CVE-2026-23086 : Detail

CVE-2026-23086

5.5
/
Medium
0.02%V4
Local
2026-02-04
16h08 +00:00
2026-07-14
12h45 +00:00
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CVE Descriptions

vsock/virtio: cap TX credit to local buffer size

In the Linux kernel, the following vulnerability has been resolved: vsock/virtio: cap TX credit to local buffer size The virtio transports derives its TX credit directly from peer_buf_alloc, which is set from the remote endpoint's SO_VM_SOCKETS_BUFFER_SIZE value. On the host side this means that the amount of data we are willing to queue for a connection is scaled by a guest-chosen buffer size, rather than the host's own vsock configuration. A malicious guest can advertise a large buffer and read slowly, causing the host to allocate a correspondingly large amount of sk_buff memory. The same thing would happen in the guest with a malicious host, since virtio transports share the same code base. Introduce a small helper, virtio_transport_tx_buf_size(), that returns min(peer_buf_alloc, buf_alloc), and use it wherever we consume peer_buf_alloc. This ensures the effective TX window is bounded by both the peer's advertised buffer and our own buf_alloc (already clamped to buffer_max_size via SO_VM_SOCKETS_BUFFER_MAX_SIZE), so a remote peer cannot force the other to queue more data than allowed by its own vsock settings. On an unpatched Ubuntu 22.04 host (~64 GiB RAM), running a PoC with 32 guest vsock connections advertising 2 GiB each and reading slowly drove Slab/SUnreclaim from ~0.5 GiB to ~57 GiB; the system only recovered after killing the QEMU process. That said, if QEMU memory is limited with cgroups, the maximum memory used will be limited. With this patch applied: Before: MemFree: ~61.6 GiB Slab: ~142 MiB SUnreclaim: ~117 MiB After 32 high-credit connections: MemFree: ~61.5 GiB Slab: ~178 MiB SUnreclaim: ~152 MiB Only ~35 MiB increase in Slab/SUnreclaim, no host OOM, and the guest remains responsive. Compatibility with non-virtio transports: - VMCI uses the AF_VSOCK buffer knobs to size its queue pairs per socket based on the local vsk->buffer_* values; the remote side cannot enlarge those queues beyond what the local endpoint configured. - Hyper-V's vsock transport uses fixed-size VMBus ring buffers and an MTU bound; there is no peer-controlled credit field comparable to peer_buf_alloc, and the remote endpoint cannot drive in-flight kernel memory above those ring sizes. - The loopback path reuses virtio_transport_common.c, so it naturally follows the same semantics as the virtio transport. This change is limited to virtio_transport_common.c and thus affects virtio-vsock, vhost-vsock, and loopback, bringing them in line with the "remote window intersected with local policy" behaviour that VMCI and Hyper-V already effectively have. [Stefano: small adjustments after changing the previous patch] [Stefano: tweak the commit message]

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) 4.8 To (excluding) 6.1.162

Linux>>Linux_kernel >> Version From (including) 6.2 To (excluding) 6.6.122

Linux>>Linux_kernel >> Version From (including) 6.7 To (excluding) 6.12.68

Linux>>Linux_kernel >> Version From (including) 6.13 To (excluding) 6.18.8

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

Linux>>Linux_kernel >> Version 6.19

References