CVE-2022-49290

Score / Severity

7.8

High

EPSS

0.01%V4

Vector

Local

Published

2025-02-26
01h56 +00:00

Modified

2025-02-26
01h56 +00:00

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CVE.org

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CVE Descriptions

mac80211: fix potential double free on mesh join

In the Linux kernel, the following vulnerability has been resolved: mac80211: fix potential double free on mesh join While commit 6a01afcf8468 ("mac80211: mesh: Free ie data when leaving mesh") fixed a memory leak on mesh leave / teardown it introduced a potential memory corruption caused by a double free when rejoining the mesh: ieee80211_leave_mesh() -> kfree(sdata->u.mesh.ie); ... ieee80211_join_mesh() -> copy_mesh_setup() -> old_ie = ifmsh->ie; -> kfree(old_ie); This double free / kernel panics can be reproduced by using wpa_supplicant with an encrypted mesh (if set up without encryption via "iw" then ifmsh->ie is always NULL, which avoids this issue). And then calling: $ iw dev mesh0 mesh leave $ iw dev mesh0 mesh join my-mesh Note that typically these commands are not used / working when using wpa_supplicant. And it seems that wpa_supplicant or wpa_cli are going through a NETDEV_DOWN/NETDEV_UP cycle between a mesh leave and mesh join where the NETDEV_UP resets the mesh.ie to NULL via a memcpy of default_mesh_setup in cfg80211_netdev_notifier_call, which then avoids the memory corruption, too. The issue was first observed in an application which was not using wpa_supplicant but "Senf" instead, which implements its own calls to nl80211. Fixing the issue by removing the kfree()'ing of the mesh IE in the mesh join function and leaving it solely up to the mesh leave to free the mesh IE.

CVE Informations

Related Weaknesses

CWE-ID	Weakness Name	Source
CWE-415	Double Free The product calls free() twice on the same memory address.

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 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. 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.	nvd@nist.gov

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.

Date	EPSS V0	EPSS V1	EPSS V2 (> 2022-02-04)	EPSS V3 (> 2025-03-07)	EPSS V4 (> 2025-03-17)
2025-02-27	–	–	–	0.04%	–
2025-03-09	–	–	–	0.04%	–
2025-03-18	–	–	–	–	0.04%
2025-03-30	–	–	–	–	0.04%
2025-04-15	–	–	–	–	0.01%
2025-04-15	–	–	–	–	0.01,%

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