CVE-2022-49446
Feb. 26, 2025, 7:01 a.m.
None
No Score
Description
In the Linux kernel, the following vulnerability has been resolved:
nvdimm: Fix firmware activation deadlock scenarios
Lockdep reports the following deadlock scenarios for CXL root device
power-management, device_prepare(), operations, and device_shutdown()
operations for 'nd_region' devices:
Chain exists of:
&nvdimm_region_key --> &nvdimm_bus->reconfig_mutex --> system_transition_mutex
Possible unsafe locking scenario:
CPU0 CPU1
---- ----
lock(system_transition_mutex);
lock(&nvdimm_bus->reconfig_mutex);
lock(system_transition_mutex);
lock(&nvdimm_region_key);
Chain exists of:
&cxl_nvdimm_bridge_key --> acpi_scan_lock --> &cxl_root_key
Possible unsafe locking scenario:
CPU0 CPU1
---- ----
lock(&cxl_root_key);
lock(acpi_scan_lock);
lock(&cxl_root_key);
lock(&cxl_nvdimm_bridge_key);
These stem from holding nvdimm_bus_lock() over hibernate_quiet_exec()
which walks the entire system device topology taking device_lock() along
the way. The nvdimm_bus_lock() is protecting against unregistration,
multiple simultaneous ops callers, and preventing activate_show() from
racing activate_store(). For the first 2, the lock is redundant.
Unregistration already flushes all ops users, and sysfs already prevents
multiple threads to be active in an ops handler at the same time. For
the last userspace should already be waiting for its last
activate_store() to complete, and does not need activate_show() to flush
the write side, so this lock usage can be deleted in these attributes.
Product(s) Impacted
Product | Versions |
---|---|
Linux Kernel |
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
References
Tags
Timeline
Published: Feb. 26, 2025, 7:01 a.m.
Last Modified: Feb. 26, 2025, 7:01 a.m.
Last Modified: Feb. 26, 2025, 7:01 a.m.
Status : Awaiting Analysis
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.