Windows Resilient File System (ReFS) Elevation of Privilege Vulnerability

A crafted NTFS image can trigger an out-of-bounds read, caused by an invalid attribute in ntfs_attr_find_in_attrdef, in NTFS-3G < 2021.8.22.

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 vulnerability was found in compare_netdev_and_ip in drivers/infiniband/core/cma.c in RDMA in the Linux Kernel. The improper cleanup results in out-of-boundary read, where a local user can utilize this problem to crash the system or escalation of privilege.

In the Linux kernel, the following vulnerability has been resolved: firmware: arm_scmi: Harden accesses to the reset domains Accessing reset domains descriptors by the index upon the SCMI drivers requests through the SCMI reset operations interface can potentially lead to out-of-bound violations if the SCMI driver misbehave. Add an internal consistency check before any such domains descriptors accesses.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions it is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However, if the input tensor is a `RaggedTensor` and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not the case. The last row of `t` contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_from_variant_op.cc#L177-L190) does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. 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.

In libdexfile, there is a possible out of bounds read due to a missing bounds 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: drm/i915/gem: add missing boundary check in vm_access A missing bounds check in vm_access() can lead to an out-of-bounds read or write in the adjacent memory area, since the len attribute is not validated before the memcpy later in the function, potentially hitting: [ 183.637831] BUG: unable to handle page fault for address: ffffc90000c86000 [ 183.637934] #PF: supervisor read access in kernel mode [ 183.637997] #PF: error_code(0x0000) - not-present page [ 183.638059] PGD 100000067 P4D 100000067 PUD 100258067 PMD 106341067 PTE 0 [ 183.638144] Oops: 0000 [#2] PREEMPT SMP NOPTI [ 183.638201] CPU: 3 PID: 1790 Comm: poc Tainted: G D 5.17.0-rc6-ci-drm-11296+ #1 [ 183.638298] Hardware name: Intel Corporation CoffeeLake Client Platform/CoffeeLake H DDR4 RVP, BIOS CNLSFWR1.R00.X208.B00.1905301319 05/30/2019 [ 183.638430] RIP: 0010:memcpy_erms+0x6/0x10 [ 183.640213] RSP: 0018:ffffc90001763d48 EFLAGS: 00010246 [ 183.641117] RAX: ffff888109c14000 RBX: ffff888111bece40 RCX: 0000000000000ffc [ 183.642029] RDX: 0000000000001000 RSI: ffffc90000c86000 RDI: ffff888109c14004 [ 183.642946] RBP: 0000000000000ffc R08: 800000000000016b R09: 0000000000000000 [ 183.643848] R10: ffffc90000c85000 R11: 0000000000000048 R12: 0000000000001000 [ 183.644742] R13: ffff888111bed190 R14: ffff888109c14000 R15: 0000000000001000 [ 183.645653] FS: 00007fe5ef807540(0000) GS:ffff88845b380000(0000) knlGS:0000000000000000 [ 183.646570] CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 [ 183.647481] CR2: ffffc90000c86000 CR3: 000000010ff02006 CR4: 00000000003706e0 [ 183.648384] DR0: 0000000000000000 DR1: 0000000000000000 DR2: 0000000000000000 [ 183.649271] DR3: 0000000000000000 DR6: 00000000fffe0ff0 DR7: 0000000000000400 [ 183.650142] Call Trace: [ 183.650988] <TASK> [ 183.651793] vm_access+0x1f0/0x2a0 [i915] [ 183.652726] __access_remote_vm+0x224/0x380 [ 183.653561] mem_rw.isra.0+0xf9/0x190 [ 183.654402] vfs_read+0x9d/0x1b0 [ 183.655238] ksys_read+0x63/0xe0 [ 183.656065] do_syscall_64+0x38/0xc0 [ 183.656882] entry_SYSCALL_64_after_hwframe+0x44/0xae [ 183.657663] RIP: 0033:0x7fe5ef725142 [ 183.659351] RSP: 002b:00007ffe1e81c7e8 EFLAGS: 00000246 ORIG_RAX: 0000000000000000 [ 183.660227] RAX: ffffffffffffffda RBX: 0000557055dfb780 RCX: 00007fe5ef725142 [ 183.661104] RDX: 0000000000001000 RSI: 00007ffe1e81d880 RDI: 0000000000000005 [ 183.661972] RBP: 00007ffe1e81e890 R08: 0000000000000030 R09: 0000000000000046 [ 183.662832] R10: 0000557055dfc2e0 R11: 0000000000000246 R12: 0000557055dfb1c0 [ 183.663691] R13: 00007ffe1e81e980 R14: 0000000000000000 R15: 0000000000000000 Changes since v1: - Updated if condition with range_overflows_t [Chris Wilson] [mauld: tidy up the commit message and add Cc: stable] (cherry picked from commit 661412e301e2ca86799aa4f400d1cf0bd38c57c6)

The eBPF ALU32 bounds tracking for bitwise ops (AND, OR and XOR) in the Linux kernel did not properly update 32-bit bounds, which could be turned into out of bounds reads and writes in the Linux kernel and therefore, arbitrary code execution. This issue was fixed via commit 049c4e13714e ("bpf: Fix alu32 const subreg bound tracking on bitwise operations") (v5.13-rc4) and backported to the stable kernels in v5.12.4, v5.11.21, and v5.10.37. The AND/OR issues were introduced by commit 3f50f132d840 ("bpf: Verifier, do explicit ALU32 bounds tracking") (5.7-rc1) and the XOR variant was introduced by 2921c90d4718 ("bpf:Fix a verifier failure with xor") ( 5.10-rc1).

