CVE-2026-23371 : Detail

CVE-2026-23371

5.5
/
Medium
0.02%V4
Local
2026-03-25
11h16 +00:00
2026-06-01
17h16 +00:00
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CVE Descriptions

In the Linux kernel, the following vulnerability has been resolved: sched/deadline: Fix missing ENQUEUE_REPLENISH during PI de-boosting Running stress-ng --schedpolicy 0 on an RT kernel on a big machine might lead to the following WARNINGs (edited). sched: DL de-boosted task PID 22725: REPLENISH flag missing WARNING: CPU: 93 PID: 0 at kernel/sched/deadline.c:239 dequeue_task_dl+0x15c/0x1f8 ... (running_bw underflow) Call trace: dequeue_task_dl+0x15c/0x1f8 (P) dequeue_task+0x80/0x168 deactivate_task+0x24/0x50 push_dl_task+0x264/0x2e0 dl_task_timer+0x1b0/0x228 __hrtimer_run_queues+0x188/0x378 hrtimer_interrupt+0xfc/0x260 ... The problem is that when a SCHED_DEADLINE task (lock holder) is changed to a lower priority class via sched_setscheduler(), it may fail to properly inherit the parameters of potential DEADLINE donors if it didn't already inherit them in the past (shorter deadline than donor's at that time). This might lead to bandwidth accounting corruption, as enqueue_task_dl() won't recognize the lock holder as boosted. The scenario occurs when: 1. A DEADLINE task (donor) blocks on a PI mutex held by another DEADLINE task (holder), but the holder doesn't inherit parameters (e.g., it already has a shorter deadline) 2. sched_setscheduler() changes the holder from DEADLINE to a lower class while still holding the mutex 3. The holder should now inherit DEADLINE parameters from the donor and be enqueued with ENQUEUE_REPLENISH, but this doesn't happen Fix the issue by introducing __setscheduler_dl_pi(), which detects when a DEADLINE (proper or boosted) task gets setscheduled to a lower priority class. In case, the function makes the task inherit DEADLINE parameters of the donoer (pi_se) and sets ENQUEUE_REPLENISH flag to ensure proper bandwidth accounting during the next enqueue operation.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE Other No informations.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 5.5 MEDIUM CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/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.

None

There is no loss of confidentiality within the impacted component.

Integrity Impact

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

None

There is no loss of integrity within 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) 4.19.257 To (excluding) 4.20

Linux>>Linux_kernel >> Version From (including) 5.4.212 To (excluding) 5.5

Linux>>Linux_kernel >> Version From (including) 5.10.1 To (excluding) 6.19.7

Linux>>Linux_kernel >> Version 5.10

Linux>>Linux_kernel >> Version 7.0

Linux>>Linux_kernel >> Version 7.0

Linux>>Linux_kernel >> Version 7.0

Linux>>Linux_kernel >> Version 7.0

Linux>>Linux_kernel >> Version 7.0

Linux>>Linux_kernel >> Version 7.0

Linux>>Linux_kernel >> Version 7.0

References