CVE-2026-43116 : Detail

CVE-2026-43116

7.8
/
High
0.02%V4
Local
2026-05-06
10h16 +00:00
2026-09-08
09h18 +00:00
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CVE Descriptions

In the Linux kernel, the following vulnerability has been resolved: netfilter: ctnetlink: ensure safe access to master conntrack Holding reference on the expectation is not sufficient, the master conntrack object can just go away, making exp->master invalid. To access exp->master safely: - Grab the nf_conntrack_expect_lock, this gets serialized with clean_from_lists() which also holds this lock when the master conntrack goes away. - Hold reference on master conntrack via nf_conntrack_find_get(). Not so easy since the master tuple to look up for the master conntrack is not available in the existing problematic paths. This patch goes for extending the nf_conntrack_expect_lock section to address this issue for simplicity, in the cases that are described below this is just slightly extending the lock section. The add expectation command already holds a reference to the master conntrack from ctnetlink_create_expect(). However, the delete expectation command needs to grab the spinlock before looking up for the expectation. Expand the existing spinlock section to address this to cover the expectation lookup. Note that, the nf_ct_expect_iterate_net() calls already grabs the spinlock while iterating over the expectation table, which is correct. The get expectation command needs to grab the spinlock to ensure master conntrack does not go away. This also expands the existing spinlock section to cover the expectation lookup too. I needed to move the netlink skb allocation out of the spinlock to keep it GFP_KERNEL. For the expectation events, the IPEXP_DESTROY event is already delivered under the spinlock, just move the delivery of IPEXP_NEW under the spinlock too because the master conntrack event cache is reached through exp->master. While at it, add lockdep notations to help identify what codepaths need to grab the spinlock.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-362 Concurrent Execution using Shared Resource with Improper Synchronization ('Race Condition')
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.

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.

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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) 2.6.16 To (excluding) 6.18.24

Linux>>Linux_kernel >> Version From (including) 6.19 To (excluding) 6.19.14

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

References