In the Linux kernel, the following vulnerability has been resolved: coresight: tmc-etf: Fix global-out-of-bounds in tmc_update_etf_buffer() commit 6f755e85c332 ("coresight: Add helper for inserting synchronization packets") removed trailing '\0' from barrier_pkt array and updated the call sites like etb_update_buffer() to have proper checks for barrier_pkt size before read but missed updating tmc_update_etf_buffer() which still reads barrier_pkt past the array size resulting in KASAN out-of-bounds bug. Fix this by adding a check for barrier_pkt size before accessing like it is done in etb_update_buffer(). BUG: KASAN: global-out-of-bounds in tmc_update_etf_buffer+0x4b8/0x698 Read of size 4 at addr ffffffd05b7d1030 by task perf/2629 Call trace: dump_backtrace+0x0/0x27c show_stack+0x20/0x2c dump_stack+0x11c/0x188 print_address_description+0x3c/0x4a4 __kasan_report+0x140/0x164 kasan_report+0x10/0x18 __asan_report_load4_noabort+0x1c/0x24 tmc_update_etf_buffer+0x4b8/0x698 etm_event_stop+0x248/0x2d8 etm_event_del+0x20/0x2c event_sched_out+0x214/0x6f0 group_sched_out+0xd0/0x270 ctx_sched_out+0x2ec/0x518 __perf_event_task_sched_out+0x4fc/0xe6c __schedule+0x1094/0x16a0 preempt_schedule_irq+0x88/0x170 arm64_preempt_schedule_irq+0xf0/0x18c el1_irq+0xe8/0x180 perf_event_exec+0x4d8/0x56c setup_new_exec+0x204/0x400 load_elf_binary+0x72c/0x18c0 search_binary_handler+0x13c/0x420 load_script+0x500/0x6c4 search_binary_handler+0x13c/0x420 exec_binprm+0x118/0x654 __do_execve_file+0x77c/0xba4 __arm64_compat_sys_execve+0x98/0xac el0_svc_common+0x1f8/0x5e0 el0_svc_compat_handler+0x84/0xb0 el0_svc_compat+0x10/0x50 The buggy address belongs to the variable: barrier_pkt+0x10/0x40 Memory state around the buggy address: ffffffd05b7d0f00: fa fa fa fa 04 fa fa fa fa fa fa fa 00 00 00 00 ffffffd05b7d0f80: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 >ffffffd05b7d1000: 00 00 00 00 00 00 fa fa fa fa fa fa 00 00 00 03 ^ ffffffd05b7d1080: fa fa fa fa 00 02 fa fa fa fa fa fa 03 fa fa fa ffffffd05b7d1100: fa fa fa fa 00 00 00 00 05 fa fa fa fa fa fa fa ==================================================================

In the Linux kernel, the following vulnerability has been resolved: media: ngene: Fix out-of-bounds bug in ngene_command_config_free_buf() Fix an 11-year old bug in ngene_command_config_free_buf() while addressing the following warnings caught with -Warray-bounds: arch/alpha/include/asm/string.h:22:16: warning: '__builtin_memcpy' offset [12, 16] from the object at 'com' is out of the bounds of referenced subobject 'config' with type 'unsigned char' at offset 10 [-Warray-bounds] arch/x86/include/asm/string_32.h:182:25: warning: '__builtin_memcpy' offset [12, 16] from the object at 'com' is out of the bounds of referenced subobject 'config' with type 'unsigned char' at offset 10 [-Warray-bounds] The problem is that the original code is trying to copy 6 bytes of data into a one-byte size member _config_ of the wrong structue FW_CONFIGURE_BUFFERS, in a single call to memcpy(). This causes a legitimate compiler warning because memcpy() overruns the length of &com.cmd.ConfigureBuffers.config. It seems that the right structure is FW_CONFIGURE_FREE_BUFFERS, instead, because it contains 6 more members apart from the header _hdr_. Also, the name of the function ngene_command_config_free_buf() suggests that the actual intention is to ConfigureFreeBuffers, instead of ConfigureBuffers (which takes place in the function ngene_command_config_buf(), above). Fix this by enclosing those 6 members of struct FW_CONFIGURE_FREE_BUFFERS into new struct config, and use &com.cmd.ConfigureFreeBuffers.config as the destination address, instead of &com.cmd.ConfigureBuffers.config, when calling memcpy(). This also helps with the ongoing efforts to globally enable -Warray-bounds and get us closer to being able to tighten the FORTIFY_SOURCE routines on memcpy().

