CVE-2021-47584
June 19, 2024, 3:15 p.m.
None
No Score
Description
In the Linux kernel, the following vulnerability has been resolved:
iocost: Fix divide-by-zero on donation from low hweight cgroup
The donation calculation logic assumes that the donor has non-zero
after-donation hweight, so the lowest active hweight a donating cgroup can
have is 2 so that it can donate 1 while keeping the other 1 for itself.
Earlier, we only donated from cgroups with sizable surpluses so this
condition was always true. However, with the precise donation algorithm
implemented, f1de2439ec43 ("blk-iocost: revamp donation amount
determination") made the donation amount calculation exact enabling even low
hweight cgroups to donate.
This means that in rare occasions, a cgroup with active hweight of 1 can
enter donation calculation triggering the following warning and then a
divide-by-zero oops.
WARNING: CPU: 4 PID: 0 at block/blk-iocost.c:1928 transfer_surpluses.cold+0x0/0x53 [884/94867]
...
RIP: 0010:transfer_surpluses.cold+0x0/0x53
Code: 92 ff 48 c7 c7 28 d1 ab b5 65 48 8b 34 25 00 ae 01 00 48 81 c6 90 06 00 00 e8 8b 3f fe ff 48 c7 c0 ea ff ff ff e9 95 ff 92 ff <0f> 0b 48 c7 c7 30 da ab b5 e8 71 3f fe ff 4c 89 e8 4d 85 ed 74 0
4
...
Call Trace:
<IRQ>
ioc_timer_fn+0x1043/0x1390
call_timer_fn+0xa1/0x2c0
__run_timers.part.0+0x1ec/0x2e0
run_timer_softirq+0x35/0x70
...
iocg: invalid donation weights in /a/b: active=1 donating=1 after=0
Fix it by excluding cgroups w/ active hweight < 2 from donating. Excluding
these extreme low hweight donations shouldn't affect work conservation in
any meaningful way.
Product(s) Impacted
Product | Versions |
---|---|
Linux kernel |
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
Tags
Timeline
Published: June 19, 2024, 3:15 p.m.
Last Modified: June 19, 2024, 3:15 p.m.
Last Modified: June 19, 2024, 3:15 p.m.
Status : Received
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
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.