CVE-2026-23100 : Detail

CVE-2026-23100

5.5
/
Sedang
0.03%V4
2026-02-04
16h08 +00:00
Local
2026-10-15
01h12 +00:00
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Deskripsi CVE

mm/hugetlb: fix hugetlb_pmd_shared()

In the Linux kernel, the following vulnerability has been resolved: mm/hugetlb: fix hugetlb_pmd_shared() Patch series "mm/hugetlb: fixes for PMD table sharing (incl. using mmu_gather)", v3. One functional fix, one performance regression fix, and two related comment fixes. I cleaned up my prototype I recently shared [1] for the performance fix, deferring most of the cleanups I had in the prototype to a later point. While doing that I identified the other things. The goal of this patch set is to be backported to stable trees "fairly" easily. At least patch #1 and #4. Patch #1 fixes hugetlb_pmd_shared() not detecting any sharing Patch #2 + #3 are simple comment fixes that patch #4 interacts with. Patch #4 is a fix for the reported performance regression due to excessive IPI broadcasts during fork()+exit(). The last patch is all about TLB flushes, IPIs and mmu_gather. Read: complicated There are plenty of cleanups in the future to be had + one reasonable optimization on x86. But that's all out of scope for this series. Runtime tested, with a focus on fixing the performance regression using the original reproducer [2] on x86. This patch (of 4): We switched from (wrongly) using the page count to an independent shared count. Now, shared page tables have a refcount of 1 (excluding speculative references) and instead use ptdesc->pt_share_count to identify sharing. We didn't convert hugetlb_pmd_shared(), so right now, we would never detect a shared PMD table as such, because sharing/unsharing no longer touches the refcount of a PMD table. Page migration, like mbind() or migrate_pages() would allow for migrating folios mapped into such shared PMD tables, even though the folios are not exclusive. In smaps we would account them as "private" although they are "shared", and we would be wrongly setting the PM_MMAP_EXCLUSIVE in the pagemap interface. Fix it by properly using ptdesc_pmd_is_shared() in hugetlb_pmd_shared().

Informasi CVE

Kelemahan Terkait

CWE-ID Nama Kelemahan Sumber
CWE Other Tidak ada informasi.

Metrik

Metrik Skor Tingkat keparahan CVSS Vektor Sumber
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 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

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Referensi