CVE-2026-43158 : Detail

CVE-2026-43158

8.8
/
High
Overflow
0.11%V4
Network
2026-05-06
12h16 +00:00
2026-05-13
21h20 +00:00
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CVE Descriptions

In the Linux kernel, the following vulnerability has been resolved: xfs: fix freemap adjustments when adding xattrs to leaf blocks xfs/592 and xfs/794 both trip this assertion in the leaf block freemap adjustment code after ~20 minutes of running on my test VMs: ASSERT(ichdr->firstused >= ichdr->count * sizeof(xfs_attr_leaf_entry_t) + xfs_attr3_leaf_hdr_size(leaf)); Upon enabling quite a lot more debugging code, I narrowed this down to fsstress trying to set a local extended attribute with namelen=3 and valuelen=71. This results in an entry size of 80 bytes. At the start of xfs_attr3_leaf_add_work, the freemap looks like this: i 0 base 448 size 0 rhs 448 count 46 i 1 base 388 size 132 rhs 448 count 46 i 2 base 2120 size 4 rhs 448 count 46 firstused = 520 where "rhs" is the first byte past the end of the leaf entry array. This is inconsistent -- the entries array ends at byte 448, but freemap[1] says there's free space starting at byte 388! By the end of the function, the freemap is in worse shape: i 0 base 456 size 0 rhs 456 count 47 i 1 base 388 size 52 rhs 456 count 47 i 2 base 2120 size 4 rhs 456 count 47 firstused = 440 Important note: 388 is not aligned with the entries array element size of 8 bytes. Based on the incorrect freemap, the name area starts at byte 440, which is below the end of the entries array! That's why the assertion triggers and the filesystem shuts down. How did we end up here? First, recall from the previous patch that the freemap array in an xattr leaf block is not intended to be a comprehensive map of all free space in the leaf block. In other words, it's perfectly legal to have a leaf block with: * 376 bytes in use by the entries array * freemap[0] has [base = 376, size = 8] * freemap[1] has [base = 388, size = 1500] * the space between 376 and 388 is free, but the freemap stopped tracking that some time ago If we add one xattr, the entries array grows to 384 bytes, and freemap[0] becomes [base = 384, size = 0]. So far, so good. But if we add a second xattr, the entries array grows to 392 bytes, and freemap[0] gets pushed up to [base = 392, size = 0]. This is bad, because freemap[1] hasn't been updated, and now the entries array and the free space claim the same space. The fix here is to adjust all freemap entries so that none of them collide with the entries array. Note that this fix relies on commit 2a2b5932db6758 ("xfs: fix attr leaf header freemap.size underflow") and the previous patch that resets zero length freemap entries to have base = 0.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-787 Out-of-bounds Write
The product writes data past the end, or before the beginning, of the intended buffer.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 8.8 HIGH CVSS:3.1/AV:N/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.

Network

The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).

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.

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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) 2.6.12.1 To (excluding) 5.10.252

Linux>>Linux_kernel >> Version From (including) 5.11 To (excluding) 5.15.202

Linux>>Linux_kernel >> Version From (including) 5.16 To (excluding) 6.1.165

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.128

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.12.75

Linux>>Linux_kernel >> Version From (including) 6.13 To (excluding) 6.18.16

Linux>>Linux_kernel >> Version From (including) 6.19 To (excluding) 6.19.6

Linux>>Linux_kernel >> Version 2.6.12

Linux>>Linux_kernel >> Version 2.6.12

Linux>>Linux_kernel >> Version 2.6.12

Linux>>Linux_kernel >> Version 2.6.12

Linux>>Linux_kernel >> Version 2.6.12

References