Possible out of bound read due to improper length calculation of WMI message. in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables

The bpf verifier in the Linux kernel did not properly handle mod32 destination register truncation when the source register was known to be 0. A local attacker with the ability to load bpf programs could use this gain out-of-bounds reads in kernel memory leading to information disclosure (kernel memory), and possibly out-of-bounds writes that could potentially lead to code execution. This issue was addressed in the upstream kernel in commit 9b00f1b78809 ("bpf: Fix truncation handling for mod32 dst reg wrt zero") and in Linux stable kernels 5.11.2, 5.10.19, and 5.4.101.

NVIDIA GPU Display Driver for Windows contains a vulnerability where a regular user can cause an out-of-bounds read, which may lead to code execution, denial of service, escalation of privileges, information disclosure, or data tampering.

NVIDIA GPU Display Driver for Linux contains a vulnerability in the kernel mode layer (nvidia.ko), where an out-of-bounds array access may lead to denial of service, data tampering, or information disclosure.

Possible out of bound read or write in VR service due to lack of validation of DSP selection values in Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT

Possible out of bound access due to improper validation of function table entries in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables, Snapdragon Wired Infrastructure and Networking

Out of bound write and read in TA while processing command from NS side due to improper length check on command and response buffers in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music

Possible out of bound read due to lack of domain input validation while processing APK close session request in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Industrial IOT, Snapdragon Wearables

Memory corruption due to buffer over-read in Modem while processing SetNativeHandle RTP service.

In the Linux kernel, the following vulnerability has been resolved: net: usb: ax88179_178a: Fix out-of-bounds accesses in RX fixup ax88179_rx_fixup() contains several out-of-bounds accesses that can be triggered by a malicious (or defective) USB device, in particular: - The metadata array (hdr_off..hdr_off+2*pkt_cnt) can be out of bounds, causing OOB reads and (on big-endian systems) OOB endianness flips. - A packet can overlap the metadata array, causing a later OOB endianness flip to corrupt data used by a cloned SKB that has already been handed off into the network stack. - A packet SKB can be constructed whose tail is far beyond its end, causing out-of-bounds heap data to be considered part of the SKB's data. I have tested that this can be used by a malicious USB device to send a bogus ICMPv6 Echo Request and receive an ICMPv6 Echo Reply in response that contains random kernel heap data. It's probably also possible to get OOB writes from this on a little-endian system somehow - maybe by triggering skb_cow() via IP options processing -, but I haven't tested that.

In the Linux kernel, the following vulnerability has been resolved: OPP: add index check to assert to avoid buffer overflow in _read_freq() Pass the freq index to the assert function to make sure we do not read a freq out of the opp->rates[] table when called from the indexed variants: dev_pm_opp_find_freq_exact_indexed() or dev_pm_opp_find_freq_ceil/floor_indexed(). Add a secondary parameter to the assert function, unused for assert_single_clk() then add assert_clk_index() which will check for the clock index when called from the _indexed() find functions.

NVIDIA GPU Display Driver for Linux contains a vulnerability in the kernel mode layer handler, where an out-of-bounds read may lead to denial of service, information disclosure, or data tampering.

Out-of-bounds read in the Intel(R) Trace Analyzer and Collector software before version 2021.5 may allow an authenticated user to potentially enable escalation of privilege via local access.

In the Linux kernel, the following vulnerability has been resolved: parport: Proper fix for array out-of-bounds access The recent fix for array out-of-bounds accesses replaced sprintf() calls blindly with snprintf(). However, since snprintf() returns the would-be-printed size, not the actually output size, the length calculation can still go over the given limit. Use scnprintf() instead of snprintf(), which returns the actually output letters, for addressing the potential out-of-bounds access properly.

An out-of-bounds access issue was found in the Linux kernel sound subsystem. It could occur when the 'id->name' provided by the user did not end with '\0'. A privileged local user could pass a specially crafted name through ioctl() interface and crash the system or potentially escalate their privileges on the system.

