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/compiler/mlir/lite/transforms/optimize.cc#L67-L70) unconditionally dereferences a pointer to an iterator to a vector without checking that the vector has elements. We have patched the issue in GitHub commit d6b57f461b39fd1aa8c1b870f1b974aac3554955. 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. 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