CVE Descriptions

In the Linux kernel, the following vulnerability has been resolved: KVM: x86: Fix shadow paging use-after-free due to unexpected GFN The shadow MMU computes GFNs for direct shadow pages using sp->gfn plus the SPTE index. This assumption breaks for shadow paging if the guest page tables are modified between VM entries (similar to commit aad885e77496, "KVM: x86/mmu: Drop/zap existing present SPTE even when creating an MMIO SPTE", 2026-03-27). The flow is as follows: - a PDE is installed for a 2MB mapping, and a page in that area is accessed. KVM creates a kvm_mmu_page consisting of 512 4KB pages; the kvm_mmu_page is marked by FNAME(fetch) as direct-mapped because the guest's mapping is a huge page (and thus contiguous). - the PDE mapping is changed from outside the guest. - the guest accesses another page in the same 2MB area. KVM installs a new leaf SPTE and rmap entry; the SPTE uses the "correct" GFN (i.e. based on the new mapping, as changed in the previous step) but that GFN is outside of the [sp->gfn, sp->gfn + 511] range; therefore the rmap entry cannot be found and removed when the kvm_mmu_page is zapped. - the memslot that covers the first 2MB mapping is deleted, and the kvm_mmu_page for the now-invalid GPA is zapped. However, rmap_remove() only looks at the [sp->gfn, sp->gfn + 511] range established in step 1, and fails to find the rmap entry that was recorded by step 3. - any operation that causes an rmap walk for the same page accessed by step 3 then walks a stale rmap and dereferences a freed kvm_mmu_page. This includes dirty logging or MMU notifier invalidations (e.g., from MADV_DONTNEED). The underlying issue is that KVM's walking of shadow PTEs assumes that if a SPTE is present when KVM wants to install a non-leaf SPTE, then the existing kvm_mmu_page must be for the correct gfn. Because the only way for the gfn to be wrong is if KVM messed up and failed to zap a SPTE... which shouldn't happen, but *actually* only happens in response to a guest write. That bug dates back literally forever, as even the first version of KVM assumes that the GFN matches and walks into the "wrong" shadow page. However, that was only an imprecision until 2032a93d66fa ("KVM: MMU: Don't allocate gfns page for direct mmu pages") came along. Fix it by checking for a target gfn mismatch and zapping the existing SPTE. That way the old SP and rmap entries are gone, KVM installs the rmap in the right location, and everyone is happy.

CVE Informations

Related Weaknesses

CWE-ID	Weakness Name	Source
CWE-416	Use After Free The product reuses or references memory after it has been freed. At some point afterward, the memory may be allocated again and saved in another pointer, while the original pointer references a location somewhere within the new allocation. Any operations using the original pointer are no longer valid because the memory "belongs" to the code that operates on the new pointer.

Metrics

Metrics	Score	Severity	CVSS Vector	Source
V3.1	8.8	HIGH	CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H More informations 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. Changed An exploited vulnerability can affect resources beyond the security scope managed by the security authority of the vulnerable component. In this case, the vulnerable component and the impacted component are different and managed by different security authorities. 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.	416baaa9-dc9f-4396-8d5f-8c081fb06d67

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.

EPSS First.org