CVE-2025-71078 : Detail

CVE-2025-71078

7.8
/
High
0.01%V4
Local
2026-01-13
15h34 +00:00
2026-07-30
06h05 +00:00
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CVE Descriptions

powerpc/64s/slb: Fix SLB multihit issue during SLB preload

In the Linux kernel, the following vulnerability has been resolved: powerpc/64s/slb: Fix SLB multihit issue during SLB preload On systems using the hash MMU, there is a software SLB preload cache that mirrors the entries loaded into the hardware SLB buffer. This preload cache is subject to periodic eviction — typically after every 256 context switches — to remove old entry. To optimize performance, the kernel skips switch_mmu_context() in switch_mm_irqs_off() when the prev and next mm_struct are the same. However, on hash MMU systems, this can lead to inconsistencies between the hardware SLB and the software preload cache. If an SLB entry for a process is evicted from the software cache on one CPU, and the same process later runs on another CPU without executing switch_mmu_context(), the hardware SLB may retain stale entries. If the kernel then attempts to reload that entry, it can trigger an SLB multi-hit error. The following timeline shows how stale SLB entries are created and can cause a multi-hit error when a process moves between CPUs without a MMU context switch. CPU 0 CPU 1 ----- ----- Process P exec swapper/1 load_elf_binary begin_new_exc activate_mm switch_mm_irqs_off switch_mmu_context switch_slb /* * This invalidates all * the entries in the HW * and setup the new HW * SLB entries as per the * preload cache. */ context_switch sched_migrate_task migrates process P to cpu-1 Process swapper/0 context switch (to process P) (uses mm_struct of Process P) switch_mm_irqs_off() switch_slb load_slb++ /* * load_slb becomes 0 here * and we evict an entry from * the preload cache with * preload_age(). We still * keep HW SLB and preload * cache in sync, that is * because all HW SLB entries * anyways gets evicted in * switch_slb during SLBIA. * We then only add those * entries back in HW SLB, * which are currently * present in preload_cache * (after eviction). */ load_elf_binary continues... setup_new_exec() slb_setup_new_exec() sched_switch event sched_migrate_task migrates process P to cpu-0 context_switch from swapper/0 to Process P switch_mm_irqs_off() /* * Since both prev and next mm struct are same we don't call * switch_mmu_context(). This will cause the HW SLB and SW preload * cache to go out of sync in preload_new_slb_context. Because there * was an SLB entry which was evicted from both HW and preload cache * on cpu-1. Now later in preload_new_slb_context(), when we will try * to add the same preload entry again, we will add this to the SW * preload cache and then will add it to the HW SLB. Since on cpu-0 * this entry was never invalidated, hence adding this entry to the HW * SLB will cause a SLB multi-hit error. */ load_elf_binary cont ---truncated---

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.

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) 4.20.1 To (excluding) 5.10.248

Linux>>Linux_kernel >> Version From (including) 5.11 To (excluding) 5.15.198

Linux>>Linux_kernel >> Version From (including) 5.16 To (excluding) 6.1.160

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.120

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.12.64

Linux>>Linux_kernel >> Version From (including) 6.13 To (excluding) 6.18.4

Linux>>Linux_kernel >> Version 4.20

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

References