CVE-2025-21983 : Detail

CVE-2025-21983

7.8
/
High
0.1%V4
Local
2025-04-01
15h47 +00:00
2025-05-04
07h26 +00:00
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CVE Descriptions

mm/slab/kvfree_rcu: Switch to WQ_MEM_RECLAIM wq

In the Linux kernel, the following vulnerability has been resolved: mm/slab/kvfree_rcu: Switch to WQ_MEM_RECLAIM wq Currently kvfree_rcu() APIs use a system workqueue which is "system_unbound_wq" to driver RCU machinery to reclaim a memory. Recently, it has been noted that the following kernel warning can be observed: workqueue: WQ_MEM_RECLAIM nvme-wq:nvme_scan_work is flushing !WQ_MEM_RECLAIM events_unbound:kfree_rcu_work WARNING: CPU: 21 PID: 330 at kernel/workqueue.c:3719 check_flush_dependency+0x112/0x120 Modules linked in: intel_uncore_frequency(E) intel_uncore_frequency_common(E) skx_edac(E) ... CPU: 21 UID: 0 PID: 330 Comm: kworker/u144:6 Tainted: G E 6.13.2-0_g925d379822da #1 Hardware name: Wiwynn Twin Lakes MP/Twin Lakes Passive MP, BIOS YMM20 02/01/2023 Workqueue: nvme-wq nvme_scan_work RIP: 0010:check_flush_dependency+0x112/0x120 Code: 05 9a 40 14 02 01 48 81 c6 c0 00 00 00 48 8b 50 18 48 81 c7 c0 00 00 00 48 89 f9 48 ... RSP: 0018:ffffc90000df7bd8 EFLAGS: 00010082 RAX: 000000000000006a RBX: ffffffff81622390 RCX: 0000000000000027 RDX: 00000000fffeffff RSI: 000000000057ffa8 RDI: ffff88907f960c88 RBP: 0000000000000000 R08: ffffffff83068e50 R09: 000000000002fffd R10: 0000000000000004 R11: 0000000000000000 R12: ffff8881001a4400 R13: 0000000000000000 R14: ffff88907f420fb8 R15: 0000000000000000 FS: 0000000000000000(0000) GS:ffff88907f940000(0000) knlGS:0000000000000000 CR2: 00007f60c3001000 CR3: 000000107d010005 CR4: 00000000007726f0 PKRU: 55555554 Call Trace: ? __warn+0xa4/0x140 ? check_flush_dependency+0x112/0x120 ? report_bug+0xe1/0x140 ? check_flush_dependency+0x112/0x120 ? handle_bug+0x5e/0x90 ? exc_invalid_op+0x16/0x40 ? asm_exc_invalid_op+0x16/0x20 ? timer_recalc_next_expiry+0x190/0x190 ? check_flush_dependency+0x112/0x120 ? check_flush_dependency+0x112/0x120 __flush_work.llvm.1643880146586177030+0x174/0x2c0 flush_rcu_work+0x28/0x30 kvfree_rcu_barrier+0x12f/0x160 kmem_cache_destroy+0x18/0x120 bioset_exit+0x10c/0x150 disk_release.llvm.6740012984264378178+0x61/0xd0 device_release+0x4f/0x90 kobject_put+0x95/0x180 nvme_put_ns+0x23/0xc0 nvme_remove_invalid_namespaces+0xb3/0xd0 nvme_scan_work+0x342/0x490 process_scheduled_works+0x1a2/0x370 worker_thread+0x2ff/0x390 ? pwq_release_workfn+0x1e0/0x1e0 kthread+0xb1/0xe0 ? __kthread_parkme+0x70/0x70 ret_from_fork+0x30/0x40 ? __kthread_parkme+0x70/0x70 ret_from_fork_asm+0x11/0x20 ---[ end trace 0000000000000000 ]--- To address this switch to use of independent WQ_MEM_RECLAIM workqueue, so the rules are not violated from workqueue framework point of view. Apart of that, since kvfree_rcu() does reclaim memory it is worth to go with WQ_MEM_RECLAIM type of wq because it is designed for this purpose.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE Other No informations.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 7.8 HIGH CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Base: Exploitabilty Metrics

The Exploitability metrics reflect the characteristics of the thing that is vulnerable, which we refer to formally as the vulnerable component.

Attack Vector

This metric reflects the context by which vulnerability exploitation is possible.

Local

The vulnerable component is not bound to the network stack and the attacker’s path is via read/write/execute capabilities.

Attack Complexity

This metric describes the conditions beyond the attacker’s control that must exist in order to exploit the vulnerability.

Low

Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success when attacking the vulnerable component.

Privileges Required

This metric describes the level of privileges an attacker must possess before successfully exploiting the vulnerability.

Low

The attacker requires privileges that provide basic user capabilities that could normally affect only settings and files owned by a user. Alternatively, an attacker with Low privileges has the ability to access only non-sensitive resources.

User Interaction

This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable component.

None

The vulnerable system can be exploited without interaction from any user.

Base: Scope Metrics

The Scope metric captures whether a vulnerability in one vulnerable component impacts resources in components beyond its security scope.

Scope

Formally, a security authority is a mechanism (e.g., an application, an operating system, firmware, a sandbox environment) that defines and enforces access control in terms of how certain subjects/actors (e.g., human users, processes) can access certain restricted objects/resources (e.g., files, CPU, memory) in a controlled manner. All the subjects and objects under the jurisdiction of a single security authority are considered to be under one security scope. If a vulnerability in a vulnerable component can affect a component which is in a different security scope than the vulnerable component, a Scope change occurs. Intuitively, whenever the impact of a vulnerability breaches a security/trust boundary and impacts components outside the security scope in which vulnerable component resides, a Scope change occurs.

Unchanged

An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.

Base: Impact Metrics

The Impact metrics capture the effects of a successfully exploited vulnerability on the component that suffers the worst outcome that is most directly and predictably associated with the attack. Analysts should constrain impacts to a reasonable, final outcome which they are confident an attacker is able to achieve.

Confidentiality Impact

This metric measures the impact to the confidentiality of the information resources managed by a software component due to a successfully exploited vulnerability.

High

There is a total loss of confidentiality, resulting in all resources within the impacted component being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server.

Integrity Impact

This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information.

High

There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the impacted component. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the impacted component.

Availability Impact

This metric measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability.

High

There is a total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).

Temporal Metrics

The Temporal metrics measure the current state of exploit techniques or code availability, the existence of any patches or workarounds, or the confidence in the description of a vulnerability.

Environmental Metrics

These metrics enable the analyst to customize the CVSS score depending on the importance of the affected IT asset to a user’s organization, measured in terms of Confidentiality, Integrity, and Availability.

nvd@nist.gov

EPSS

EPSS is a scoring model that predicts the likelihood of a vulnerability being exploited.

EPSS Score

The EPSS model produces a probability score between 0 and 1 (0 and 100%). The higher the score, the greater the probability that a vulnerability will be exploited.

EPSS Percentile

The percentile is used to rank CVE according to their EPSS score. For example, a CVE in the 95th percentile according to its EPSS score is more likely to be exploited than 95% of other CVE. Thus, the percentile is used to compare the EPSS score of a CVE with that of other CVE.

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 6.12 To (excluding) 6.12.20

Linux>>Linux_kernel >> Version From (including) 6.13 To (excluding) 6.13.8

Linux>>Linux_kernel >> Version 6.14

Linux>>Linux_kernel >> Version 6.14

Linux>>Linux_kernel >> Version 6.14

Linux>>Linux_kernel >> Version 6.14

Linux>>Linux_kernel >> Version 6.14

References