In the Linux kernel, the following vulnerability has been resolved: netfilter: nftables: avoid overflows in nft_hash_buckets() Number of buckets being stored in 32bit variables, we have to ensure that no overflows occur in nft_hash_buckets() syzbot injected a size == 0x40000000 and reported: UBSAN: shift-out-of-bounds in ./include/linux/log2.h:57:13 shift exponent 64 is too large for 64-bit type 'long unsigned int' CPU: 1 PID: 29539 Comm: syz-executor.4 Not tainted 5.12.0-rc7-syzkaller #0 Hardware name: Google Google Compute Engine/Google Compute Engine, BIOS Google 01/01/2011 Call Trace: __dump_stack lib/dump_stack.c:79 [inline] dump_stack+0x141/0x1d7 lib/dump_stack.c:120 ubsan_epilogue+0xb/0x5a lib/ubsan.c:148 __ubsan_handle_shift_out_of_bounds.cold+0xb1/0x181 lib/ubsan.c:327 __roundup_pow_of_two include/linux/log2.h:57 [inline] nft_hash_buckets net/netfilter/nft_set_hash.c:411 [inline] nft_hash_estimate.cold+0x19/0x1e net/netfilter/nft_set_hash.c:652 nft_select_set_ops net/netfilter/nf_tables_api.c:3586 [inline] nf_tables_newset+0xe62/0x3110 net/netfilter/nf_tables_api.c:4322 nfnetlink_rcv_batch+0xa09/0x24b0 net/netfilter/nfnetlink.c:488 nfnetlink_rcv_skb_batch net/netfilter/nfnetlink.c:612 [inline] nfnetlink_rcv+0x3af/0x420 net/netfilter/nfnetlink.c:630 netlink_unicast_kernel net/netlink/af_netlink.c:1312 [inline] netlink_unicast+0x533/0x7d0 net/netlink/af_netlink.c:1338 netlink_sendmsg+0x856/0xd90 net/netlink/af_netlink.c:1927 sock_sendmsg_nosec net/socket.c:654 [inline] sock_sendmsg+0xcf/0x120 net/socket.c:674 ____sys_sendmsg+0x6e8/0x810 net/socket.c:2350 ___sys_sendmsg+0xf3/0x170 net/socket.c:2404 __sys_sendmsg+0xe5/0x1b0 net/socket.c:2433 do_syscall_64+0x2d/0x70 arch/x86/entry/common.c:46

In the Linux kernel, the following vulnerability has been resolved: net: marvell: prestera: fix incorrect structure access In line: upper = info->upper_dev; We access upper_dev field, which is related only for particular events (e.g. event == NETDEV_CHANGEUPPER). So, this line cause invalid memory access for another events, when ptr is not netdev_notifier_changeupper_info. The KASAN logs are as follows: [ 30.123165] BUG: KASAN: stack-out-of-bounds in prestera_netdev_port_event.constprop.0+0x68/0x538 [prestera] [ 30.133336] Read of size 8 at addr ffff80000cf772b0 by task udevd/778 [ 30.139866] [ 30.141398] CPU: 0 PID: 778 Comm: udevd Not tainted 5.16.0-rc3 #6 [ 30.147588] Hardware name: DNI AmazonGo1 A7040 board (DT) [ 30.153056] Call trace: [ 30.155547] dump_backtrace+0x0/0x2c0 [ 30.159320] show_stack+0x18/0x30 [ 30.162729] dump_stack_lvl+0x68/0x84 [ 30.166491] print_address_description.constprop.0+0x74/0x2b8 [ 30.172346] kasan_report+0x1e8/0x250 [ 30.176102] __asan_load8+0x98/0xe0 [ 30.179682] prestera_netdev_port_event.constprop.0+0x68/0x538 [prestera] [ 30.186847] prestera_netdev_event_handler+0x1b4/0x1c0 [prestera] [ 30.193313] raw_notifier_call_chain+0x74/0xa0 [ 30.197860] call_netdevice_notifiers_info+0x68/0xc0 [ 30.202924] register_netdevice+0x3cc/0x760 [ 30.207190] register_netdev+0x24/0x50 [ 30.211015] prestera_device_register+0x8a0/0xba0 [prestera]

