CVE-2025-68725 : Detail

CVE-2025-68725

5.5
/
Medium
0.01%V4
Local
2025-12-24
10h33 +00:00
2026-07-14
12h44 +00:00
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CVE Descriptions

bpf: Do not let BPF test infra emit invalid GSO types to stack

In the Linux kernel, the following vulnerability has been resolved: bpf: Do not let BPF test infra emit invalid GSO types to stack Yinhao et al. reported that their fuzzer tool was able to trigger a skb_warn_bad_offload() from netif_skb_features() -> gso_features_check(). When a BPF program - triggered via BPF test infra - pushes the packet to the loopback device via bpf_clone_redirect() then mentioned offload warning can be seen. GSO-related features are then rightfully disabled. We get into this situation due to convert___skb_to_skb() setting gso_segs and gso_size but not gso_type. Technically, it makes sense that this warning triggers since the GSO properties are malformed due to the gso_type. Potentially, the gso_type could be marked non-trustworthy through setting it at least to SKB_GSO_DODGY without any other specific assumptions, but that also feels wrong given we should not go further into the GSO engine in the first place. The checks were added in 121d57af308d ("gso: validate gso_type in GSO handlers") because there were malicious (syzbot) senders that combine a protocol with a non-matching gso_type. If we would want to drop such packets, gso_features_check() currently only returns feature flags via netif_skb_features(), so one location for potentially dropping such skbs could be validate_xmit_unreadable_skb(), but then otoh it would be an additional check in the fast-path for a very corner case. Given bpf_clone_redirect() is the only place where BPF test infra could emit such packets, lets reject them right there.

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) 5.6 To (excluding) 5.10.249

Linux>>Linux_kernel >> Version From (including) 5.11 To (excluding) 5.15.199

Linux>>Linux_kernel >> Version From (including) 5.16 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) 6.18.2

References