CVE-2026-43456 : Detail

CVE-2026-43456

7.8
/
High
0.02%V4
Local
2026-05-08
15h16 +00:00
2026-07-24
15h17 +00:00
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CVE Descriptions

In the Linux kernel, the following vulnerability has been resolved: bonding: fix type confusion in bond_setup_by_slave() kernel BUG at net/core/skbuff.c:2306! Oops: invalid opcode: 0000 [#1] SMP KASAN NOPTI RIP: 0010:pskb_expand_head+0xa08/0xfe0 net/core/skbuff.c:2306 RSP: 0018:ffffc90004aff760 EFLAGS: 00010293 RAX: 0000000000000000 RBX: ffff88807e3c8780 RCX: ffffffff89593e0e RDX: ffff88807b7c4900 RSI: ffffffff89594747 RDI: ffff88807b7c4900 RBP: 0000000000000820 R08: 0000000000000005 R09: 0000000000000000 R10: 00000000961a63e0 R11: 0000000000000000 R12: ffff88807e3c8780 R13: 00000000961a6560 R14: dffffc0000000000 R15: 00000000961a63e0 CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 CR2: 00007fe1a0ed8df0 CR3: 000000002d816000 CR4: 00000000003526f0 Call Trace: ipgre_header+0xdd/0x540 net/ipv4/ip_gre.c:900 dev_hard_header include/linux/netdevice.h:3439 [inline] packet_snd net/packet/af_packet.c:3028 [inline] packet_sendmsg+0x3ae5/0x53c0 net/packet/af_packet.c:3108 sock_sendmsg_nosec net/socket.c:727 [inline] __sock_sendmsg net/socket.c:742 [inline] ____sys_sendmsg+0xa54/0xc30 net/socket.c:2592 ___sys_sendmsg+0x190/0x1e0 net/socket.c:2646 __sys_sendmsg+0x170/0x220 net/socket.c:2678 do_syscall_x64 arch/x86/entry/syscall_64.c:63 [inline] do_syscall_64+0x106/0xf80 arch/x86/entry/syscall_64.c:94 entry_SYSCALL_64_after_hwframe+0x77/0x7f RIP: 0033:0x7fe1a0e6c1a9 When a non-Ethernet device (e.g. GRE tunnel) is enslaved to a bond, bond_setup_by_slave() directly copies the slave's header_ops to the bond device: bond_dev->header_ops = slave_dev->header_ops; This causes a type confusion when dev_hard_header() is later called on the bond device. Functions like ipgre_header(), ip6gre_header(),all use netdev_priv(dev) to access their device-specific private data. When called with the bond device, netdev_priv() returns the bond's private data (struct bonding) instead of the expected type (e.g. struct ip_tunnel), leading to garbage values being read and kernel crashes. Fix this by introducing bond_header_ops with wrapper functions that delegate to the active slave's header_ops using the slave's own device. This ensures netdev_priv() in the slave's header functions always receives the correct device. The fix is placed in the bonding driver rather than individual device drivers, as the root cause is bond blindly inheriting header_ops from the slave without considering that these callbacks expect a specific netdev_priv() layout. The type confusion can be observed by adding a printk in ipgre_header() and running the following commands: ip link add dummy0 type dummy ip addr add 10.0.0.1/24 dev dummy0 ip link set dummy0 up ip link add gre1 type gre local 10.0.0.1 ip link add bond1 type bond mode active-backup ip link set gre1 master bond1 ip link set gre1 up ip link set bond1 up ip addr add fe80::1/64 dev bond1

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-908 Use of Uninitialized Resource
The product uses or accesses a resource that has not been initialized.

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) 2.6.24 To (excluding) 6.12.78

Linux>>Linux_kernel >> Version From (including) 6.13 To (excluding) 6.18.19

Linux>>Linux_kernel >> Version From (including) 6.19 To (excluding) 6.19.9

Linux>>Linux_kernel >> Version 7.0

Linux>>Linux_kernel >> Version 7.0

Linux>>Linux_kernel >> Version 7.0

References