In the Linux kernel, the following vulnerability has been resolved: net/sched: sch_frag: fix stack OOB read while fragmenting IPv4 packets when 'act_mirred' tries to fragment IPv4 packets that had been previously re-assembled using 'act_ct', splats like the following can be observed on kernels built with KASAN: BUG: KASAN: stack-out-of-bounds in ip_do_fragment+0x1b03/0x1f60 Read of size 1 at addr ffff888147009574 by task ping/947 CPU: 0 PID: 947 Comm: ping Not tainted 5.12.0-rc6+ #418 Hardware name: Red Hat KVM, BIOS 1.11.1-4.module+el8.1.0+4066+0f1aadab 04/01/2014 Call Trace: <IRQ> dump_stack+0x92/0xc1 print_address_description.constprop.7+0x1a/0x150 kasan_report.cold.13+0x7f/0x111 ip_do_fragment+0x1b03/0x1f60 sch_fragment+0x4bf/0xe40 tcf_mirred_act+0xc3d/0x11a0 [act_mirred] tcf_action_exec+0x104/0x3e0 fl_classify+0x49a/0x5e0 [cls_flower] tcf_classify_ingress+0x18a/0x820 __netif_receive_skb_core+0xae7/0x3340 __netif_receive_skb_one_core+0xb6/0x1b0 process_backlog+0x1ef/0x6c0 __napi_poll+0xaa/0x500 net_rx_action+0x702/0xac0 __do_softirq+0x1e4/0x97f do_softirq+0x71/0x90 </IRQ> __local_bh_enable_ip+0xdb/0xf0 ip_finish_output2+0x760/0x2120 ip_do_fragment+0x15a5/0x1f60 __ip_finish_output+0x4c2/0xea0 ip_output+0x1ca/0x4d0 ip_send_skb+0x37/0xa0 raw_sendmsg+0x1c4b/0x2d00 sock_sendmsg+0xdb/0x110 __sys_sendto+0x1d7/0x2b0 __x64_sys_sendto+0xdd/0x1b0 do_syscall_64+0x33/0x40 entry_SYSCALL_64_after_hwframe+0x44/0xae RIP: 0033:0x7f82e13853eb Code: 66 2e 0f 1f 84 00 00 00 00 00 0f 1f 44 00 00 f3 0f 1e fa 48 8d 05 75 42 2c 00 41 89 ca 8b 00 85 c0 75 14 b8 2c 00 00 00 0f 05 <48> 3d 00 f0 ff ff 77 75 c3 0f 1f 40 00 41 57 4d 89 c7 41 56 41 89 RSP: 002b:00007ffe01fad888 EFLAGS: 00000246 ORIG_RAX: 000000000000002c RAX: ffffffffffffffda RBX: 00005571aac13700 RCX: 00007f82e13853eb RDX: 0000000000002330 RSI: 00005571aac13700 RDI: 0000000000000003 RBP: 0000000000002330 R08: 00005571aac10500 R09: 0000000000000010 R10: 0000000000000000 R11: 0000000000000246 R12: 00007ffe01faefb0 R13: 00007ffe01fad890 R14: 00007ffe01fad980 R15: 00005571aac0f0a0 The buggy address belongs to the page: page:000000001dff2e03 refcount:1 mapcount:0 mapping:0000000000000000 index:0x0 pfn:0x147009 flags: 0x17ffffc0001000(reserved) raw: 0017ffffc0001000 ffffea00051c0248 ffffea00051c0248 0000000000000000 raw: 0000000000000000 0000000000000000 00000001ffffffff 0000000000000000 page dumped because: kasan: bad access detected Memory state around the buggy address: ffff888147009400: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ffff888147009480: f1 f1 f1 f1 04 f2 f2 f2 f2 f2 f2 f2 00 00 00 00 >ffff888147009500: 00 00 00 00 00 00 00 00 00 00 f2 f2 f2 f2 f2 f2 ^ ffff888147009580: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ffff888147009600: 00 00 00 00 00 00 00 00 00 00 00 00 00 f2 f2 f2 for IPv4 packets, sch_fragment() uses a temporary struct dst_entry. Then, in the following call graph: ip_do_fragment() ip_skb_dst_mtu() ip_dst_mtu_maybe_forward() ip_mtu_locked() the pointer to struct dst_entry is used as pointer to struct rtable: this turns the access to struct members like rt_mtu_locked into an OOB read in the stack. Fix this changing the temporary variable used for IPv4 packets in sch_fragment(), similarly to what is done for IPv6 few lines below.

