CVE-2026-23342 : Detail

CVE-2026-23342

4.7
/
Sedang
0.01%V4
2026-03-25
11h16 +00:00
Local
2026-04-23
21h16 +00:00
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Deskripsi CVE

In the Linux kernel, the following vulnerability has been resolved: bpf: Fix race in cpumap on PREEMPT_RT On PREEMPT_RT kernels, the per-CPU xdp_bulk_queue (bq) can be accessed concurrently by multiple preemptible tasks on the same CPU. The original code assumes bq_enqueue() and __cpu_map_flush() run atomically with respect to each other on the same CPU, relying on local_bh_disable() to prevent preemption. However, on PREEMPT_RT, local_bh_disable() only calls migrate_disable() (when PREEMPT_RT_NEEDS_BH_LOCK is not set) and does not disable preemption, which allows CFS scheduling to preempt a task during bq_flush_to_queue(), enabling another task on the same CPU to enter bq_enqueue() and operate on the same per-CPU bq concurrently. This leads to several races: 1. Double __list_del_clearprev(): after bq->count is reset in bq_flush_to_queue(), a preempting task can call bq_enqueue() -> bq_flush_to_queue() on the same bq when bq->count reaches CPU_MAP_BULK_SIZE. Both tasks then call __list_del_clearprev() on the same bq->flush_node, the second call dereferences the prev pointer that was already set to NULL by the first. 2. bq->count and bq->q[] races: concurrent bq_enqueue() can corrupt the packet queue while bq_flush_to_queue() is processing it. The race between task A (__cpu_map_flush -> bq_flush_to_queue) and task B (bq_enqueue -> bq_flush_to_queue) on the same CPU: Task A (xdp_do_flush) Task B (cpu_map_enqueue) ---------------------- ------------------------ bq_flush_to_queue(bq) spin_lock(&q->producer_lock) /* flush bq->q[] to ptr_ring */ bq->count = 0 spin_unlock(&q->producer_lock) bq_enqueue(rcpu, xdpf) <-- CFS preempts Task A --> bq->q[bq->count++] = xdpf /* ... more enqueues until full ... */ bq_flush_to_queue(bq) spin_lock(&q->producer_lock) /* flush to ptr_ring */ spin_unlock(&q->producer_lock) __list_del_clearprev(flush_node) /* sets flush_node.prev = NULL */ <-- Task A resumes --> __list_del_clearprev(flush_node) flush_node.prev->next = ... /* prev is NULL -> kernel oops */ Fix this by adding a local_lock_t to xdp_bulk_queue and acquiring it in bq_enqueue() and __cpu_map_flush(). These paths already run under local_bh_disable(), so use local_lock_nested_bh() which on non-RT is a pure annotation with no overhead, and on PREEMPT_RT provides a per-CPU sleeping lock that serializes access to the bq. To reproduce, insert an mdelay(100) between bq->count = 0 and __list_del_clearprev() in bq_flush_to_queue(), then run reproducer provided by syzkaller.

Informasi CVE

Kelemahan Terkait

CWE-ID Nama Kelemahan Sumber
CWE-362 Concurrent Execution using Shared Resource with Improper Synchronization
The product contains a concurrent code sequence that requires temporary, exclusive access to a shared resource, but a timing window exists in which the shared resource can be modified by another code sequence operating concurrently.

Metrik

Metrik Skor Tingkat keparahan CVSS Vektor Sumber
V3.1 4.7 MEDIUM CVSS:3.1/AV:L/AC:H/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.

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.

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 adalah model penilaian yang memprediksi kemungkinan suatu kerentanan dieksploitasi.

Skor EPSS

Model EPSS menghasilkan skor probabilitas antara 0 dan 1 (0 hingga 100%). Semakin tinggi skor, semakin besar probabilitas bahwa suatu kerentanan akan dieksploitasi.

Persentil EPSS

Persentil digunakan untuk meranking CVE berdasarkan skor EPSS mereka. Misalnya, CVE di persentil ke-95 berdasarkan skor EPSS-nya lebih mungkin dieksploitasi daripada 95% CVE lainnya. Dengan demikian, persentil digunakan untuk membandingkan skor EPSS suatu CVE dengan CVE lainnya.

Produk yang Disebutkan

Konfigurasi 0

Linux>>Linux_kernel >> Version Dari (termasuk) 6.18.1 Hingga (tidak termasuk) 6.18.17

Linux>>Linux_kernel >> Version Dari (termasuk) 6.19 Hingga (tidak termasuk) 6.19.7

Linux>>Linux_kernel >> Version 6.18

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

Referensi