CVE-2022-48847

July 16, 2024, 1:43 p.m.

None
No Score

Description

In the Linux kernel, the following vulnerability has been resolved: watch_queue: Fix filter limit check In watch_queue_set_filter(), there are a couple of places where we check that the filter type value does not exceed what the type_filter bitmap can hold. One place calculates the number of bits by: if (tf[i].type >= sizeof(wfilter->type_filter) * 8) which is fine, but the second does: if (tf[i].type >= sizeof(wfilter->type_filter) * BITS_PER_LONG) which is not. This can lead to a couple of out-of-bounds writes due to a too-large type: (1) __set_bit() on wfilter->type_filter (2) Writing more elements in wfilter->filters[] than we allocated. Fix this by just using the proper WATCH_TYPE__NR instead, which is the number of types we actually know about. The bug may cause an oops looking something like: BUG: KASAN: slab-out-of-bounds in watch_queue_set_filter+0x659/0x740 Write of size 4 at addr ffff88800d2c66bc by task watch_queue_oob/611 ... Call Trace: <TASK> dump_stack_lvl+0x45/0x59 print_address_description.constprop.0+0x1f/0x150 ... kasan_report.cold+0x7f/0x11b ... watch_queue_set_filter+0x659/0x740 ... __x64_sys_ioctl+0x127/0x190 do_syscall_64+0x43/0x90 entry_SYSCALL_64_after_hwframe+0x44/0xae Allocated by task 611: kasan_save_stack+0x1e/0x40 __kasan_kmalloc+0x81/0xa0 watch_queue_set_filter+0x23a/0x740 __x64_sys_ioctl+0x127/0x190 do_syscall_64+0x43/0x90 entry_SYSCALL_64_after_hwframe+0x44/0xae The buggy address belongs to the object at ffff88800d2c66a0 which belongs to the cache kmalloc-32 of size 32 The buggy address is located 28 bytes inside of 32-byte region [ffff88800d2c66a0, ffff88800d2c66c0)

Timeline

Published: July 16, 2024, 1:15 p.m.
Last Modified: July 16, 2024, 1:43 p.m.

Status : Awaiting Analysis

CVE has been marked for Analysis. Normally once in this state the CVE will be analyzed by NVD staff within 24 hours.

More info

Source

416baaa9-dc9f-4396-8d5f-8c081fb06d67

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.