TensorFlow is an open source platform for machine learning. In affected versions the implementation of `FusedBatchNorm` kernels is vulnerable to a heap OOB access. 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.

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `QuantizeV2` can trigger a read outside of bounds of heap allocated array. This occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer. The code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `tf.ragged.cross` can trigger a read outside of bounds of heap allocated array. 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.

TensorFlow is an open source platform for machine learning. In affected versions the implementation of `SparseBinCount` is vulnerable to a heap OOB access. This is because of missing validation between the elements of the `values` argument and the shape of the sparse output. 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.

TensorFlow is an open source platform for machine learning. In affected versions the implementation of `SparseFillEmptyRows` can be made to trigger a heap OOB access. This occurs whenever the size of `indices` does not match the size of `values`. 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.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `BoostedTreesSparseCalculateBestFeatureSplit`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/stats_ops.cc) needs to validate that each value in `stats_summary_indices` is in range. We have patched the issue in GitHub commit e84c975313e8e8e38bb2ea118196369c45c51378. 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 if the arguments to `tf.raw_ops.RaggedGather` don't determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/ragged_gather_op.cc#L70) directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (i.e., it is not a scalar). Furthermore, the implementation does not check that the list given by `params_nested_splits` is not an empty list of tensors. We have patched the issue in GitHub commit a2b743f6017d7b97af1fe49087ae15f0ac634373. 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.

An out-of-bounds (OOB) memory read flaw was found in the Qualcomm IPC router protocol in the Linux kernel. A missing sanity check allows a local attacker to gain access to out-of-bounds memory, leading to a system crash or a leak of internal kernel information. The highest threat from this vulnerability is to system availability.

In the PatternMatch function in fontfile/fontdir.c in libXfont through 1.5.2 and 2.x before 2.0.2, an attacker with access to an X connection can cause a buffer over-read during pattern matching of fonts, leading to information disclosure or a crash (denial of service). This occurs because '\0' characters are incorrectly skipped in situations involving ? characters.

An out-of-bounds (OOB) memory access flaw was found in fs/f2fs/node.c in the f2fs module in the Linux kernel in versions before 5.12.0-rc4. A bounds check failure allows a local attacker to gain access to out-of-bounds memory leading to a system crash or a leak of internal kernel information. The highest threat from this vulnerability is to system availability.

Possible out of bound read due to lack of length check of data length for a DIAG event in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music

An Out-of-Bounds Read was discovered in arch/arm/mach-footbridge/personal-pci.c in the Linux kernel through 5.12.11 because of the lack of a check for a value that shouldn't be negative, e.g., access to element -2 of an array, aka CID-298a58e165e4.

An issue was discovered in InsydeH2O. A malicious operating system can tamper with a runtime-writable EFI variable, leading to out-of-bounds memory reads and a denial of service. This is fixed in version 01.01.04.0016.

Possible buffer over read due to improper buffer allocation for file length passed from user space in Snapdragon Auto, Snapdragon Connectivity, Snapdragon Industrial IOT, Snapdragon Mobile

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `tf.raw_ops.RaggedTensorToTensor`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) uses the same index to access two arrays in parallel. Since the user controls the shape of the input arguments, an attacker could trigger a heap OOB access when `parent_output_index` is shorter than `row_split`. 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 open source platform for machine learning. In affected versions the shape inference functions for `SparseCountSparseOutput` can trigger a read outside of bounds of heap allocated array. 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.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can read data outside of bounds of heap allocated buffer in `tf.raw_ops.QuantizeAndDequantizeV3`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/11ff7f80667e6490d7b5174aa6bf5e01886e770f/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L237) does not validate the value of user supplied `axis` attribute before using it to index in the array backing the `input` argument. 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 access data outside of bounds of heap allocated array in `tf.raw_ops.UnicodeEncode`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/472c1f12ad9063405737679d4f6bd43094e1d36d/tensorflow/core/kernels/unicode_ops.cc) assumes that the `input_value`/`input_splits` pair specify a valid sparse tensor. 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 implementations of the `Minimum` and `Maximum` TFLite operators can be used to read data outside of bounds of heap allocated objects, if any of the two input tensor arguments are empty. This is because the broadcasting implementation(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/maximum_minimum.h#L52-L56) indexes in both tensors with the same index but does not validate that the index is within bounds. 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.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ef0c008ee84bad91ec6725ddc42091e19a30cf0e/tensorflow/core/kernels/maxpooling_op.cc#L1016-L1017) uses the same value to index in two different arrays but there is no guarantee that the sizes are identical. 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.