In the Linux kernel, the following vulnerability has been resolved: bpf: Reset register ID for BPF_END value tracking When a register undergoes a BPF_END (byte swap) operation, its scalar value is mutated in-place. If this register previously shared a scalar ID with another register (e.g., after an `r1 = r0` assignment), this tie must be broken. Currently, the verifier misses resetting `dst_reg->id` to 0 for BPF_END. Consequently, if a conditional jump checks the swapped register, the verifier incorrectly propagates the learned bounds to the linked register, leading to false confidence in the linked register's value and potentially allowing out-of-bounds memory accesses. Fix this by explicitly resetting `dst_reg->id` to 0 in the BPF_END case to break the scalar tie, similar to how BPF_NEG handles it via `__mark_reg_known`.

TensorFlow is an end-to-end open source platform for machine learning. A specially crafted TFLite model could trigger an OOB read on heap in the TFLite implementation of `Split_V`(https://github.com/tensorflow/tensorflow/blob/c59c37e7b2d563967da813fa50fe20b21f4da683/tensorflow/lite/kernels/split_v.cc#L99). If `axis_value` is not a value between 0 and `NumDimensions(input)`, then the `SizeOfDimension` function(https://github.com/tensorflow/tensorflow/blob/102b211d892f3abc14f845a72047809b39cc65ab/tensorflow/lite/kernels/kernel_util.h#L148-L150) will access data outside the bounds of the tensor shape 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.

In the Linux kernel, the following vulnerability has been resolved: media: qcom: camss: vfe: Fix out-of-bounds access in vfe_isr_reg_update() vfe_isr() iterates using MSM_VFE_IMAGE_MASTERS_NUM(7) as the loop bound and passes the index to vfe_isr_reg_update(). However, vfe->line[] array is defined with VFE_LINE_NUM_MAX(4): struct vfe_line line[VFE_LINE_NUM_MAX]; When index is 4, 5, 6, the access to vfe->line[line_id] exceeds the array bounds and resulting in out-of-bounds memory access. Fix this by using separate loops for output lines and write masters.

In the Linux kernel, the following vulnerability has been resolved: hwmon: (pmbus/q54sj108a2) fix stack overflow in debugfs read The q54sj108a2_debugfs_read function suffers from a stack buffer overflow due to incorrect arguments passed to bin2hex(). The function currently passes 'data' as the destination and 'data_char' as the source. Because bin2hex() converts each input byte into two hex characters, a 32-byte block read results in 64 bytes of output. Since 'data' is only 34 bytes (I2C_SMBUS_BLOCK_MAX + 2), this writes 30 bytes past the end of the buffer onto the stack. Additionally, the arguments were swapped: it was reading from the zero-initialized 'data_char' and writing to 'data', resulting in all-zero output regardless of the actual I2C read. Fix this by: 1. Expanding 'data_char' to 66 bytes to safely hold the hex output. 2. Correcting the bin2hex() argument order and using the actual read count. 3. Using a pointer to select the correct output buffer for the final simple_read_from_buffer call.

vcs_write in drivers/tty/vt/vc_screen.c in the Linux kernel through 5.3.13 does not prevent write access to vcsu devices, aka CID-0c9acb1af77a.

An issue was discovered in the Linux kernel before 5.2.3. An out of bounds access exists in the function hclge_tm_schd_mode_vnet_base_cfg in the file drivers/net/ethernet/hisilicon/hns3/hns3pf/hclge_tm.c.

An issue was discovered in the Linux kernel before 4.20.2. An out-of-bounds access exists in the function build_audio_procunit in the file sound/usb/mixer.c.

The kernel module has an out-of-bounds read vulnerability.Successful exploitation of this vulnerability may cause memory overwriting.

An Out-Of-Bounds Read Vulnerability in Autodesk FBX SDK version 2020. and prior may lead to code execution or information disclosure through maliciously crafted FBX files. This vulnerability in conjunction with other vulnerabilities could lead to code execution in the context of the current process.

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.

In the Linux kernel, the following vulnerability has been resolved: RDMA/bnxt_re: Fix out of bound check Driver exports pacing stats only on GenP5 and P7 adapters. But while parsing the pacing stats, driver has a check for "rdev->dbr_pacing". This caused a trace when KASAN is enabled. BUG: KASAN: slab-out-of-bounds in bnxt_re_get_hw_stats+0x2b6a/0x2e00 [bnxt_re] Write of size 8 at addr ffff8885942a6340 by task modprobe/4809

The kernel module has an out-of-bounds read vulnerability.Successful exploitation of this vulnerability may cause memory overwriting.

Possible buffer overflow and over read possible due to missing bounds checks for fixed limits if we consider widevine HLOS client as non-trustable in Snapdragon Auto, Snapdragon Compute, Snapdragon Mobile, Snapdragon Wired Infrastructure and Networking in Kamorta, QCS404, Rennell, SC7180, SDX55, SM6150, SM7150, SM8250, SXR2130

Possible out of bound memory access while playing a crafted clip in media player in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in SM8150

Lack of boundary checking of a buffer in set_skb_priv() of modem interface driver prior to SMR Oct-2021 Release 1 allows OOB read and it results in arbitrary code execution by dereference of invalid function pointer.