CVE-2025-39749 : Detail

CVE-2025-39749

7
/
High
0.02%V4
Local
2025-09-11
16h52 +00:00
2026-05-12
12h06 +00:00
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CVE Descriptions

rcu: Protect ->defer_qs_iw_pending from data race

In the Linux kernel, the following vulnerability has been resolved: rcu: Protect ->defer_qs_iw_pending from data race On kernels built with CONFIG_IRQ_WORK=y, when rcu_read_unlock() is invoked within an interrupts-disabled region of code [1], it will invoke rcu_read_unlock_special(), which uses an irq-work handler to force the system to notice when the RCU read-side critical section actually ends. That end won't happen until interrupts are enabled at the soonest. In some kernels, such as those booted with rcutree.use_softirq=y, the irq-work handler is used unconditionally. The per-CPU rcu_data structure's ->defer_qs_iw_pending field is updated by the irq-work handler and is both read and updated by rcu_read_unlock_special(). This resulted in the following KCSAN splat: ------------------------------------------------------------------------ BUG: KCSAN: data-race in rcu_preempt_deferred_qs_handler / rcu_read_unlock_special read to 0xffff96b95f42d8d8 of 1 bytes by task 90 on cpu 8: rcu_read_unlock_special+0x175/0x260 __rcu_read_unlock+0x92/0xa0 rt_spin_unlock+0x9b/0xc0 __local_bh_enable+0x10d/0x170 __local_bh_enable_ip+0xfb/0x150 rcu_do_batch+0x595/0xc40 rcu_cpu_kthread+0x4e9/0x830 smpboot_thread_fn+0x24d/0x3b0 kthread+0x3bd/0x410 ret_from_fork+0x35/0x40 ret_from_fork_asm+0x1a/0x30 write to 0xffff96b95f42d8d8 of 1 bytes by task 88 on cpu 8: rcu_preempt_deferred_qs_handler+0x1e/0x30 irq_work_single+0xaf/0x160 run_irq_workd+0x91/0xc0 smpboot_thread_fn+0x24d/0x3b0 kthread+0x3bd/0x410 ret_from_fork+0x35/0x40 ret_from_fork_asm+0x1a/0x30 no locks held by irq_work/8/88. irq event stamp: 200272 hardirqs last enabled at (200272): [] finish_task_switch+0x131/0x320 hardirqs last disabled at (200271): [] __schedule+0x129/0xd70 softirqs last enabled at (0): [] copy_process+0x4df/0x1cc0 softirqs last disabled at (0): [<0000000000000000>] 0x0 ------------------------------------------------------------------------ The problem is that irq-work handlers run with interrupts enabled, which means that rcu_preempt_deferred_qs_handler() could be interrupted, and that interrupt handler might contain an RCU read-side critical section, which might invoke rcu_read_unlock_special(). In the strict KCSAN mode of operation used by RCU, this constitutes a data race on the ->defer_qs_iw_pending field. This commit therefore disables interrupts across the portion of the rcu_preempt_deferred_qs_handler() that updates the ->defer_qs_iw_pending field. This suffices because this handler is not a fast path.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE Other No informations.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 7 HIGH CVSS:3.1/AV:L/AC:H/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.

High

successful attack depends on conditions beyond the attacker's control. That is, a successful attack cannot be accomplished at will, but requires the attacker to invest in some measurable amount of effort in preparation or execution against the vulnerable component before a successful attack can be expected.

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) 5.3 To (excluding) 5.4.297

Linux>>Linux_kernel >> Version From (including) 5.5 To (excluding) 5.10.241

Linux>>Linux_kernel >> Version From (including) 5.11 To (excluding) 5.15.190

Linux>>Linux_kernel >> Version From (including) 5.16 To (excluding) 6.1.149

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.103

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.12.43

Linux>>Linux_kernel >> Version From (including) 6.13 To (excluding) 6.15.11

Linux>>Linux_kernel >> Version From (including) 6.16 To (excluding) 6.16.2

Configuraton 0

Debian>>Debian_linux >> Version 11.0

References