CVE-2025-68795 : 詳細

CVE-2025-68795

7.8
/
高
0.05%V4
2026-01-13
15h29 +00:00
Local
2026-10-19
18h05 +00:00
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CVE の説明

ethtool: Avoid overflowing userspace buffer on stats query

In the Linux kernel, the following vulnerability has been resolved: ethtool: Avoid overflowing userspace buffer on stats query The ethtool -S command operates across three ioctl calls: ETHTOOL_GSSET_INFO for the size, ETHTOOL_GSTRINGS for the names, and ETHTOOL_GSTATS for the values. If the number of stats changes between these calls (e.g., due to device reconfiguration), userspace's buffer allocation will be incorrect, potentially leading to buffer overflow. Drivers are generally expected to maintain stable stat counts, but some drivers (e.g., mlx5, bnx2x, bna, ksz884x) use dynamic counters, making this scenario possible. Some drivers try to handle this internally: - bnad_get_ethtool_stats() returns early in case stats.n_stats is not equal to the driver's stats count. - micrel/ksz884x also makes sure not to write anything beyond stats.n_stats and overflow the buffer. However, both use stats.n_stats which is already assigned with the value returned from get_sset_count(), hence won't solve the issue described here. Change ethtool_get_strings(), ethtool_get_stats(), ethtool_get_phy_stats() to not return anything in case of a mismatch between userspace's size and get_sset_size(), to prevent buffer overflow. The returned n_stats value will be equal to zero, to reflect that nothing has been returned. This could result in one of two cases when using upstream ethtool, depending on when the size change is detected: 1. When detected in ethtool_get_strings(): # ethtool -S eth2 no stats available 2. When detected in get stats, all stats will be reported as zero. Both cases are presumably transient, and a subsequent ethtool call should succeed. Other than the overflow avoidance, these two cases are very evident (no output/cleared stats), which is arguably better than presenting incorrect/shifted stats. I also considered returning an error instead of a "silent" response, but that seems more destructive towards userspace apps. Notes: - This patch does not claim to fix the inherent race, it only makes sure that we do not overflow the userspace buffer, and makes for a more predictable behavior. - RTNL lock is held during each ioctl, the race window exists between the separate ioctl calls when the lock is released. - Userspace ethtool always fills stats.n_stats, but it is likely that these stats ioctls are implemented in other userspace applications which might not fill it. The added code checks that it's not zero, to prevent any regressions.

CVE の情報

関連する弱点

CWE-ID 弱点名 出典
CWE-122 Heap-based Buffer Overflow
The product writes past the end of a buffer that was allocated on the heap.

メトリクス

メトリクス スコア 深刻度 CVSS ベクター 出典
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.

EPSS

EPSSは脆弱性が悪用される可能性を予測するスコアリングモデルです。

EPSSスコア

EPSSモデルは0から1(0〜100%)の確率スコアを算出します。スコアが高いほど、脆弱性が悪用される可能性が高いことを示します。

EPSSパーセンタイル

パーセンタイルはCVEをEPSSスコアで順位付けするために使用されます。例えば、EPSSスコアで95パーセンタイルにあるCVEは、他の95%のCVEよりも悪用される可能性が高いことを意味します。パーセンタイルはCVEのEPSSスコアを他のCVEと比較するために使用されます。

参考資料