An issue was discovered in the Linux kernel through 5.11.3. drivers/scsi/scsi_transport_iscsi.c is adversely affected by the ability of an unprivileged user to craft Netlink messages.

TensorFlow is an open source platform for machine learning. In affected versions the shape inference functions for the `QuantizeAndDequantizeV*` operations can trigger a read outside of bounds of heap allocated array. 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.

Lack of boundary checking of a buffer in libSPenBase library of Samsung Notes prior to Samsung Note version 4.3.02.61 allows OOB read

In read_paint of ttcolr.c, there is a possible out of bounds read due to a heap buffer overflow. This could lead to local information disclosure with no additional execution privileges needed. User interaction is not needed for exploitation.Product: AndroidVersions: Android-13Android ID: A-254803162

Out of bounds read in firmware for some Intel(R) Wireless Bluetooth(R) and Killer(TM) Bluetooth(R) products before version 22.120 may allow a privileged user to potentially enable information disclosure via local access.

In the Linux kernel, the following vulnerability has been resolved: iio: health: afe4403: Fix oob read in afe4403_read_raw KASAN report out-of-bounds read as follows: BUG: KASAN: global-out-of-bounds in afe4403_read_raw+0x42e/0x4c0 Read of size 4 at addr ffffffffc02ac638 by task cat/279 Call Trace: afe4403_read_raw iio_read_channel_info dev_attr_show The buggy address belongs to the variable: afe4403_channel_leds+0x18/0xffffffffffffe9e0 This issue can be reproduced by singe command: $ cat /sys/bus/spi/devices/spi0.0/iio\:device0/in_intensity6_raw The array size of afe4403_channel_leds is less than channels, so access with chan->address cause OOB read in afe4403_read_raw. Fix it by moving access before use it.

There is an out-of-bound read vulnerability in Taurus-AL00A 10.0.0.1(C00E1R1P1). A module does not verify the some input. Attackers can exploit this vulnerability by sending malicious input through specific app. This could cause out-of-bound, compromising normal service.

In the Linux kernel, the following vulnerability has been resolved: ipv4: Handle attempt to delete multipath route when fib_info contains an nh reference Gwangun Jung reported a slab-out-of-bounds access in fib_nh_match: fib_nh_match+0xf98/0x1130 linux-6.0-rc7/net/ipv4/fib_semantics.c:961 fib_table_delete+0x5f3/0xa40 linux-6.0-rc7/net/ipv4/fib_trie.c:1753 inet_rtm_delroute+0x2b3/0x380 linux-6.0-rc7/net/ipv4/fib_frontend.c:874 Separate nexthop objects are mutually exclusive with the legacy multipath spec. Fix fib_nh_match to return if the config for the to be deleted route contains a multipath spec while the fib_info is using a nexthop object.

A component of the HarmonyOS has a Out-of-bounds Read vulnerability. Local attackers may exploit this vulnerability to cause kernel out-of-bounds read.

In the Linux kernel, the following vulnerability has been resolved: usbnet: ipheth: use static NDP16 location in URB Original code allowed for the start of NDP16 to be anywhere within the URB based on the `wNdpIndex` value in NTH16. Only the start position of NDP16 was checked, so it was possible for even the fixed-length part of NDP16 to extend past the end of URB, leading to an out-of-bounds read. On iOS devices, the NDP16 header always directly follows NTH16. Rely on and check for this specific format. This, along with NCM-specific minimal URB length check that already exists, will ensure that the fixed-length part of NDP16 plus a set amount of DPEs fit within the URB. Note that this commit alone does not fully address the OoB read. The limit on the amount of DPEs needs to be enforced separately.

An issue was discovered in the Linux kernel before 6.2. The ntfs3 subsystem does not properly check for correctness during disk reads, leading to an out-of-bounds read in ntfs_set_ea in fs/ntfs3/xattr.c.

