CVE-2025-22111 : Detail

CVE-2025-22111

5.5
/
Medium
0.02%V4
Local
2025-04-16
14h12 +00:00
2026-07-14
12h40 +00:00
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CVE Descriptions

net: Remove RTNL dance for SIOCBRADDIF and SIOCBRDELIF.

In the Linux kernel, the following vulnerability has been resolved: net: Remove RTNL dance for SIOCBRADDIF and SIOCBRDELIF. SIOCBRDELIF is passed to dev_ioctl() first and later forwarded to br_ioctl_call(), which causes unnecessary RTNL dance and the splat below [0] under RTNL pressure. Let's say Thread A is trying to detach a device from a bridge and Thread B is trying to remove the bridge. In dev_ioctl(), Thread A bumps the bridge device's refcnt by netdev_hold() and releases RTNL because the following br_ioctl_call() also re-acquires RTNL. In the race window, Thread B could acquire RTNL and try to remove the bridge device. Then, rtnl_unlock() by Thread B will release RTNL and wait for netdev_put() by Thread A. Thread A, however, must hold RTNL after the unlock in dev_ifsioc(), which may take long under RTNL pressure, resulting in the splat by Thread B. Thread A (SIOCBRDELIF) Thread B (SIOCBRDELBR) ---------------------- ---------------------- sock_ioctl sock_ioctl `- sock_do_ioctl `- br_ioctl_call `- dev_ioctl `- br_ioctl_stub |- rtnl_lock | |- dev_ifsioc ' ' |- dev = __dev_get_by_name(...) |- netdev_hold(dev, ...) . / |- rtnl_unlock ------. | | |- br_ioctl_call `---> |- rtnl_lock Race | | `- br_ioctl_stub |- br_del_bridge Window | | | |- dev = __dev_get_by_name(...) | | | May take long | `- br_dev_delete(dev, ...) | | | under RTNL pressure | `- unregister_netdevice_queue(dev, ...) | | | | `- rtnl_unlock \ | |- rtnl_lock <-' `- netdev_run_todo | |- ... `- netdev_run_todo | `- rtnl_unlock |- __rtnl_unlock | |- netdev_wait_allrefs_any |- netdev_put(dev, ...) <----------------' Wait refcnt decrement and log splat below To avoid blocking SIOCBRDELBR unnecessarily, let's not call dev_ioctl() for SIOCBRADDIF and SIOCBRDELIF. In the dev_ioctl() path, we do the following: 1. Copy struct ifreq by get_user_ifreq in sock_do_ioctl() 2. Check CAP_NET_ADMIN in dev_ioctl() 3. Call dev_load() in dev_ioctl() 4. Fetch the master dev from ifr.ifr_name in dev_ifsioc() 3. can be done by request_module() in br_ioctl_call(), so we move 1., 2., and 4. to br_ioctl_stub(). Note that 2. is also checked later in add_del_if(), but it's better performed before RTNL. SIOCBRADDIF and SIOCBRDELIF have been processed in dev_ioctl() since the pre-git era, and there seems to be no specific reason to process them there. [0]: unregister_netdevice: waiting for wpan3 to become free. Usage count = 2 ref_tracker: wpan3@ffff8880662d8608 has 1/1 users at __netdev_tracker_alloc include/linux/netdevice.h:4282 [inline] netdev_hold include/linux/netdevice.h:4311 [inline] dev_ifsioc+0xc6a/0x1160 net/core/dev_ioctl.c:624 dev_ioctl+0x255/0x10c0 net/core/dev_ioctl.c:826 sock_do_ioctl+0x1ca/0x260 net/socket.c:1213 sock_ioctl+0x23a/0x6c0 net/socket.c:1318 vfs_ioctl fs/ioctl.c:51 [inline] __do_sys_ioctl fs/ioctl.c:906 [inline] __se_sys_ioctl fs/ioctl.c:892 [inline] __x64_sys_ioctl+0x1a4/0x210 fs/ioctl.c:892 do_syscall_x64 arch/x86/entry/common.c:52 [inline] do_syscall_64+0xcb/0x250 arch/x86/entry/common.c:83 entry_SYSCALL_64_after_hwframe+0x77/0x7f

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE Other No informations.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 5.5 MEDIUM CVSS:3.1/AV:L/AC:L/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.

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.

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.

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 5.15 To (excluding) 6.14.2

References