CVE-2024-26837 : Detail

CVE-2024-26837

4.7
/
Medium
0.04%V4
Local
2024-04-17
10h10 +00:00
2024-12-19
08h48 +00:00
CVE.org
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CVE Descriptions

net: bridge: switchdev: Skip MDB replays of deferred events on offload

In the Linux kernel, the following vulnerability has been resolved: net: bridge: switchdev: Skip MDB replays of deferred events on offload Before this change, generation of the list of MDB events to replay would race against the creation of new group memberships, either from the IGMP/MLD snooping logic or from user configuration. While new memberships are immediately visible to walkers of br->mdb_list, the notification of their existence to switchdev event subscribers is deferred until a later point in time. So if a replay list was generated during a time that overlapped with such a window, it would also contain a replay of the not-yet-delivered event. The driver would thus receive two copies of what the bridge internally considered to be one single event. On destruction of the bridge, only a single membership deletion event was therefore sent. As a consequence of this, drivers which reference count memberships (at least DSA), would be left with orphan groups in their hardware database when the bridge was destroyed. This is only an issue when replaying additions. While deletion events may still be pending on the deferred queue, they will already have been removed from br->mdb_list, so no duplicates can be generated in that scenario. To a user this meant that old group memberships, from a bridge in which a port was previously attached, could be reanimated (in hardware) when the port joined a new bridge, without the new bridge's knowledge. For example, on an mv88e6xxx system, create a snooping bridge and immediately add a port to it: root@infix-06-0b-00:~$ ip link add dev br0 up type bridge mcast_snooping 1 && \ > ip link set dev x3 up master br0 And then destroy the bridge: root@infix-06-0b-00:~$ ip link del dev br0 root@infix-06-0b-00:~$ mvls atu ADDRESS FID STATE Q F 0 1 2 3 4 5 6 7 8 9 a DEV:0 Marvell 88E6393X 33:33:00:00:00:6a 1 static - - 0 . . . . . . . . . . 33:33:ff:87:e4:3f 1 static - - 0 . . . . . . . . . . ff:ff:ff:ff:ff:ff 1 static - - 0 1 2 3 4 5 6 7 8 9 a root@infix-06-0b-00:~$ The two IPv6 groups remain in the hardware database because the port (x3) is notified of the host's membership twice: once via the original event and once via a replay. Since only a single delete notification is sent, the count remains at 1 when the bridge is destroyed. Then add the same port (or another port belonging to the same hardware domain) to a new bridge, this time with snooping disabled: root@infix-06-0b-00:~$ ip link add dev br1 up type bridge mcast_snooping 0 && \ > ip link set dev x3 up master br1 All multicast, including the two IPv6 groups from br0, should now be flooded, according to the policy of br1. But instead the old memberships are still active in the hardware database, causing the switch to only forward traffic to those groups towards the CPU (port 0). Eliminate the race in two steps: 1. Grab the write-side lock of the MDB while generating the replay list. This prevents new memberships from showing up while we are generating the replay list. But it leaves the scenario in which a deferred event was already generated, but not delivered, before we grabbed the lock. Therefore: 2. Make sure that no deferred version of a replay event is already enqueued to the switchdev deferred queue, before adding it to the replay list, when replaying additions.

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 4.7 MEDIUM CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/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.

High

successful attack depends on conditions beyond the attacker's control. That is, a successful attack cannot be accomplished at will, but requires the attacker to invest in some measurable amount of effort in preparation or execution against the vulnerable component before a successful attack can be expected.

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.

None

There is no loss of confidentiality within the impacted component.

Integrity Impact

This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information.

None

There is no loss of integrity within 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.

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

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 5.13 To (excluding) 6.1.80

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.19

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.7.7

Linux>>Linux_kernel >> Version 6.8

Linux>>Linux_kernel >> Version 6.8

Linux>>Linux_kernel >> Version 6.8

Linux>>Linux_kernel >> Version 6.8

Linux>>Linux_kernel >> Version 6.8

References

The information presented on CVE Find originates from several carefully selected reference sources. CVE data is provided by MITRE Corporation and the National Vulnerability Database (NVD). The Known Exploited Vulnerabilities (KEV) catalog is sourced from the Cybersecurity and Infrastructure Security Agency (CISA), while EPSS scores come from FIRST.org. Additionally, data regarding software weaknesses (CWE) and common attack patterns (CAPEC) is maintained by MITRE Corporation, and information on hardware and software configurations (CPE) is provided by the NVD.