Buffer over read could occur due to incorrect check of buffer size while flashing emmc devices in Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables, Snapdragon Wired Infrastructure and Networking

In the Linux kernel, the following vulnerability has been resolved: vlan: enforce underlying device type Currently, VLAN devices can be created on top of non-ethernet devices. Besides the fact that it doesn't make much sense, this also causes a bug which leaks the address of a kernel function to usermode. When creating a VLAN device, we initialize GARP (garp_init_applicant) and MRP (mrp_init_applicant) for the underlying device. As part of the initialization process, we add the multicast address of each applicant to the underlying device, by calling dev_mc_add. __dev_mc_add uses dev->addr_len to determine the length of the new multicast address. This causes an out-of-bounds read if dev->addr_len is greater than 6, since the multicast addresses provided by GARP and MRP are only 6 bytes long. This behaviour can be reproduced using the following commands: ip tunnel add gretest mode ip6gre local ::1 remote ::2 dev lo ip l set up dev gretest ip link add link gretest name vlantest type vlan id 100 Then, the following command will display the address of garp_pdu_rcv: ip maddr show | grep 01:80:c2:00:00:21 Fix the bug by enforcing the type of the underlying device during VLAN device initialization.

In the Linux kernel, the following vulnerability has been resolved: usbnet: ipheth: fix possible overflow in DPE length check Originally, it was possible for the DPE length check to overflow if wDatagramIndex + wDatagramLength > U16_MAX. This could lead to an OoB read. Move the wDatagramIndex term to the other side of the inequality. An existing condition ensures that wDatagramIndex < urb->actual_length.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of sparse reduction operations in TensorFlow can trigger accesses outside of bounds of heap allocated data. The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_reduce_op.cc#L217-L228) fails to validate that each reduction group does not overflow and that each corresponding index does not point to outside the bounds of the input tensor. We have patched the issue in GitHub commit 87158f43f05f2720a374f3e6d22a7aaa3a33f750. 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.

NVIDIA GPU Display Driver for Windows and Linux contains a vulnerability in the kernel mode layer (nvlddmkm.sys) handler for DxgkDdiEscape where an out of bounds array access may lead to denial of service or information disclosure.

In the Linux kernel, the following vulnerability has been resolved: usbnet: ipheth: fix DPE OoB read Fix an out-of-bounds DPE read, limit the number of processed DPEs to the amount that fits into the fixed-size NDP16 header.

An out-of-bounds read was addressed with improved input validation. This issue is fixed in macOS Catalina 10.15.4. A local user may be able to cause unexpected system termination or read kernel memory.

In the Linux kernel, the following vulnerability has been resolved: ksmbd: validate zero num_subauth before sub_auth is accessed Access psid->sub_auth[psid->num_subauth - 1] without checking if num_subauth is non-zero leads to an out-of-bounds read. This patch adds a validation step to ensure num_subauth != 0 before sub_auth is accessed.

An out-of-bounds array read in the apr_time_exp*() functions was fixed in the Apache Portable Runtime 1.6.3 release (CVE-2017-12613). The fix for this issue was not carried forward to the APR 1.7.x branch, and hence version 1.7.0 regressed compared to 1.6.3 and is vulnerable to the same issue.

In the Linux kernel, the following vulnerability has been resolved: drm/amd/display: Adjust VSDB parser for replay feature At some point, the IEEE ID identification for the replay check in the AMD EDID was added. However, this check causes the following out-of-bounds issues when using KASAN: [ 27.804016] BUG: KASAN: slab-out-of-bounds in amdgpu_dm_update_freesync_caps+0xefa/0x17a0 [amdgpu] [ 27.804788] Read of size 1 at addr ffff8881647fdb00 by task systemd-udevd/383 ... [ 27.821207] Memory state around the buggy address: [ 27.821215] ffff8881647fda00: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 [ 27.821224] ffff8881647fda80: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 [ 27.821234] >ffff8881647fdb00: fc fc fc fc fc fc fc fc fc fc fc fc fc fc fc fc [ 27.821243] ^ [ 27.821250] ffff8881647fdb80: fc fc fc fc fc fc fc fc fc fc fc fc fc fc fc fc [ 27.821259] ffff8881647fdc00: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 [ 27.821268] ================================================================== This is caused because the ID extraction happens outside of the range of the edid lenght. This commit addresses this issue by considering the amd_vsdb_block size. (cherry picked from commit b7e381b1ccd5e778e3d9c44c669ad38439a861d8)

Out-of-bounds read in Samsung Notes allows local attackers to bypass ASLR.

In the Linux kernel, the following vulnerability has been resolved: orangefs: fix a oob in orangefs_debug_write I got a syzbot report: slab-out-of-bounds Read in orangefs_debug_write... several people suggested fixes, I tested Al Viro's suggestion and made this patch.