CVE-2026-45855 : Detail

CVE-2026-45855

5.5
/
Medium
0.02%V4
Local
2026-05-27
14h16 +00:00
2026-06-25
21h08 +00:00
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CVE Descriptions

In the Linux kernel, the following vulnerability has been resolved: ata: libata-scsi: avoid Non-NCQ command starvation When a non-NCQ command is issued while NCQ commands are being executed, ata_scsi_qc_issue() indicates to the SCSI layer that the command issuing should be deferred by returning SCSI_MLQUEUE_XXX_BUSY. This command deferring is correct and as mandated by the ACS specifications since NCQ and non-NCQ commands cannot be mixed. However, in the case of a host adapter using multiple submission queues, when the target device is under a constant load of NCQ commands, there are no guarantees that requeueing the non-NCQ command will be executed later and it may be deferred again repeatedly as other submission queues can constantly issue NCQ commands from different CPUs ahead of the non-NCQ command. This can lead to very long delays for the execution of non-NCQ commands, and even complete starvation for these commands in the worst case scenario. Since the block layer and the SCSI layer do not distinguish between queueable (NCQ) and non queueable (non-NCQ) commands, libata-scsi SAT implementation must ensure forward progress for non-NCQ commands in the presence of NCQ command traffic. This is similar to what SAS HBAs with a hardware/firmware based SAT implementation do. Implement such forward progress guarantee by limiting requeueing of non-NCQ commands from ata_scsi_qc_issue(): when a non-NCQ command is received and NCQ commands are in-flight, do not force a requeue of the non-NCQ command by returning SCSI_MLQUEUE_XXX_BUSY and instead return 0 to indicate that the command was accepted but hold on to the qc using the new deferred_qc field of struct ata_port. This deferred qc will be issued using the work item deferred_qc_work running the function ata_scsi_deferred_qc_work() once all in-flight commands complete, which is checked with the port qc_defer() callback return value indicating that no further delay is necessary. This check is done using the helper function ata_scsi_schedule_deferred_qc() which is called from ata_scsi_qc_complete(). This thus excludes this mechanism from all internal non-NCQ commands issued by ATA EH. When a port deferred_qc is non NULL, that is, the port has a command waiting for the device queue to drain, the issuing of all incoming commands (both NCQ and non-NCQ) is deferred using the regular busy mechanism. This simplifies the code and also avoids potential denial of service problems if a user issues too many non-NCQ commands. Finally, whenever ata EH is scheduled, regardless of the reason, a deferred qc is always requeued so that it can be retried once EH completes. This is done by calling the function ata_scsi_requeue_deferred_qc() from ata_eh_set_pending(). This avoids the need for any special processing for the deferred qc in case of NCQ error, link or device reset, or device timeout.

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) 5.10 To (excluding) 6.12.77

Linux>>Linux_kernel >> Version From (including) 6.13 To (excluding) 6.18.14

Linux>>Linux_kernel >> Version From (including) 6.19 To (excluding) 6.19.4

References