CVE-2026-46110 : Detail

CVE-2026-46110

7.5
/
High
Memory Corruption
0.06%V4
Network
2026-05-28
10h16 +00:00
2026-06-24
18h28 +00:00
CVE.org
NVD
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CVE Descriptions

In the Linux kernel, the following vulnerability has been resolved: net: stmmac: Prevent NULL deref when RX memory exhausted The CPU receives frames from the MAC through conventional DMA: the CPU allocates buffers for the MAC, then the MAC fills them and returns ownership to the CPU. For each hardware RX queue, the CPU and MAC coordinate through a shared ring array of DMA descriptors: one descriptor per DMA buffer. Each descriptor includes the buffer's physical address and a status flag ("OWN") indicating which side owns the buffer: OWN=0 for CPU, OWN=1 for MAC. The CPU is only allowed to set the flag and the MAC is only allowed to clear it, and both must move through the ring in sequence: thus the ring is used for both "submissions" and "completions." In the stmmac driver, stmmac_rx() bookmarks its position in the ring with the `cur_rx` index. The main receive loop in that function checks for rx_descs[cur_rx].own=0, gives the corresponding buffer to the network stack (NULLing the pointer), and increments `cur_rx` modulo the ring size. After the loop exits, stmmac_rx_refill(), which bookmarks its position with `dirty_rx`, allocates fresh buffers and rearms the descriptors (setting OWN=1). If it fails any allocation, it simply stops early (leaving OWN=0) and will retry where it left off when next called. This means descriptors have a three-stage lifecycle (terms my own): - `empty` (OWN=1, buffer valid) - `full` (OWN=0, buffer valid and populated) - `dirty` (OWN=0, buffer NULL) But because stmmac_rx() only checks OWN, it confuses `full`/`dirty`. In the past (see 'Fixes:'), there was a bug where the loop could cycle `cur_rx` all the way back to the first descriptor it dirtied, resulting in a NULL dereference when mistaken for `full`. The aforementioned commit resolved that *specific* failure by capping the loop's iteration limit at `dma_rx_size - 1`, but this is only a partial fix: if the previous stmmac_rx_refill() didn't complete, then there are leftover `dirty` descriptors that the loop might encounter without needing to cycle fully around. The current code therefore panics (see 'Closes:') when stmmac_rx_refill() is memory-starved long enough for `cur_rx` to catch up to `dirty_rx`. Fix this by explicitly checking, before advancing `cur_rx`, if the next entry is dirty; exit the loop if so. This prevents processing of the final, used descriptor until stmmac_rx_refill() succeeds, but fully prevents the `cur_rx == dirty_rx` ambiguity as the previous bugfix intended: so remove the clamp as well. Since stmmac_rx_zc() is a copy-paste-and-tweak of stmmac_rx() and the code structure is identical, any fix to stmmac_rx() will also need a corresponding fix for stmmac_rx_zc(). Therefore, apply the same check there. In stmmac_rx() (not stmmac_rx_zc()), a related bug remains: after the MAC sets OWN=0 on the final descriptor, it will be unable to send any further DMA-complete IRQs until it's given more `empty` descriptors. Currently, the driver simply *hopes* that the next stmmac_rx_refill() succeeds, risking an indefinite stall of the receive process if not. But this is not a regression, so it can be addressed in a future change.

CVE Informations

Related Weaknesses

CWE-ID Weakness Name Source
CWE-476 NULL Pointer Dereference
The product dereferences a pointer that it expects to be valid but is NULL.

Metrics

Metrics Score Severity CVSS Vector Source
V3.1 7.5 HIGH CVSS:3.1/AV:N/AC:L/PR:N/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.

Network

The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).

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.

None

The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an attack.

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.

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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.
EPSS First.org

Products Mentioned

Configuraton 0

Linux>>Linux_kernel >> Version From (including) 6.1.64 To (excluding) 6.1.176

Linux>>Linux_kernel >> Version From (including) 6.5.13 To (excluding) 6.6

Linux>>Linux_kernel >> Version From (including) 6.6.3 To (excluding) 6.6.140

Linux>>Linux_kernel >> Version From (including) 6.7.1 To (excluding) 6.12.88

Linux>>Linux_kernel >> Version From (including) 6.13 To (excluding) 6.18.30

Linux>>Linux_kernel >> Version From (including) 6.19 To (excluding) 7.0.7

Linux>>Linux_kernel >> Version 6.7

Linux>>Linux_kernel >> Version 6.7

Linux>>Linux_kernel >> Version 6.7

Linux>>Linux_kernel >> Version 6.7

Linux>>Linux_kernel >> Version 6.7

Linux>>Linux_kernel >> Version 6.7

Linux>>Linux_kernel >> Version 6.7

Linux>>Linux_kernel >> Version 6.7

Linux>>Linux_kernel >> Version 7.1

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.