An out-of-bounds read vulnerability in WLAvalancheService component of Ivanti Avalanche before 6.4.3, in certain conditions can allow an authenticated remote attacker to read sensitive information in memory.
An out-of-bounds read vulnerability in WLAvalancheService component of Ivanti Avalanche before 6.4.3, in certain conditions can allow an unauthenticated remote attacker to read sensitive information in memory.
An out-of-bounds read vulnerability in WLAvalancheService component of Ivanti Avalanche before 6.4.3, in certain conditions can allow an unauthenticated remote attacker to read sensitive information in memory.
An out-of-bounds read vulnerability in WLAvalancheService component of Ivanti Avalanche before 6.4.3, in certain conditions can allow an unauthenticated remote attacker to read sensitive information in memory.
An out-of-bounds read vulnerability in WLAvalancheService component of Ivanti Avalanche before 6.4.3, in certain conditions can allow an unauthenticated remote attacker to read sensitive information in memory.
In the Linux kernel, the following vulnerability has been resolved: fbdev: Fix invalid page access after closing deferred I/O devices When a fbdev with deferred I/O is once opened and closed, the dirty pages still remain queued in the pageref list, and eventually later those may be processed in the delayed work. This may lead to a corruption of pages, hitting an Oops. This patch makes sure to cancel the delayed work and clean up the pageref list at closing the device for addressing the bug. A part of the cleanup code is factored out as a new helper function that is called from the common fb_release().
A weakness has been identified in QuickJS up to eb2c89087def1829ed99630cb14b549d7a98408c. This affects the function js_array_buffer_slice of the file quickjs.c. This manipulation causes buffer over-read. The attack is restricted to local execution. The exploit has been made available to the public and could be exploited. This product adopts a rolling release strategy to maintain continuous delivery Patch name: c6fe5a98fd3ef3b7064e6e0145dfebfe12449fea. To fix this issue, it is recommended to deploy a patch.
Buffer Overflow vulenrability in Ffmpeg v.N113007-g8d24a28d06 allows a local attacker to execute arbitrary code via the libavcodec/jpegxl_parser.c in gen_alias_map.
TensorFlow is an open source platform for machine learning. In affected versions the code for sparse matrix multiplication is vulnerable to undefined behavior via binding a reference to `nullptr`. This occurs whenever the dimensions of `a` or `b` are 0 or less. In the case on one of these is 0, an empty output tensor should be allocated (to conserve the invariant that output tensors are always allocated when the operation is successful) but nothing should be written to it (that is, we should return early from the kernel implementation). Otherwise, attempts to write to this empty tensor would result in 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.
A local privilege escalation vulnerability was found on polkit's pkexec utility. The pkexec application is a setuid tool designed to allow unprivileged users to run commands as privileged users according predefined policies. The current version of pkexec doesn't handle the calling parameters count correctly and ends trying to execute environment variables as commands. An attacker can leverage this by crafting environment variables in such a way it'll induce pkexec to execute arbitrary code. When successfully executed the attack can cause a local privilege escalation given unprivileged users administrative rights on the target machine.
An out-of-bounds read was addressed with improved bounds checking. This issue is fixed in macOS Sonoma 14.2, macOS Ventura 13.6.3, macOS Monterey 12.7.2. A user may be able to cause unexpected app termination or arbitrary code execution.
An improper input validation in saped_rec_silence in libsaped prior to SMR Nov-2023 Release 1 allows local attackers to cause out-of-bounds read and write.
An improper input validation in saped_dec in libsaped prior to SMR Nov-2023 Release 1 allows local attackers to cause out-of-bounds read and write.
An improper input validation in get_head_crc in libsaped prior to SMR Nov-2023 Release 1 allows local attackers to cause out-of-bounds read and write.
A crafted NTFS image can cause an out-of-bounds read in ntfs_runlists_merge_i in NTFS-3G < 2021.8.22.
A crafted NTFS image can cause an out-of-bounds read in ntfs_ie_lookup in NTFS-3G < 2021.8.22.
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.
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
A crafted NTFS image can cause out-of-bounds reads in ntfs_attr_find and ntfs_external_attr_find in NTFS-3G < 2021.8.22.
Windows Common Log File System Driver Elevation of Privilege Vulnerability
Windows Kernel Elevation of Privilege Vulnerability
Windows Common Log File System Driver Elevation of Privilege Vulnerability
Windows Kernel Elevation of Privilege Vulnerability
An integer overflow in Silicon Labs Gecko Bootloader version 4.3.1 and earlier allows unbounded memory access when reading from or writing to storage slots.
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.
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.
It was discovered that the eBPF implementation in the Linux kernel did not properly track bounds information for 32 bit registers when performing div and mod operations. A local attacker could use this to possibly execute arbitrary code.
Memory corruption while processing buffer initialization, when trusted report for certain report types are generated.
This vulnerability allows local attackers to escalate privileges on affected installations of Linux Kernel 5.14-rc3. An attacker must first obtain the ability to execute low-privileged code on the target system in order to exploit this vulnerability. The specific flaw exists within the handling of eBPF programs. The issue results from the lack of proper validation of user-supplied eBPF programs, which can result in a type confusion condition. An attacker can leverage this vulnerability to escalate privileges and execute arbitrary code in the context of the kernel. Was ZDI-CAN-14689.
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.
Microsoft PostScript Printer Driver Remote Code Execution Vulnerability
mlocate's %post script allows RUN_UPDATEDB_AS user to make arbitrary files world readable by abusing insecure file operations that run with root privileges.
The cam_get_device_priv function does not check the type of handle being returned (device/session/link). This would lead to invalid type usage if a wrong handle is passed to it.
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.
Memory Corruption in WLAN HOST while fetching TX status information.
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
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.
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.
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
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).
The snd_msnd_interrupt function in sound/isa/msnd/msnd_pinnacle.c in the Linux kernel through 4.11.7 allows local users to cause a denial of service (over-boundary access) or possibly have unspecified other impact by changing the value of a message queue head pointer between two kernel reads of that value, aka a "double fetch" vulnerability.
Access of resource using incompatible type ('type confusion') in Microsoft Office allows an unauthorized attacker to execute code locally.
A malformed SMI (System Management Interface) command may allow an attacker to establish a corrupted SMI Trigger Info data structure, potentially leading to out-of-bounds memory reads and writes when triggering an SMI resulting in a potential loss of resources.
Out-of-bounds read in Windows Encrypting File System (EFS) allows an authorized attacker to elevate privileges locally.
A weakness has been identified in FascinatedBox lily up to 2.3. This vulnerability affects the function count_transforms of the file src/lily_emitter.c. This manipulation causes out-of-bounds read. The attack can only be executed locally. The exploit has been made available to the public and could be used for attacks. The project was informed of the problem early through an issue report but has not responded yet.
Out-of-bounds read in Windows NTFS allows an authorized attacker to elevate privileges locally.
A possible buffer overflow vulnerability in libSPenBase library of Samsung Notes prior to Samsung Note version 4.3.02.61 allows arbitrary code execution.
Win32k Elevation of Privilege Vulnerability
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.
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.